This use case is from South London Partnership – InnOvaTe “IoT” Project.
Outcome
To support local business growth and improve business rates retention through equipping small businesses with digital tools and support.
Sectors
Local authority, Business Improvement District (BID), High Street team, public sector.
Key Stakeholders
Mayor of Croydon, various local business districts i.e. South Norwood, Purley and Thorton Heath, local businesses, High Street team.
Overview
The creation of “digital town hubs”, made accessible via a smartphone app for residents and businesses in three high streets in the Croydon borough, namely: South Norwood, Purley, and Thornton Heath enabling direct engagement with residents/customers/visitors to the town centre to promote their businesses, and to provide information about local traffic, construction, re-routing, as well as local events and offers in real time. The hubs promoted local businesses, events and offers to residents with the primary idea being to drive back local spend into the independent shops. South Norwood and Purley were supported by the Croydon High Street teams, whereas Thornton Heath was supported by the supplier directly.
The project sits as part of Croydon Council’s strategic vision for Digital Place and was accelerated by the impacts of the pandemic which clarified the need for a real-time digital platform to enable businesses and residents to engage locally.
About the Author
The InnOvaTe Programme is an Internet of Things initiative by South London Partnership (SLP) to “pilot and research” IoT across the 5 London boroughs of Croydon, Merton, Richmond upon Thames, Sutton, and the Royal Borough of Kingston upon Thames. The programme looks at ways to generate economic growth, support local businesses, help people live better, healthier lives and assist with addressing the climate emergency. The project assessed 150 IoT ideas for the councils concerned, implementing 48 of them successfully over 18 months. The programme was formally completed in March 2023.
Case Study Challenge
Many businesses in South Norwood, Purley, and Thornton Heath lacked digital engagement platforms, making it difficult for them to reach and retain customers during and after the pandemic. The project intended to increase local spending in independent shops and promote economic recovery in secondary business districts in need of regeneration. The digital hubs were designed to foster a stronger sense of community by providing real-time information on local events, offers, traffic, and construction, thereby connecting residents, businesses, and visitors. The initiative aimed to collect and use local data to support local authorities and businesses, providing insights that could drive decision-making and enhance the overall well-being of the community.
Use Case Design Objectives
The targeted areas were secondary business districts in need of regeneration. For example, in South Norwood, only 70 of the 190 local businesses have any online presence at all. This scheme can therefore truly open up access for these businesses to a wider local audience, which will hopefully drive significant engagement that would otherwise be unobtainable.
Some objectives of the project included:
Commissioning (budget/procurement)
A tender (RFQ) opportunity was run in February 2021. Loqiva was awarded as the winning supplier with an overall cost in the range of £100,000 to £200,000, with the contract lasting for an initial period of one year.
Deployment (what / who / where / how long)
All three Croydon based town hubs in South Norwood, Purley, and Thornton Heath, were live as of January 2022, and sensor installation progressed well. Croydon staff had access to the dashboards. The goal at the time of launching was 20 businesses per hub. Within the scope of the trial, they managed to have more than 25 businesses signed up, and more than 2,000 app downloads. The aim was to hit 1,000 app downloads per site target. The pilot ran until the end of 2022.
Technology Implemented
Implementation of LoRaWAN enabled footfall sensors, combined with an online engagement portal.
Results / Key Findings
Loqiva, the supplier, provided significant support to businesses, helping them understand and utilise the digital platform. Regular check-ins and support were essential, particularly for digitally inexperienced business owners.
It generally took three to four visits for businesses to appreciate the potential benefits, highlighting the importance of building trust through consistent engagement. The presence of council officers alongside Loqiva representatives helped reduce reluctance from local businesses.
Council officers were pleased with the progress and outcomes of the pilot. The trial saw over 25 businesses sign up and more than 2,000 app downloads, nearly meeting the target of 1,000 downloads per site.
Awareness of the app spread through social media, word of mouth, and direct outreach by staff. The involvement of the Poet Laureate, who created promotional videos, also added credibility and visibility.
Post-trial, the project transitioned to a zero-finance contract, with Loqiva maintaining the platform independently. The council facilitated introductions to potential new regions for Loqiva to expand.
The app facilitated connections between businesses and the community, offering opportunities for network building. Features such as direct messaging and potential payment integration were under development to enhance functionality.
Footfall sensors and the app’s engagement data provided valuable insights. Businesses could access anonymized heat maps and demographic information, allowing them to push geo-fenced alerts and offers to nearby customers.
Many small business owners initially lacked digital literacy and were sceptical about the technology, fearing surveillance. One-on-one interactions were crucial for building rapport and encouraging participation. The trial’s success demonstrated its potential for other regions. Loqiva’s expansion across the UK, including the Outer Hebrides, underscores the interest in and usefulness of such digital platforms for local communities.
In summary, the initiative successfully demonstrated how digital tools could support local businesses, enhance community engagement, and drive economic recovery, particularly in the wake of the COVID-19 pandemic. The project’s ability to build trust, provide consistent support, and offer valuable data insights were key to its success.
Benefits / Usefulness of Data
The data collected primarily from footfall sensors installed in local businesses and through the mobile app was instrumental in driving engagement and providing valuable insights. Key benefits included:
Lessons Learned
The project revealed several important lessons:
Conclusion
The trial was deemed highly successful, marking a significant achievement as the largest initiative of its kind in the UK. It successfully connected residents with local businesses, fostering community ties that were crucial post-COVID-19. The engaged businesses benefited greatly, and the project’s success inspired other councils to adopt similar digital platforms. Loqiva’s expansion across the UK, including remote areas like the Outer Hebrides, underscores the widespread interest and potential impact of such initiatives. The project highlighted the importance of consistent support, digital literacy, and community engagement in driving economic recovery and growth.
Photos from the use case
Contact
For further information, please contact the service leads involved in this project, listed below.
Asha Kanhai
Digital Services Project Lead
London Borough of Croydon
Asha.Kanhai@croydon.gov.uk
Pierre Venter
IoT Delivery Manager
Royal Borough of Kingston and London Borough of Sutton
pierre.venter@sutton.gov.uk
This use case is from South London Partnership – InnOvaTe “IoT” Project.
Outcome
Using sensors to monitor wildlife corridor conservation sites to help identify biodiversity changes within Richmond and Kingston to inform how the council manages council-owned land.
Sectors
Local authority, Green and climate change teams
Key Stakeholders
BioDiversity Team, Institute of Zoology – Zoological Society of London (ZSL), Data Team, Environment team
Overview
The South London Partnership (SLP) designed an Internet of Things (IoT) trial to capture wildlife data in conservation sites to help identify biodiversity changes within Richmond and Kingston. Utilising the remote sensing methods, officers investigated species richness and activity on key wildlife corridors. A video about the study was posted on Kingston Council’s YouTube account.
About the Author
The InnOvaTe Programme is an Internet of Things initiative by South London Partnership (SLP) to “pilot and research” IoT across the 5 London boroughs of Croydon, Merton, Richmond upon Thames, Sutton, and the Royal Borough of Kingston upon Thames. The programme looks at ways to generate economic growth, support local businesses, help people live better, healthier lives and assist with addressing the climate emergency. The project assessed 150 IoT ideas for the councils concerned, implementing 48 of them successfully over 18 months. The programme was formally completed in March 2023.
Case Study Challenge
In 2021, Richmond and Kingston Councils embarked on a mission to revitalise their approach to nature recovery, with a particular focus on the Sites of Importance for Nature Conservation (SINC). This initiative included a comprehensive resurvey of the flora and habitats within these sites, a process not undertaken since the early 1990s. The goal was to integrate this new data with additional information to create a strategy that enhanced site connectivity, bolstered climate change resilience, and prioritised actions for habitats and species. To support this strategy, the councils considered the implementation of IoT connected cellular camera traps. These advanced devices offer significant advantages over traditional non-connected technology by providing real-time data for immediate analysis and response. Strategically placed in various quiet locations across the borough, these camera traps capture static images triggered by movement. The images are then uploaded to the cloud, enabling analysis by officers, community groups, volunteer citizen scientists, and the Institute of Zoology using machine learning technology.
Use Case Design Objectives
This trial is part of the councils’ efforts to update biodiversity information with more accurate and current data on local species. Traditionally, data was collected manually through surveys. The new data will be used to improve conservation efforts and address gaps in knowledge about the functionality and health of the boroughs’ wildlife corridors.
The use of sensing camera technology will enhance research methods by allowing the assessment of wildlife presence and health. Stationary devices placed throughout habitats enable officers to observe cryptic species and their behaviours without direct human interference, which can alter animal activity. Additionally, the capability to remotely send data reduces human effort and facilitates extensive investigations over larger geographical and temporal scales than previously possible.
The primary aim of this use case is to confirm the presence of target species, which will inform how the council manages council-owned land. For connecting lands between sites that are not council-owned, the council can advocate for the animals with landowners or offer to manage the land with the owner’s permission. Furthermore, if the data allows, officers aim to determine the population status of each species and identify which sites are most active and important to these key species.
Commissioning (budget/procurement)
This project was facilitated through the expansion of an existing relationship with the Institute of Zoology (IoZ). The budget range for this trial was less than £50K and lasted a year.
Deployment (what / who / where / how long)
In Richmond, the cameras were set up in small clusters in selected locations for 3-4 week deployments. There was a minimum of nine deployments of at least 20 cameras undertaken between autumn 2021 to autumn 2022. Three weeks was sufficient to gather information on the species present or migrating at a location, whilst avoiding significant duplication of data.
The Institute of Zoology managed four of these deployments, from camera set-up through to analysis of the data, using their self-developed automated image recognition using machine learning technology. Officers and citizen scientists managed the other deployments. The cameras were placed wherever it was needed to capture images of passing wildlife. This then built up a picture of which species were present in the monitored areas, and gave an indication of relative species abundance.
The Kingston team conducted surveys using state of the art wildlife cameras deployed across various sites in 53 locations, from April to August 2023, capturing animal activity throughout nature reserves in the borough of Kingston. Kingston council staff, working with the London HogWatch Project, as well as volunteers, facilitated camera placement using GPS coordinates generated by a computer and Google MyMaps. All cameras were in place for around 2 weeks per site.
Cameras were set to trigger and take a photo every second if an animal entered the detection zone of the camera. Use of infrared flash meant cameras could also be active at night. To ensure even coverage of each site and to align the Random Encounter Model 7 protocol, cameras were placed as close as possible to a predetermined grid pattern. All species in a 24-hour period which triggered the camera were ‘tagged’. The processed data was then used to calculate trapping rates (amount of sightings/number of nights the camera was active) for each site and species.
Early indications from the cameras in the field (from which photos can be manually extracted) produced an average of around 30 images per day. The cameras were set on a three-shot multiple mode to increase the chances of getting a clear shot of the animal. As most wildlife activity is in the lowest traffic areas, this is where the cameras were deployed as a priority. Cameras were moved monthly depending on data needed for specific projects as well as to cover the expanse of land that data is sought for. At busier times of year for animal activity, as little as two weeks might be enough to determine the presence or absence of a species and a rudimentary analysis of relative abundance.
Technology Implemented
The suppliers of the sensors were provided by Wildlife Future Outdoors Ltd. The trial deployed a number of wildlife cameras and motion sensors connected to a cellular adapter. The motion sensor detected movement and triggered the camera to take images. The cellular adapter then transmitted the image data back to a dashboard in the cloud, tagged with date, time, and location data. The data was then accessed by the Zoological Society of London (ZSL). Images were manually tagged by their team and their volunteers. The manual identification was then fed back to the data processors so the AI could “learn” to identify different species based on this information, ultimately taking over the process of identification entirely.
Although there are all-in-one units that combine the camera and cellular technology in one device, the image resolution is typically of a lower quality. Officers decided to buy a good camera and then a separate universal cellular adapter which is attached to it and holds the memory card. These items come from different manufacturers. Kingston used Browning Strike Force Pro camera traps.
Results / Key Findings
Overall, the results of the data generated were positive. One of the species of greatest interest was a protected species. Sensors were finding more animals of this species than expected. The trials gathered data from 220 camera placements between the spring and early winter. Images of hedgehogs, a bathing kingfisher, grass snake, the rare water rail bird and a muntjac deer with young, were all captured. Data collected from the Kingston surveys enabled the calculation of trapping rates for different species at each site. Additionally, various mammal and bird species were recorded, including those of conservation concern.
Benefits / Usefulness of Data
The Richmond trial sought to gather information on the presence or absence of key species in the area, to inform plans for the management of council-owned land. A good number of various mammal and bird species were recorded, including those of conservation concern.
Kingston concluded that this was the most comprehensive wildlife camera survey that has ever been conducted in the borough, and will inform conservation management of our nature reserves in the future. One of the largest insights was as to the scale of dog disruption to animals and how with considered fencing there could be a dramatic reduction in dogs interfering in areas that the Council wish to encourage biodiversity for all the reasons noted previously.
Lessons Learned
It was clear that officer engagement is imperative. Placement, and quality, of the cameras is crucial. Significant time could also be saved by using AI to support data processing.
Conclusion
The South London Partnership’s IoT trial has proven to be a significant step forward in monitoring and conserving biodiversity within Richmond and Kingston. By leveraging advanced camera and sensor technologies, the project provided real-time data on local wildlife, which was previously challenging to obtain through traditional methods. The deployment of cellular camera traps allowed for extensive monitoring with minimal human interference, capturing valuable insights into species presence, abundance, and behaviour across key conservation sites.
The collaboration between local authorities, the Institute of Zoology, and volunteer citizen scientists was instrumental in the project’s success. The data collected not only highlighted the presence of protected and cryptic species but also shed light on the impact of human activities, such as dog disruptions, on wildlife. This information is crucial for shaping future conservation strategies and land management practices.
Overall, the IoT initiative has demonstrated the potential of technology in enhancing environmental conservation efforts. The positive outcomes, including the identification of key species and the generation of comprehensive wildlife data, underscore the project’s value in promoting biodiversity and resilience against climate change. This case study serves as a model for other regions looking to integrate IoT solutions into their environmental monitoring and conservation programs.
Photos from the use case
Contact
For further information, please contact the service leads involved in this project, listed below.
Elliot Newton
Biodiversity Officer
Royal Borough of Kingston
elliot.newton@kingston.gov.uk
Bethany Pepper
Programme and Policy Lead (Climate Change and Sustainability)
London Borough of Richmond
bethany.pepper@richmondandwandsworth.gov.uk
Rebekah Brown
Business Analyst
Royal Borough of Kingston
rebekah.brown@kingston.gov.uk
Pierre Venter
IoT Delivery Manager
Royal Borough of Kingston and London Borough of Sutton
pierre.venter@sutton.gov.uk
This use case is from South London Partnership – InnOvaTe “IoT” Project.
Outcome
Road users and air quality monitoring has provided detailed insights into vehicular, cycling, and pedestrian patterns which has not only improved traffic management and road safety, but provided insights into air policy implications in residential areas, supported strategic planning and helped respond to Freedom Of Information requests and council member enquiries.
Sectors
Local authority, Highways, Transport, Air Quality, Public Realm, Public Sector.
Key Stakeholders
Highways Team, Parks Team, Air Quality, Strategic Transport Team, Data Team, Environment Team, GLA, TfL.
Overview
Data captured by IoT Sensors from across the urban landscape about vehicles, pedestrians, cyclists, buses, journey times, air quality, cycle congestion and footfall across the public realm, has helped generate new insights. Previously siloed data was ingested from various systems and applications into a centralised data platform where it was overlaid with other data sources and transformed to provide actionable insights for urban planning, traffic regulation, and environmental protection.
About the Author
The InnOvaTe Programme is an Internet of Things initiative by South London Partnership (SLP) to “pilot and research” IoT across the 5 London boroughs of Croydon, Merton, Richmond upon Thames, Sutton, and the Royal Borough of Kingston upon Thames. The programme looks at ways to generate economic growth, support local businesses, help people live better, healthier lives and assist with addressing the climate emergency. The project assessed 150 IoT ideas for the councils concerned, implementing 48 of them successfully over 18 months. The programme was formally completed in March 2023.
Case Study Challenge
Confronted with challenges like rising traffic congestion, deteriorating air quality, and the need for safer pedestrian pathways, a number of boroughs were willing to deploy sensors to capture data points relating to these aspects so that new insights could be generated. The goal was to employ a number of IoT solutions to gather nuanced insights into urban dynamics, thereby enabling smarter, data-driven governance to support decision-making at a strategic level. All use cases started with a problem statement, rather than focussing on the technology – this allowed for suitable solutions to be designed to resolve challenges, rather than focussing on the technology itself.
Use Case Design Objectives
The project aimed to use IoT for real-time monitoring of traffic flow, various road users including cyclists and pedestrians, air quality (near schools), and footfall in parks and busy streets. The objective was to gain insights for improving road safety, reducing pollution, and enhancing public space utilisation. The following types of questions were asked:
The goal of each use case eas to ascertain if there is indeed a problem and then subsequently:
Commissioning (budget/procurement)
A number of competitive tender processes took place in 2021 and 2022 for various services related to this case study, with the primary procurement vehicle being the Crown Commercial Services (CSS) Spark framework. Use cases ranged from £10,000 to £300,000 typical supplier cost per use case.
Deployment (what / who / where / how long)
Deployment involved the installation of various types of sensors in key locations by specialised teams. Traffic sensors were typically installed by Vivacity Labs on lamp columns across the boroughs once Street Lighting teams provision power via commando sockets. Air quality monitors were placed near schools to gauge pollution levels and devise health-protective strategies. Footfall sensors in parks provided data on public space usage. The deployment spanned several months, involving local councils and technology providers.
Technology Implemented
Traffic sensors offered detailed analytics on vehicle, cycle, and pedestrian movement (VivaCity Labs). Air quality monitors assessed pollutants to inform health-focused urban policies (Breathe London). Footfall sensors captured park and street usage patterns, influencing planning and maintenance (North Tech).
Results / Key Findings
Traffic sensors provided detailed data on movement patterns, leading to more improvements made to traffic management – this has specifically supported journey time improvements on high congestion routes, baselines for future changes, and utilising road user path data for decision making when considering new pedestrian crossings. Air quality monitors revealed insights that were used to understand the real impact of policy changes, especially around schools and cycle lanes – this combined with traffic data provided evidence to support schemes and policy changes. Insights obtained provided to Community Safety new facts to guide changes and improvements to traffic flow. Following the lifting of restrictions, evidence was obtained using footfall data to identify if there has been a ‘bounce back’ in the months following. Footfall sensors highlighted usage patterns in parks and streets to assist in optimising cleaning routine and prioritise high usage areas. Kingston had very limited data about the use of its cycle infrastructure – data was generated successfully to confirm the number of cyclists using these pathways and when they are travelling, which direction they are going, possible routes for expansion, how congested the routes were and if there was any unauthorised usage of the spaces by mopeds and other vehicles. These insights have significant implications to obtaining new investment in cycling infrastructure and are very beneficial to those who need to make investment decisions.
Benefits / Usefulness of Data
Traffic data led to optimised road safety measures and congestion management. Air quality data informed policies for health protection in school areas – this was especially innovative as the overlaying of air quality data with traffic data gave unique insights into understanding the impact on pedestrians at various times of the day. Data captured has been invaluable for understanding pollution at a very detailed level, i.e. number of pedestrians who were present outside a specific school, with accompanying traffic and air quality data to match. We could also see how those levels change in response to traffic volumes, vehicle types and interventions made by the council, helping to influence and inform future decision making. Public space usage data aided in better park management and urban planning. Data was captured during Covid Lockdowns which assisted in preparing for people returning to the public realm. Large volumes of data provided new insights into longer time-frame patterns for footfall, vehicle types/counts, journey paths and journey times.
Lessons Learned
Emphasised the importance of multi-disciplinary collaboration, the value of real-time data for proactive management, and the necessity for ongoing technological adaptation. Council staff confirmed that the quantity of information was beneficial, especially as this data would take hours to manually capture and would not be as accurate. The challenge experienced was around reporting – generating outputs that specifically met business needs was difficult and often involved a lot of data manipulation. Data anomalies did often occur and needed investigation, e.g. a mobility scooter driving through a pedestrian underpass under the A3 was mistaken for black cab, however these occurrences did reduce over time as the system learned and improved its visual recognition. Data generated was very useful to support ideas for developing new schemes. Data is also used for defending schemes and if TfL requests justifications for road layouts, and helps explain road changes, and supports with funding bids. Interestingly, overhanging trees were often a cause for sensors not capturing data, and this required sensor adjustment or a team to be sent to remove the offending branches. Finally, lack of engagement from data users typically meant the data was not fully utilised – preventing positive outcomes from being captured, despite data being made available to achieve this.
Conclusion
This case study demonstrates the significant role that IoT can play in capturing data pertaining to modern urban environments. The insights gained from this project have provided data insights to a number of different council teams which has aided decision-making at a strategic level.
Photos from the use case
Contact
For further information, please contact the service leads involved in this project, listed below.
Chris Smith
Team Leader – Design and Delivery, Highways
Royal Borough of Kingston
chris.smith@kingston.gov.uk
Paul Garside
Senior Travel Planner
London Borough of Sutton
paul.garside@sutton.gov.uk
Jason Andrews
EH Pollution Manager (Air Quality)
London Boroughs of Merton
Jason.Andrews@merton.gov.uk
Helen Millier
Senior Sustainable Transport Officer
Royal Borough of Kingston
helen.millier@kingston.gov.uk
Mark Dalzell
Head of Neighbourhood Services
London Borough of Sutton
mark.dalzell@sutton.gov.uk
Liam Swaffield
Community Safety
London Borough of Sutton
liam.swaffield@sutton.gov.uk
Sean Gillen
Corporate Head of Employment, Skills and Enterprise
Royal Borough of Kingston
sean.gillen@kingston.gov.uk
Heather Evans
Economic Renewal and Regeneration
London Borough of Sutton
heather.evans@sutton.gov.uk
Pierre Venter
IoT Delivery Manager
Royal Borough of Kingston and London Borough of Sutton
pierre.venter@sutton.gov.uk
This use case is from South London Partnership – InnOvaTe “IoT” Project.
Outcome
Using sensors to monitor ASB (anti-social behaviour), and areas where action may be required to avert accidents or situations developing, by putting in preventative measures.
Sectors
Local authority, Highways, Public Realm, Regeneration,
Key Stakeholders
Highways Team, Community Safety, Business Improvement Districts
Overview
The South London Partnership (SLP) designed a number of Internet of Things (IoT) trials with the goal to capture data that could be used to reduce or prevent anti-social behaviour occurring in a number of locations in the borough. The problems being considered were illegal parking; car park barriers being opened without authorisation; traffic infringements such as no left or right turn junctions and on one-way streets; unauthorised motorbikes and mopeds; illegal entry to void properties. Trials were carried out across Kingston, Sutton and Croydon.
About the Author
The InnOvaTe Programme is an Internet of Things initiative by South London Partnership (SLP) to “pilot and research” IoT across the 5 London boroughs of Croydon, Merton, Richmond upon Thames, Sutton, and the Royal Borough of Kingston upon Thames. The programme looks at ways to generate economic growth, support local businesses, help people live better, healthier lives and assist with addressing the climate emergency. The project assessed 150 IoT ideas for the councils concerned, implementing 48 of them successfully over 18 months. The programme was formally completed in March 2023.
Case Study Challenge
A number of discrete IoT trails were deployed, each aiming to address a specific challenge.
Use Case Design Objectives
Sensors were strategically installed in various locations, including car parking spaces; car park barriers; lampposts; main entrances in different areas such as Beddington Park; parks with car park barriers; streets with illegal turns; illegal motorbike use; void properties. The purpose was to gather data on unexpected activities, and infringement issues. This data helped officers deter illegal activities, investigate infringements promptly, and monitor vacant properties to prevent unauthorised access and potential hazards like flooding or fire damage.
Commissioning (budget/procurement)
A number of competitive tender processes took place in 2021 and 2022 for various services related to this case study, with the primary procurement vehicle being the Crown Commercial Services (CSS) Spark framework. The budget range for all of these trials was less than £50K each, and most lasted a year, or just under.
Deployment (what / who / where / how long)
The following points highlight the various deployment approaches used in each of the related use cases. Most trials were run for 12 months or less:
Technology Implemented
A number of different IoT solutions were implemented:
Results / Key Findings
Benefits / Usefulness of Data
All trials produce new data which was not available to the service previously. This in itself added stakeholders in strategic decision-making which was very beneficial. New data generated has allowed improvements to be made to a number of council operations as well as changes to policies. Data from the illegal left turn/right turn & one-way streets sensors revealed high infringement levels, enabled the council to identify where to strategically place enforcement cameras and coversley where the problem was insufficient in scale to merit action. The data assisted in identifying problematic areas and improving signage. Further the data enabled Council Officers to respond factually to members of the Public, MP’s and Cllrs when challenged with statements such as ‘there are hundreds of offences a day’. This was very helpful as it removed subjectivity and enabled a pure focus on facts and then in turn decisions.
Officers planned to expand the trial and obtain funding for more sensors, but concerns about data accessibility arose, requiring improvement in the data dashboard. Unauthorised motorbike access data revealed that peak activity occurred on weekends and school holidays, and cold weather reduced motorbike activity. This enabled Sutton Council to allocate funding to install motorbike inhibitor gates at specific locations based on sensor data. As a result of this success, the scheme extended to the neighbouring borough, Croydon. Void Properties monitoring initially showed no illegal access, serving as a successful preventive measure, however the sensors did detect an intruder on one occasion which validated the benefits of the use case. Additionally, it unintentionally allowed contractor monitoring to take place which assisted in giving the service more contract monitoring insights into services being delivered to the council.
Lessons Learned
A number of discrete lessons learned have been identified. Generally, it was noted that using discrete sensors for a specific purpose was more useful than sensors that captured a large amount of data. Connectivity played a big role in the success of the use case, as this did cause sensors to go offline which impacted data collection. This was mitigated by working with connectivity providers to boost the signal and ensure all sensors had sufficient coverage for the duration of the trial. It was also discovered that some sensors were insufficiently robust enough to handle the requirements of the use case. This unfortunately meant the pausing and even halting of a number of trials as suppliers were then required to make improvements to their solutions. Trials needed to be implemented for a significant amount of time (often months) in order to capture the necessary data.
Cross-referencing data points with other sensors was useful to confirm sensor data reliability during this period of settling in. Some trials experienced inaccuracies in data capture which required refinements to be made to the sensors themselves. For example; changes in lenses / realignment, or even improvements to machine-learning algorithms to better identify objects due to mis-classification. Regarding alerting, changes to tolerances were needed to ensure officers were only alerted when real events had taken place. This required many iterations and changes, which the supplier was often very willing to assist with.
Conclusion
In various trials, IoT sensors have proven to be successful tools for addressing different ASB issues. In general, residents and council officers were supportive of sensor installations, which provided valuable data on park usage, car park occupancy, and cafe popularity. Car park barrier trials led to a change in Council policy, revealing frequent truck damage and prompting the installation of CCTV for insurance claims. Trials for monitoring illegal turns and one-way streets provided objective data to address traffic violations effectively, with potential enforcement measures. During the monitoring of the open space for illegal motorbike usage other unauthorised caravan incursions were identified and because they were spotted so quickly action could be taken before significant damage or fly tipping had occurred thus saving the Council a considerable sum of money. Finally, sensors in void properties proved cost-effective, renewing for another year, and offering flexibility for relocation when needed. Again these were able to alert staff to break ins at the earliest opportunity thus preventing large scale damage or theft of materials such as copper which can result in flooding or significant interruption of services to neighbours.
Photos from the use case
Contact
For further information, please contact the service leads involved in this project, listed below.
Mark Dalzell
Head of Neighbourhood Services, Environment, Housing and Regeneration
London Borough of Sutton
mark.dalzell@sutton.gov.uk
Liam Swaffield
Technical and Infrastructure Manager, Environment, Housing and Regeneration
London Borough of Sutton
liam.swaffield@sutton.gov.uk
Liz Bishop
Neighbourhood/Estate Management Client Lead, Cambridge Road Estate
Royal Borough of Kingston
liz.bishop@kingston.gov.uk
Lewis Kelly
London Borough of Croydon
Lewis.Kelly@croydon.gov.uk
Pierre Venter
IoT Delivery Manager
Royal Borough of Kingston and London Borough of Sutton
pierre.venter@sutton.gov.uk
This use case is from DG Cities.
Outcome
The main outcome of the project is a greater understanding of conditions in our housing stock and a wealth of data relating to conditions that lead to damp and mould. By gaining access to this data we have been able to monitor conditions in homes over time, without relying on costly and time consuming in-person visits that has the potential to add efficiency to local authority housing divisions. We are able to understand how conditions change over time and identify key trends in the data.
In addition to key trends, by combining data from damp and mould sensors with existing datasets on housing age and archetypes, we can start to identify specific problems that are shared by properties of a similar age and building type. This information can help housing departments to make assumptions about different housing types that is supported by data. For example, we find similar issues across the majority of solid brick homes which is useful when designing different interventions. As well as identifying issues and potential interventions, damp and mould sensors allow us to monitor the performance of homes before and after interventions are put in place, which allows us to effectively evaluate the impact of interventions and make recommendations for scale-up. This is key in building and developing business cases for organisations.
Finally, we found that access to this data improves the way in which we are able to engage with residents around damp and mould. We can understand how both structural and behavioural components can increase the risk of damp and mould in properties, and work with residents to identify different solutions. The data also provides evidence, which is effective in delivering different messaging to residents.
Sectors
Local authority, Housing, Temporary Accommodation, Public Sector, Social Housing
Key Stakeholders
Damp and Mould, Repairs and Investment, Housing and Safer Communities
Overview
In 2022 DG Cities approached Royal Greenwich with a recommendation to test the potential of IoT sensors to improve the delivery of their damp and mould response. We designed a trial programme for 160 council homes, with the aim of testing the benefits of environmental sensors and building a business case for their use, focusing on evaluation and analysis.
Following our market assessment, we opted for AICO environmental sensors, outlining their product and offer to council officers. DG Cities designed and managed the pilot project, working closely with council officers to understand internal processes and identify areas for improvement, as well as engaging closely with AICO to maximise the value of data insights.
About the Author
DG Cities is an innovation company owned by Greenwich Council. DG Cities has a wealth of experience and expertise in delivering public sector projects and working with local authorities and central government bodies, such as the Royal Borough of Greenwich, Hackney Council, Department for Energy Security and Net Zero, OFGEM and UKRI. DG Cities sits at the interface between local government and business, allowing us to make the connection between innovative technological solutions and real-world problems.
Case Study Challenge
How can IoT be used in social housing to complement existing damp and mould processes, and encourage a shift away from reactive repairs, to pro-active?
Use Case Design Objectives
The project was designed to be implemented in social housing, in line with the Council’s priorities around damp and mould. The goal was to assess the viability of sensors in supporting the transformation of the council’s approach to damp and mould, and the potential to move to a more pro-active strategy.
Commissioning (budget/procurement)
The Royal Borough of Greenwich Council commissioned DG Cities, its innovation company, to research, develop, manage, implement and evaluate the use of environmental sensors in Council homes with a history of damp and mould. Following as assessment of alternative options currently available AICOHomeLink were chosen as the provider of the sensors due to the technical specification of their product, their expertise and reputation, as well as their existing relationship with the Council. Devices were procured in line with the Council’s procurement process, which was led by the Repairs and Investment team in the Housing and Safer Communities division.
Deployment (what / who / where / how long)
500 Environmental sensors were installed in 160 council homes across Royal Greenwich, covering 42 estates. In each home residents were given three environmental sensors to monitor temperature and humidity over time across three different rooms. Installation and initial monitoring has been completed and monitoring over a 12 month has commenced to take account of seasonal variances.
Technology Implemented
AICO Environmental Sensors
Results / Key Findings
We were able to identify damp and mould risk across all 160 properties where devices were installed, ranking properties as Low, Medium and High risk, as well as providing a risk score out of 100.
We were also able to develop an understanding of potential causes of damp and mould, based on the way conditions change in homes over time. The devices provide the council with insights into different components that contribute to damp and mould risk, highlighting structural issues as well as behavioural components. DG Cities found that these insights were useful, but understood the limitations of the tech and found ways to improve the data’s usability with our own analysis, turning it into a more effective tool for the Council and other local authorities. This allowed us to unlock new opportunities and full potential for the use of environmental sensors and develop more cost-effective ways of expanding their use.
Benefits / Usefulness of Data
We found that the devices offered high-level insights into the condition of housing stock, but were less effective in providing actionable insights for a local authority. For example, damp and mould risk scores are a useful way of identifying trends across the housing stock and providing an overall summary of conditions, which can be used to prioritise homes for inspections and repairs. However, this information is not robust enough to inform programmes such as retrofit, or structural repairs, and requires more advanced methods of data analysis and reporting.
The component data, generated by analysing the performance of homes in relation to damp and mould, offers a more detailed insight into homes but falls short of recommending suitable actions to tackle the problem. In identifying these limitations, we provided bespoke data analysis and process mapping to deliver actionable insights to the Council, transforming data from the devices into strategies and programmes, ultimately helping to improve housing conditions and operational efficiency.
Lessons Learned
We found that undertaking additional data analysis is necessary in order to deliver actionable insights to the Council. Our trial showed us that the Council requires additional information in order to act on insights from the devices, including supplementary guidance from damp surveyors and additional data analysis. We found that the devices alone cannot replace existing processes, but rather complement them, and have the potential to add value following detailed consultation with council officers, who can assist in identifying opportunities within their process where the devices can add value.
Due to the cost of installing devices, we learnt that it is not always viable to install environmental sensors on a large scale. As such, we found that combining device data with existing council housing stock data can produce an effective way of identifying conditions in homes without the extensive deployment of sensors. DG Cities conducted bespoke data analysis to identify ways in which device value can be extended across the housing stock. Where a lack of funding can limit the effectiveness of sensors, data analysis performs a key role in realising real benefits at a large scale.
Conclusion
Environmental sensors offer a useful way for local authorities to have 24-hour monitoring of conditions in homes, which is particularly useful in properties that are known to be at risk of damp and mould. In properties with a history of damp and mould issues and repeated visits over time, where there no known cause, environmental sensors can be a useful tool to understand conditions and potential causes of damp and mould. While there are numerous limitations involved in their use, the use of intelligent and well-planned data analysis can add value to existing processes, and act as another tool for local authorities in their management of damp and mould.
Contact
For further information, please contact the service leads involved in this project, listed below.
Balazs Csuvar
Director of Innovation & Net Zero
DG Cities
Balazs.csuvar@dgcities.com
This use case is from South London Partnership – InnOvaTe “IoT” Project.
Outcome
Kingston Council has successfully utilised IoT technology to support improvements to living conditions by proactively identifying and addressing damp and mould concerns in properties.
Sectors
Local authority, Housing, Temporary Accommodation, Public Sector.
Key Stakeholders
Housing Team, Private Landlords, Residential Services.
Overview
Kingston Council has used damp monitoring sensors successfully to track issues in temporary accommodation properties. Due to the large number and variety of properties being used by temporary housing services, it is possible that some of the properties are experiencing damp problems. By monitoring (with tenants permission) the accommodation, data can be collected to persuade landlords to improve the condition of their properties, ultimately for the benefit of the occupants. The purpose of the trial was to quantify the scale of the damp problem in properties which helped to identify and/or trigger site visits and surveys to address immediate treatment, but also identify longer term solutions to problems that reoccur. The council team involved has emphasised that sensors merely spotlight issues rather than solve them, but have helped to prioritise and identify issues early on, especially those issues inherent within some properties rather than the action of any particular tenant. Data obtained from the IoT solution (small battery-powered NB-IoT sensor measuring temperature and humidity levels) has been vital to illustrate the evidence needed to justify access for surveys, or even the need for property owners to address changes in behaviours, or even evidence in response to claims e.g. where the Local authority was being taken to court for disrepair, the sensor data was useful for noting that the resident had not being using the heating and therefore contributing to damp and mould in the property. Data obtained from properties near empty properties also supported large scale decanting. Overall, this solution has supported service improvements and efficiencies, good outcomes for occupants, as well as aided to reduce potential claims where landlords were not meeting legislative requirements.
About the Author
The InnOvaTe Programme is an Internet of Things initiative by South London Partnership (SLP) to “pilot and research” IoT across the 5 London boroughs of Croydon, Merton, Richmond upon Thames, Sutton, and the Royal Borough of Kingston upon Thames. The programme looks at ways to generate economic growth, support local businesses, help people live better, healthier lives and assist with addressing the climate emergency. The project assessed 150 IoT ideas for the councils concerned, implementing 48 of them successfully over 18 months. The programme was formally completed in March 2023.
Case Study Challenge
Damp and mould concerns in properties have risen significantly with a large number of Londoners faced with unhealthy living conditions on a daily basis. Utilising in-home sensors, Kingston Council set out to proactively identify potential issues, prioritise site visits for immediate treatment and long-term solutions, but also obtain data to be used as the basis for further discussions with tenants and landlords. The IoT sensor collects temperature and humidity data, and using smart algorithms to determine mould risk, the solution issues prompt alerting to council officers to spotlight potential issues. This trial was focused on temporary accommodation which yielded insights enabling preventive measures. Results include identifying residents at risk of fuel poverty, preventing condensation, and understanding heating usage’s impact on damp conditions – all of which could be used during formal discussions with tenants and landlords to bring about permanent improvements to these properties. The sensors proved instrumental in addressing property issues before mould growth, enhancing tenant experience, and supporting service improvements.
The council initiated this project in response to upcoming legislative changes and a commitment to improving residents’ health. The proactive stance on damp and mould issues, exacerbated by recent news stories, underlines the urgency of addressing these concerns for tenant health and wellbeing.
Use Case Design Objectives
The primary objective of this project was to proactively enhance the living experiences of tenants by intervening in potential conditions that could lead to damp and mould before issues escalated. Quantifying the scale of the damp problem in properties helped to identify and/or trigger site visits and surveys to address immediate treatment but also identify longer-term solutions to the issues that reoccur. The comprehensive and cost-effective technology used for this project meant that the council could also use the sensors to ensure implemented measures provided the desired outcomes.
Commissioning (budget/procurement)
Towards the end of 2022, a selection of relevant suppliers listed on the Crown Commercial Services (CSS) Spark dynamic purchasing systems (DPS) were invited to tender a competitive process managed by the Sutton Procurement team. The contract was awarded to IoT Solutions Group with a budget range of less than £50,000 and trials typically lasted less than 12 months.
Deployment (what / who / where / how long)
A number of sensors were delivered to residents’ properties and installed in the rooms on concern within a matter of seconds (a plastic tab is simply removed from the back of the device).
Technology Implemented
Adopting IoT in-home sensors for their ability to monitor temperature and humidity, the council aimed to identify at-risk properties efficiently. This approach was part of a broader strategy to ensure healthy living environments and was supported by the successful use of IoTSG’s DORIS care sensors in other contexts. Focusing on temporary accommodation, the council deployed sensors to monitor environmental conditions. Real-time data from these sensors enabled the council to prioritise interventions, leveraging web-based dashboards and weekly status reports for effective monitoring.
Results / Key Findings
This project principally focused on tracking issues in temporary accommodation properties. Once installed, the data collected from these sensors was available on a web-based dashboard, as well as being delivered as weekly red-amber-green status reports. This allowed Temporary Accommodation teams at Kingston Council to prioritise the investigation of those properties most at risk of damp and mould and take preventative measures.
The initiative identified residents at risk of fuel poverty and properties with high humidity, enabling targeted advice and structural improvements. The project’s success in preventing mould growth and enhancing tenant satisfaction underscores the effectiveness of this proactive approach.
The insights from these sensors have enabled Kingston’s Housing Teams to take a proactive approach and address property issues before mould starts to grow. This included identifying residents that they needed to engage with and properties that needed structural improvements.
Further results included:
David Hill, Accommodation Manager for The Royal Borough of Kingston upon Thames, commented on the project:
“These sensors were warmly welcomed to nip problems in the bud before they happened, but also to give us a bigger understanding of what is going on inside properties. The sensors enabled us to identify properties with critical cold and potential for mould, allowing them to go and talk to residents and offer any available support. It’s a wonderful bit of kit; fantastic!”
Benefits / Usefulness of Data
The overall tenant experience was enhanced by ensuring improved living conditions and supporting tenant health and general satisfaction. Additionally, this solution has supported service improvements and efficiencies.
Lessons Learned
This technology has enabled the council to take a proactive, rather than the traditional reactive, approach to tackling homes at risk of damp and mould. The simple single-sensor design means that residents don’t need to do anything, making it super easy for the council to collect data. Using a battery-powered NB-IoT device meant the sensors could be deployed anywhere without having to use the residents power or connectivity. NB-IoT performs better indoors than mobile signal, allowing monitoring of void properties which did give some indication to officers of what a “baseline” (i.e. unheated) property looks like – this aided in analysis later on.
The following case-specific lesson’s were captured:
Conclusion
Kingston Council’s use of this IoT solution has set a new benchmark in tenant services, showcasing how technology can effectively address and prevent common housing issues. This initiative reflects the council’s dedication to proactive, high-quality tenant support.
Photos from the use case
Damp and Mould Sensor
Contact
For further information, please contact the service leads involved in this project, listed below.
David Hill
Accommodation Manager – Housing
Royal Borough of Kingston
david.hill@kingston.gov.uk
Theresa Mayers
Business Assurance Officer – Housing
Royal Borough of Kingston
theresa.mayers@kingston.gov.uk
Pierre Venter
IoT Delivery Manager
Royal Borough of Kingston and London Borough of Sutton
pierre.venter@sutton.gov.uk
This use case is from South London Partnership – InnOvaTe “IoT” Project.
Outcome
This trial consisted of three approaches:
*The ANPR was only used for vehicle classification as it was deemed more acceptable, and gave us the same real data i.e. X cars, Y vans and Z trucks.
This will hopefully lead to enable local decision making to improve the environment and avoid the adverse impacts on health.
Sectors
Highways.
Key Stakeholders
Schools and Highways.
Overview
All five of the SLP boroughs (Croydon, Kingston, Merton, Richmond and Sutton) were keen to run at least one air quality monitoring IoT trial in their borough. The purpose was to either ascertain whether school street schemes are effective in reducing air pollution around schools at key times of the day; to monitor air quality more generally across the boroughs; to combine data from air quality and sound sensors with *ANPR (automatic number plate recognition) sensors to build a picture of activity at three waste transfer industrial sites in Merton.
*The ANPR was only used for vehicle classification as it was deemed more acceptable, and gave us the same real data i.e. X cars, Y vans and Z trucks.
About the Author
The InnOvaTe Programme is an Internet of Things initiative by South London Partnership (SLP) to “pilot and research” IoT across the 5 London boroughs of Croydon, Merton, Richmond upon Thames, Sutton, and the Royal Borough of Kingston upon Thames. The programme looks at ways to generate economic growth, support local businesses, help people live better, healthier lives and assist with addressing the climate emergency. The project assessed 150 IoT ideas for the councils concerned, implementing 48 of them successfully over 18 months. The programme was formally completed in March 2023.
Case Study Challenge
A number of school streets schemes have been trialled that aim to improve the safety of school children travelling to school, specifically the area around the schools. Many parents use their cars to transport their child and often leave their car idling. Our IoT trial would like to monitor the various effects of the schemes, namely air quality. The air quality sensors would be based near the entrance to the schools and monitor real time data. We would also need to monitor traffic flows including vehicles, pedestrians, cycles and scooters. It is expected that this data will help to build the case for implementation and retention of school streets and potentially of other traffic management schemes.
Secondly, information around travel and transport and its impact upon air quality is vital to understanding this complex issue, and to deliver the best outcomes in line with our statutory requirements. Detailed information of the links between transport and local air quality will better influence policy making, prioritising actions and interventions as well as enable local decision making to improve the environment and avoid the adverse impacts on health. This project will provide a detailed picture of transport and associated pollution in the borough, as well as that caused by vehicles passing through the borough.
Last but not least, one trial worked with businesses in the London Borough of Merton, specifically to reduce air quality emissions by using data, its management and new monitoring technology. Merton has a number of waste transfer stations that help deliver the South London Waste Plan which are located in a specific area of the borough. With businesses of this nature there is an environmental impact which includes, noise, dust (particulates), NO2 and associated vehicle movements in and around the sites. Merton worked with 3 companies by introducing technology to assist with measuring air quality, noise and vehicle movement around these sites, and as they enter the industrial estate. Real-time data allowed these businesses to better self-regulate, enable flagging of incidents of dust or noise and allow these to be identified and addressed immediately by the business. It also allowed for better regulation and understanding of the impact of individual sites on air quality in the area. Further, at the time the trial started there was active legal action being taken by one of the traveller sites, and local residents had also got the Environment Agency involved. Merton was firmly stuck in the middle with little solid data on which to respond.
Use Case Design Objectives
SLP designed these trials to monitor air quality in key locations across the boroughs in order to inform decisions about whether and where potential interventions may be needed. In addition, by recording baseline data before changes are implemented, the effects of any new schemes can be measured. The sensors provide several air quality indicators in real-time. Some of the trials utilised Breathe London devices, which combine data from a huge network of sensors with that from its reference sites, which are used to correct and calibrate the data. Reference units are technical equipment, which collect detailed air quality hourly data. This data is then fed into a statistical model that is used to assess historical and recent data to determine air quality and whether the data is likely to be representative. Over a hundred air quality sensors were installed across the SLP by the end of 2021, demonstrating a clear commitment to tackling air quality issues.
The last trial worked in a different way. It used EMSOL equipment to deploy ANPR (automatic number plate recognition) and air quality sensors to generate a picture of current dust and noise pollution on three waste transfer sites. The ANPR data would be useful to determine whether some types of vehicles exacerbate the dust problem more than others.
Commissioning (budget/procurement)
A selection of relevant suppliers listed on the Crown Commercial Services (CSS) Spark dynamic purchasing systems (DPS) were invited to tender a competitive process managed by the Sutton Procurement team.
Contracts were awarded to:
The budget range for the trials varied as the Breathe London sensors were very expensive (£1,600 each), so it was dependent on the number used. The EMSOL trial cost between £50k and £100k. All trials ran for 18 to 24 months.
Deployment (what / who / where / how long)
Vivacity Labs’ traffic sensors were mounted to lamp posts or similar infrastructure with a power source. The sensors use AI to identify how many people and vehicles pass the sensor site and record relevant information such as time, mode of transport, direction of travel, etc. This constant monitoring generates a detailed picture of traffic at the sensor site, which can then be mined for insights and trends developing over times of day, week vs. weekend, month to month etc. In the case of schools, term-time and school holidays might also be interesting comparison points. Breathe London air quality sensors are co-located with the traffic sensors and log detailed readings of several air quality indicators in real-time.
Sensors were installed as follows:
In Merton, for many years there have been ongoing concerns around waste vehicles and site pollution in Weir Road. These sites play a vital role in the waste management plans for the South London Waste Partnership. A number of the sites converge in Weir Road, leading to a disproportionate number of skip and waste vehicles in the local area. From a public perspective this can lead to concerns over pollution, load shedding and safety. A number of residential properties surround this area and we see ongoing complaints regarding re-suspended road surface dust and site specific waste. Additionally, the area is being made over with a number of new, tall and expensive apartments that will now be overlooking the sites adding further pressure to the situation. The trial was to work with three key sites and use an approach that has developed to cover the environmental impact of construction and apply this to industrial waste management. The project consisted of a number of activities, including the installation of pollution monitoring at each site and at the site entrances of three key waste management sites. Additionally, traffic movement will be required to identify the makeup of the traffic in the area and where possible tagging (with the permission of businesses) specific site equipment. The type of data to be monitored will be both noise and dust in 6 locations (2 on each site).
Sensors were installed as follows:
Technology Implemented
Suppliers of the sensors were:
Results / Key Findings
Benefits / Usefulness of Data
The creation of the Tracsis dashboard showing traffic data and air quality data together was helpful. The granularity of Vivacity data is a benefit here as, for example, officers can now discern how many pedestrians are affected by pollution at a particular time in a particular location, which is believed to be an innovative feature. Richmond officers, in particular, recognised that the air quality data available in this trial was much more sophisticated than what they had access to before, i.e. PM2.5 readings, which indicate levels of particles of less than 2.5 micrometres in diameter (< 2.5μm). This fine particulate matter is the most likely to cause health problems so is a metric of special interest.
Richmond is motivated to learn about what is happening to air quality in the borough in real-time and potentially linking this to an updated health messaging service. This is a good example of how data generated by these trials can be drawn on for diverse uses.
At least one officer on the Comms and Engagement team has used the Tracsis dashboard data to demonstrate the efficacy of a school streets scheme. The data showed reduced car numbers and improved air quality readings at Cheam Common Junior Academy in Kingston (see Table 5 below).
Table 5 – Tracsis Dashboard data showing reduction in care numbers and lower air pollution readings after school streets implementation at Cheam Common Junior Academy, Sept to Nov 2021
Interestingly, the InnOvaTe programme has approached both Breathe London and the GLA to seek feedback on the combined traffic and air quality datasets, to see if broader benefits are being realised beyond the SLP. We believe this is an angle that should be more fully explored.
For the Merton industrial site trial, in keeping with officer expectations, initial data from the one fully installed site suggests that it is well within the limits for construction site air quality measures. Early data shows that the sites can be quite dirty even outside of working hours, though we do not yet know why. Interestingly, on one occasion some nearby Breathe London air quality sensors picked up a spike in air pollution that was captured on site. This indicated that the data from those may also be somewhat useful in conjunction with the data captured specifically for this trial.
EMSOL proactively tailored their alert system to share timely updates with officers. For instance, they have decreased the dust sensor alert range from a change in air quality over three minutes to only when there are spikes lasting for at least one hour after initial detection. This new alert range is a much better measure of actual meaningful air pollution given the complexities of measuring air quality.
EMSOL have shared detailed information with officers on how alerts are triggered and how thresholds have been set, as well as proposals for adjusting them. When there is a pollution spike, the dashboard provides a snapshot photo of the area. Meanwhile, data from the ANPR cameras list all vehicles in the location for ten minutes prior to the breach, so that officers can begin to ascertain whether their presence affects the breach rate.
From the beginning, the officers handling the waste site trials worked hard to coordinate activities between the SLP, the sensor/data providers, and the industrial waste facilities.
Lessons Learned
With the Breathe London sensors, air quality recordings must be calibrated in order to establish baseline air quality levels against which to compare changes before it can be fully ratified. In addition, as the sensors are solar powered, some struggled to function fully through the winter as sunlight is weak and the days are short. This resulted in power management controls to reduce functionality to conserve energy. This caused some initial confusion for officers as the dashboard showed some sensors as greyed out, which meant no index data could be generated for that particular hour, although underlying data was still accessible.
This innovation was not fully recognised by some officers involved in the pilots or communicated to colleagues with sufficient impact. Some officers involved in the scheme did not use the Tracsis dashboard at all, and programme management had to push some councils to provide information on which sensors should be added to the dashboard for their borough. Even where councils were engaging, the message was not getting through, although it was not possible to ascertain whether this was due to low internal appetite or a simple lack of awareness. Council efforts were not being fully publicised and therefore will not be recognised by residents.
The main problem with this trial was the lack of engagement with colleagues. This is essential for the programme to work. The Breathe London sensors are very expensive. At the time they were the best available, but shopping around would be suggested.
For the waste site trial, officers reported spending a great deal of time building trust among the three groups. They assured all parties that the sensors were meant to serve as objective data collection mechanisms, rather than as monitoring devices implemented with preconceived expectations.
Data results and insights were shared with all partners. Findings revealed that the major sources of air and noise pollution were vehicles on the adjacent roads, rather than the waste facilities. The facilities also learned of a few basic ways to improve their practices, which they swiftly implemented.
Conclusion
On the whole, the air quality trials were a success.
For the schools air quality trial, the AQ colleagues didn’t wish to engage with the schools and build a real programme. However, the units subsequently proved very useful for Highways colleagues, and Councillors loved them. In Richmond, the data fed in at the right time to focus on this area. It has subsequently become embedded and part of BAU to get baseline data. Data was proven to be very important, although the link to the school, children and education was missed, so Highways took it over. With better officer and CEO engagement the data was attended to. This is absolutely key to generate baseline information and assist in making supportive decisions based on facts.
The Merton waste site trial was a big success! It was perhaps our most interesting trial. The three waste transfer sites were literally being targeted by all sides, as new flats had now been built, two traveller camps overlook the sites and in short they could never appear to be treated fairly. The introduction of sensors on the sites and outside, allowed facts to be obtained covering noise, vehicle movements and air quality. Whilst the sites clearly were silly at times e.g. not turning on sprinklers during dry and windy days, they were nowhere near as bad as portrayed. Also, by allowing live data to be fed to admin staff they could immediately get involved if noisy or dirty vehicles came on site. In the end the data showed a 28-40% improvement in air quality and noise at nil cost to the council, and based on WHO averages, the three sites were compliant. Ultimately, this led not only to the environment agency referring to this scheme as a poster child, but also the suspension of their interest in the sites as they were now deemed clean and within all approved limits.
Photos from the use case
Contact
For further information, please contact the service leads involved in this project, listed below.
Paul Garside
Sustainable Transport Officer, Kingston and Sutton Shared Environment Service
London Borough of Sutton and Royal Borough of Kingston
paul.garside@sutton.gov.uk
Peter Bond
Environmental Protection Officer, Kingston & Sutton Shared Environment Service
London Borough of Sutton and Royal Borough of Kingston
peter.bond@sutton.gov.uk
Jason Andrews
EH Pollution Manager (Air Quality)
London Boroughs of Merton, Richmond upon Thames and Wandsworth
Jason.Andrews@merton.gov.uk
Pierre Venter
IoT Delivery Manager
Royal Borough of Kingston and London Borough of Sutton
pierre.venter@sutton.gov.uk
This use case is from South London Partnership – InnOvaTe “IoT” Project.
Outcome
Reduce and deter the number of fly tipping occurrences, which cost the council money to remove the rubbish and has a significant detrimental impact on the residents and their enjoyment of their home.
Sectors
Landlord Services, Highways, Enforcement.
Key Stakeholders
Landlord Services.
Overview
There were two main IoT trials for fly tipping; one in Kingston and the other in Sutton.
SLP (South London Partnership) designed these trials for Sutton and Kingston with the goal of furnishing officers with the data on fly-tipping offences at their selected sites, and to work with enforcement teams to act on the information as appropriate. Fly-tipping is an issue affecting many local authorities. The sensors, provided by iDefigo and Vodafone, rely on a machine-learning back-end function which learns to detect when rubbish has been dumped and then triggers a video recording of the offence. Enforcement officers can then review the footage from the sensor to determine whether an offence was genuinely committed, and can issue a fine if warranted.
The sensors were accompanied by correlated signage notifying potential fly-tippers that the area was being monitored.
About the Author
The InnOvaTe Programme is an Internet of Things initiative by South London Partnership (SLP) to “pilot and research” IoT across the 5 London boroughs of Croydon, Merton, Richmond upon Thames, Sutton, and the Royal Borough of Kingston upon Thames. The programme looks at ways to generate economic growth, support local businesses, help people live better, healthier lives and assist with addressing the climate emergency. The project assessed 150 IoT ideas for the councils concerned, implementing 48 of them successfully over 18 months. The programme was formally completed in March 2023.
Case Study Challenge
Fly tipping is an issue affecting many local authorities and this pilot was conceived after the ‘Let’s Scrap It’ scheme in Sutton, which saw anti-fly tipping signs posted across the borough, actually exacerbated rather than diminished the problem. This experience indicated that enforcement will be necessary to curb the problem, although officers acknowledge that fly tipping is likely to be largely relocated rather than completely eradicated.
Use Case Design Objectives
The sensors, provided by Idefigo and Vodafone, rely on a machine-learning back-end function which learns to detect when rubbish has been dumped and then trigger video recording of the offence. Enforcement officers can then review the footage from the sensor to determine whether an offence was genuinely committed and can issue a fine if warranted. Although the council might generate some income through the fines, the hope is that publicising the successes of the scheme will act as a deterrent to other potential offenders. The sensors were accompanied by correlex signage notifying potential fly tippers that the area is being monitored.
Commissioning (budget/procurement)
Mid 2021, a selection of relevant suppliers listed on the Crown Commercial Services (CSS) Spark dynamic purchasing systems (DPS) were invited to tender a competitive process managed by the Sutton Procurement team. The contract was awarded to Vodafone and iDefigo.
The budget range for the Kingston trial was £100-150K. The Kingston trial lasted just under two years until it was absorbed into BAU as the Councillors and Housing Officers felt there was considerable value in continuing to address issues on their estates.
Deployment (what / who / where / how long)
In Sutton, this scheme targeted 12 hotspot areas to be monitored for potential fly tipping offences. A total of 29 sensors, attached to lamp posts, were deployed; eight on the high street and a further 21 in outlying fly tipping hotspots. In an attempt to deter would-be vandals, the sensors were placed on a routine night-check and the sensitivity of the anti-tamper alarms was increased. The intention was for the sensors to be moved each quarter to the latest dumping hotspots as fly tippers change their routines.
In Kingston the focus was slightly different. Kingston Homes manage a number of housing sites in the borough and are struggling to overcome fly tipping issues at some of their locations. Most of the refuse appears to be industrial, construction, or commercial waste, likely dumped by professional waste removal services. As a result, it is often hazardous and has to be sorted and disposed of correctly, which is a more complex and costly process. This scheme targeted 10 hotspot areas, using 20 sensors, across Kingston Homes sites to be monitored for potential fly tipping offences. Final Kingston sensor relocations and removals were completed in December 2022.
Technology Implemented
The suppliers of the sensors were Idefigo and Vodafone.
Results / Key Findings
Kingston:
Sutton:
Benefits / Usefulness of Data
Lessons Learned
Kingston:
The main concerns were in Sutton:
Conclusion
The Kingston Fly Tipping trial was the biggest single IoT programme success. The trial saw an 80% reduction in fly tipping and was so popular with residents and Councillors that money was found to continue and expand the trial. It really grabbed the attention of the communities, as they saw how people took advantage of bin stores, and catching people commercially dumping asbestos and mattresses etc was brilliant. Additionally, we stopped the trading of waste between criminal gangs as they knew they’d be caught. In the case of one site off the A3, after years of blight they finally broke the back of traveller groups dumping waste in their streets.
Sutton believed that the sensors were not providing the service intended or desired. Despite an initial enthusiasm, Housing Officers decided that the prevention of fly tipping was not a priority. Therefore, within weeks, and despite vast amounts of training support, it quickly became apparent we should remove the cameras as no one looked at the events. Sadly the users then complained as residents would notice the cameras had gone! In the end, as they weren’t being monitored, the units were removed.
Photos/videos from the use case
BBC Click Video: https://www.bbc.co.uk/programmes/m0018tzr
Contact
For further information, please contact the service leads involved in this project, listed below.
Jane Ball
Corporate Head of Landlord Services
Royal Borough of Kingston upon Thames
jane.ball@kingston.gov.uk
Pierre Venter
IoT Delivery Manager
Royal Borough of Kingston and London Borough of Sutton
pierre.venter@sutton.gov.uk
This use case is from South London Partnership – InnOvaTe “IoT” Project.
Outcome
Deployment of flood monitoring IoT sensors to minimise impact of flooding on roads after heavy rainfall and support optimised cleaning routines for council services.
Sectors
Local authority, Highways teams, public sector.
Key Stakeholders
Highways Team, Highways clearance and cleaning contractors, Data Team, Environment Team.
Overview
IoT data can be used to generate real-time insights and predictive analysis to support informed decision-making to lower response times, and also to reduce burdens on council officers to control or prevent flooding in known hotspots. Benefits of this includes the reduction in disruption and safety of life to residents and business (risk of people putting themselves in harm by entering deep water, damage to property and traffic congestion, wasted money and time specifically), but also includes efficiencies to improve council services, less miles driven and cost to repair post any flooding. Finally the biggest single benefit is that the Council moves to a proactive footing when dealing with flooding.’
About the Author
The InnOvaTe Programme is an Internet of Things initiative by South London Partnership (SLP) to “pilot and research” IoT across the 5 London boroughs of Croydon, Merton, Richmond upon Thames, Sutton, and the Royal Borough of Kingston upon Thames. The programme looks at ways to generate economic growth, support local businesses, help people live better, healthier lives and assist with addressing the climate emergency. The project assessed 150 IoT ideas for the councils concerned, implementing 48 of them successfully over 18 months. The programme was formally completed in March 2023.
Case Study Challenge
The impact of our changing climate on how we live and work is one of the latest challenges facing local authorities. Record-breaking dry spells, followed by wet weather can see councils having to deal with park fires one day and flash floods the next. In the summer of 2021 the London Borough of Sutton experienced this challenge first hand. The long hot summer resulted in hard parched ground, so when the rain came the borough’s drainage system couldn’t cope, further impeding progress was the grass clipping which had formed a barrier effectively over manholes. The result was a number of flash floods across Sutton. With extreme weather predicted to continue, Sutton and Kingston councils wanted to find a better way of monitoring the risk of flooding to reduce the impact it has on lives, property and vehicles.
Use Case Design Objectives
Pilots were designed to furnish officers with the data to make informed, efficient, and proactive decisions to control, prevent or respond quickly to flooding in known hotspots and thereby reduce disruption for residents and businesses. Gully and soakaway sensors, as well as rainfall measurement sensors needed to be deployed at key strategic locations across both Kingston and Sutton boroughs to provide near real time data for both tactical and strategic use.
Commissioning (budget/procurement)
In April 2021, a selection of relevant suppliers listed on the Crown Commercial Services (CSS) Spark dynamic purchasing systems (DPS) were invited to tender a competitive process managed by the Sutton Procurement team. Aquasition was awarded as the winning supplier with an overall cost in the range of £50,000 to £100,000.
Deployment (what / who / where / how long)
Sutton and Kingston councils deployed IoT sensors to 14 sites across the boroughs. This included gully, soakaway and rainfall sensors. The sensors monitor the water levels, reporting this data to a central dashboard. Tolerances were set to give service a visual indication of water capacity within the target area – either below, rising or above limits. Alerts were also used to notify relevant staff from different teams i.e. highways, flood management and corporate communications teams. Rain forecast data was used to help officers predict potential flooding issues in the near future, allowing for preventative action to be taken if needed. The solution was handed over to council services in November 2022.
Technology Implemented
Road gully / drain monitoring sensors were deployed (pole mounted / bollards), as well as rain gauges at strategic locations in the borough. Connectivity was provided via the NB-IoT wireless network to a cloud hosted service. In addition, Environment Agency data as well as rainfall forecast data was also used. A data dashboard was also created on Microsoft Power BI allowing officers to see and drill into all data generated by the solution.
Results / Key Findings
Having deployed across two separate boroughs, both councils have reported feeling empowered to make proactive decisions with greater confidence thanks to the data. During times of downpour, the council is now able to quickly verify if flooding is likely to occur without the need to reallocate staff from other areas of the borough, which is now no longer the case. Insights have also led to changes in operational processes to 3rd party cleaning regimes, and have allowed significant time reduction spent by officers to manage reactions to flooding hot spots. Before the pilot, cleaning crews were sent out without any information at all, being deployed based on educated guesses which often led to costs being incurred without delivering any benefit but now slow-draining sites can be prioritised in real-time. Further via the implementation of sensors Council Officers can now see the before and after effects of cleaning in a soakaway and ensure it has a) occurred and b) made a real difference. The schemes are already viewed as highly successful and have been strongly supported by councillors, with officers themselves having expressed a need to extend the deployment to additional sites of concern. Knowing which soakaways need clearing, officers can now allocate regular clearing services more efficiently in anticipation of rain. Residents experience less flooding because the borough can identify high-risk areas before flooding occurs.
Benefits / Usefulness of Data
Data has improved decision-making, allowing officers to schedule cleaning maintenance as genuinely needed rather than as presumed necessary. Data has also been used to dispute ownership of flooding issues (leaks) from nearby fresh water pumps. Such has been the perceived power of the data, that the two respective CEOs are now taking an active interest along with the council’s communications teams. The comms team has promoted a video via social media to help brief members and the public. As noted above, councillors have also taken an active interest in this trial. In order to make the best use of the data, officers attempted to interrogate historical flooding data which might be used in conjunction with the current data. However, only a handful of records of flooding exist from the last 15 years, so doing this has not been possible. Officers expressed the need to have real-time predictive alerts to help improve visibility of potential flooding. Further the initial scheme was so successful that the adjacent borough of Richmond upon Thames is also now involved and we are aware in 2023 that Wandsworth is also now deploying sensors.
Lessons Learned
Engagement from multiple areas within the council is key to a successful implementation and adoption of data, this includes representatives from Highways, Comms, Street Works and Environment (Flood Monitoring). Predictive insights will help reduce response times and give more flexibility to councils teams – this combined with typography data would be very useful to understand direction of surface flooding. Added to this, improvements to the speed at which data is captured, has been required. It was noted that heavy downpours don’t trigger alerts quickly enough however this can be adjusted with him from the supplier. In addition, cameras are needed to be deployed to give officers visibility of surface flooding. Adoption by other services, including Emergency Services, has been slow.
Conclusion
The ability to monitor water-levels has already improved decision-making, allowing officers to schedule cleaning maintenance as genuinely needed rather than as presumed necessary. The schemes have been strongly supported by councillors, and officers are looking at extending the use of these sensors to additional sites beyond the pilot locations. The data has been used to optimise cleaning schedules and to feed into larger decisions about longer-term infrastructure investment. The success of these trials has led to a similar scheme being implemented in Richmond.
Photos from the use case
For more photos, visit the Aquasition Deployment photo library.
Contact
For further information, please contact the service leads involved in this project, listed below.
Mark Murphy
Principal Inspector Highway Operations
Royal Borough of Kingston
mark.murphy@kingston.gov.uk
Gary Mersh
Senior Professional Engineer
London Borough of Sutton
gary.mersh@sutton.gov.uk
Pierre Venter
IoT Delivery Manager
Royal Borough of Kingston and London Borough of Sutton
pierre.venter@sutton.gov.uk
This use case is from South London Partnership – InnOvaTe “IoT” Project.
Outcome
Discrete monitoring of vulnerable residents in their homes to enable them to live independently by detecting changes in activity that may require interventions that could ultimately save lives.
Sectors
Local authority, Adult Social Care, public sector.
Key Stakeholders
Adult Social Care, housing partnership, housing, Data Team.
Overview
Sutton and Merton launched pilots in an effort to explore how IoT can contribute to Independent Living Officers’ (ILOs’) work, keeping at-risk residents living independently and safely at home. Digital solutions are becoming increasingly important as analogue telephone services, on which the existing telecare providers rely, will be reduced from 2023, and switched off entirely by 2025. This use case was prompted by the COVID-19 outbreak in particular, because vulnerable residents could not be as closely monitored during that period. They were also likely to be at higher risk of illness and physical or mental decline given the conditions of lockdown.
The hospital to home trial partially reproduced the strategy used above to support carers in assisting residents within their scope of activity, but with a system called Vayyar.
The ability to review resident well being data gathered by in-home sensors has fundamentally changed how the council services organise their workload, ultimately improving care delivered. Quantifying financial benefit (and therefore investment justification) has been difficult, especially when other organisations (e.g. NHS) could be the indirect beneficiaries. This technology has proven itself by optimising council resources and saving human lives.
There were three main IoT trials related to resident care support; two in Sutton and one in Merton.
The first cases for Sutton and Merton were born of the need to support vulnerable residents during the COVID-19 pandemic, when physical visits were not permitted. A single battery-powered device was hand-posted to the resident, which was used to indicate decline in the health of the resident and allow an ILO (Independent Living Officer) to intervene. In Sutton, the ability to review the sensor data has fundamentally changed how the ILOs organise their workload and allowed them to provide a more targeted and efficient support service to residents. Data visualisation has emerged as a key benefit from this system. The provider of the sensors was IoTSG (IoT Solutions Group).
In the second trial for Sutton, 50 sensors would be deployed in dwellings used for the rehabilitation of people discharged from the hospital (hospital to home). While people were still recovering, carers would provide tailored support to those people for up to six weeks. The aim was to use Vayyar devices on the wall to pick up if, when and where a person falls. Then the device would send an alert to the carers so they could take immediate action.
About the Author
The InnOvaTe Programme is an Internet of Things initiative by South London Partnership (SLP) to “pilot and research” IoT across the 5 London boroughs of Croydon, Merton, Richmond upon Thames, Sutton, and the Royal Borough of Kingston upon Thames. The programme looks at ways to generate economic growth, support local businesses, help people live better, healthier lives and assist with addressing the climate emergency. The project assessed 150 IoT ideas for the councils concerned, implementing 48 of them successfully over 18 months. The programme was formally completed in March 2023.
Case Study Challenge
The adult social care system in the UK is facing a number of challenges, including increased demand, complexity, workforce shortages, and integration. These challenges are having a number of negative consequences, including cuts in other services, longer waiting times, and declining quality of care. Increased strain on Independent Living Officers (ILOs) has meant less time can be given to individuals. Unobtrusive and easily deployable pilots were aimed to address this by providing prioritised actionable insights to staff to focus on those who need care the most.
Use Case Design Objectives
Use cases were designed to help council services work more efficiently by detecting changes in residents’ daily activities and alerting teams to declining activity. This provides early warning of vulnerable residents becoming unwell. Sensors were hand-posted to residents and continuously recorded humidity and temperature data. The data was reported back to a central database every four hours. Data was processed using machine learning to understand the resident’s normal activity patterns, giving smart insights into any possible changes. In addition, to support vulnerable residents returning from hospital, sensors were deployed to detect falls and send alerts to carers, providing tailored support to people recovering at home.
Commissioning (budget/procurement)
In November 2020, a selection of relevant suppliers listed on the Crown Commercial Services (CSS) Spark dynamic purchasing systems (DPS) were invited to tender a competitive process managed by the Sutton Procurement team. The contract was awarded to IoT Solutions Group in January 2021. The budget range for each trial was less than £50,000 and trials typically lasted 1-2 years.
Deployment (what / who / where / how long)
Around 150 sensors were deployed in Sutton and less than 50 in Merton. The sensors were posted to the trial participants with instructions to place the device in the kitchen. Sensors were battery-powered and required no setup or install by residents. Each morning council services team members checked status of each of the sensors via an online dashboard portal – this data would focus the staff members attention for the day, prioritising their workload to perform check-ins on residents who most likely needed assistance that day. In addition, alerts were generated if a resident’s status changed drastically within a four-hour period. In Merton, the sensors were deployed in two groups of residents. The first was a group of 15 adults with learning disabilities, where there was a genuine concern that cuckooing of some of these residents may be occuring. The second group was 6 adults receiving telecare support. This provided key learnings to contrast across the groups. Monitoring residents returning from hospital helps to provide essential intervention when needed.
Technology Implemented
Sensors measuring a number of factors to assess activity were deployed. Connectivity was provided via the NB-IoT wireless network to a cloud hosted service. A secure data dashboard was also created on Microsoft Power BI allowing officers to see and drill into all data generated by the solution.
Results / Key Findings
In Sutton, IoT technology helped Sutton Housing Partnership (SHP) save the lives of five residents. The sensors improved council service efficiencies, delivering better care to more residents – it’s important to add that no normal checking calls were due for the affected residents. Insights were also generated to investigate possible fuel poverty, as well as provide alerts during periods of extreme hot and cold weather. Five residents’ lives were saved because of proactive alerts. The sensors proved to be non-invasive and gave residents peace of mind. Overall, the IoT trial in Sutton was a success, and the technology has the potential to improve the lives of many people. SLP won the Smart Places Award at Connected Britain Awards 2022 as a result of this trial.
In the Merton trial, capacity in the care team was stretched over the busy winter period due to COVID-19. Merton continued to monitor the 21 homes with the sensors but did not roll out anymore. Merton officers found the sensors useful, as they confirmed cuckooing was not occurring. However, they already had access to similar technology in their adult accommodation and this product added no significant additional value to what was already in place.
With regards to monitoring residents returning to home from hospital, sensors were successful in detecting if a resident fell in their home after release from hospital. Sutton was interested in using the sensors to monitor residents’ health and safety. There is also an intention in exploring other functionalities of the devices, such as monitoring residents’ breathing and heart rate to capture anomalies to enable swift action to be taken.
Benefits / Usefulness of Data
Data obtained from the trial has shown that these kinds are insights are very valuable. There has been improved decision-making and has led to changes in the way the service has been run. Additional insights were obtained that were not expected, e.g. confirming the support needs of adults with learning disabilities. Over time, the quality of the data obtained has improved its reliability, strengthening the value of the overall solution.
Lessons Learned
Some key lessons learned involved the display / presentation of the data obtained. Data visualisation has emerged as a key requirement for this case study. We learnt that it is advisable for early response sensors to be rolled out primarily where a local authority owns the housing stock, and can roll out the sensor as standard to many homes at once. When a local authority has officers with responsibility for many more residents than they can reasonably monitor in close detail. Communication with the residents was key, investment into this was essential. Ensuring requirements for outcomes (not technology) was also important.
Conclusion
IoT sensor deployment in Sutton has been considered a big success, providing more insights than expected, and having saved a life in the first week, expectations were exceeded on all counts. Additionally, the insights generated have driven a good number of fuel poverty and temperature related interventions. The trial did deliver on its original goal, which was to enable officers to be more efficient with their allocation of time to vulnerable residents, improving the overall service experience. Merton did also generate good outcomes but not as significant as Sutton, primarily due to the fact that Merton does not have its own housing stock.
Photos from the use case
Contact
For further information, please contact the service leads involved in this project, listed below.
Bradley Coupar
IoT Delivery Manager and Social Worker
London Borough of Sutton
bradley.coupar@sutton.gov.uk
Clive Green
People and Places Lead
Sutton Housing Partnership
clive.green@suttonhousingpartnership.org.uk
Pierre Venter
IoT Delivery Manager
Royal Borough of Kingston and London Borough of Sutton
pierre.venter@sutton.gov.uk
