<IoT social housing information panel/>

>Using sensors and an analytics platform to measure activity in social housing to help flag resident’s needs

>The puzzle

North Wales’s largest social housing provider wanted to bring IoT into its properties to see how it could enhance its services. It wanted data measuring the patterns of how each of its properties is utilized in order to run it effectively, detect anomalies and identify the needs of its residents.

Yet it couldn’t make a viable case for the cost-efficacy of existing commercially available solutions across its estate. So, our mission was to develop a bespoke, cost-effective, platform as a working pilot, in partnership with the client’s internal IT resource.

>Our approach

The system needed to ingest data from a number of different Elsys IoT sensors, positioned around the properties, feeding data to an online information panel, and providing visual information and analytics to quite different groups of users, including:

  1. The housing welfare team
  2. IT staff
  3. Relatives/friends of a specific resident

In addition, a simple, integrated, asset management system, monitoring the placement and maintenance of the sensors themselves, was needed to underpin the system.

>The Solution

In seven months and with a team of two, Kodergarten:

  • Designed, built, and deployed an information panel
  • Provided a secure and GDPR compliant panel access to a diverse range of users, via their browsers
  • Supplied an integrated asset management system which was able to work with The Things Network API, assisting the IT team with the sensor installation and support by providing robust asset management
  • Created an innovative data ingestion system using influxDB tags to ensure that sensors could be moved or replaced while still providing consistent data and tracking for the asset management module
  • Connected with the Influx Kapacitor system to enable initial analysis of anomaly detection features and capabilities and specific sensors
  • Produced a basic SMS alert system for door sensors, based on globally set threshold values and a decision-making application
  • Delivered a system that was fully English / Welsh bi-lingual, right down to the axes on the graphs
  • Deployed onto AWS (pre-production and production environments)


We created a successful pilot system that can now be rolled out more widely to further social housing. The project delivered on the objective of gaining practical insights about how IoT could be used to help enhance social housing services across the organization and being created using open-source components, it is significantly more cost effective than existing off the shelf products.

As well as general housing maintenance data, users can detect things like, ‘has the front door been left open?,’ ‘has the cooker or the lights been left on?’, ‘is the motion around the house consistent with the resident’s usual routines?’.

By tracking resident’s movements, the analytics can flag when there is an anomaly, ensuring that help and support is provided, as quickly as possible. The analytics can also provide an early warning system of the resident’s deteriorating health, as when health and mental state decline, daily routines and patterns at home can often begin to be interrupted. Spotting anomalies in the data could for example suggest the early onset of Alzheimer’s Disease and discovering this early would ensure that individuals get the support they need as quickly as possible.

To sum up, the system offers futuristic social housing care which is already happening now!