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Challenges
Damp and mould in homes pose a health risk and can affect both the physical and mental wellbeing of residents. Social landlords have a legal obligation to provide good quality and safe homes and services for tenants. Data collection and analysis can be used to support operational and strategic actions to meet this requirement.
Challenges related to damp and mould that the project aimed to address include:
- Swift action needed to address damp, cold, and unsafe homes within strict timeframes
- Gaps in property information
- Difficulty extracting relevant data from the repairs system
- Identifying and prioritising vulnerable residents
- Matching children to correct addresses across various systems
Approach
The project aimed to use IoT sensors for the following:
- Identify root causes of damp/mould issues
- Understand the problem’s scale in boroughs and across London
- Ensure improvements and remediations are effective
- Provide evidence for claims/discussions
- Detect problems before they occur
- Proactively mitigate reputation damage
The project was delivered in two phases. In phase one, 200 sensors were distributed to 18 boroughs for proactive monitoring, reactive responses, and baselining. This phase tested sensor distribution, deployment, data interpretation, and issue remediation.
Phase two involved creating a pan-London data platform to aggregate data from phase one participants and other boroughs collecting damp and mould data. The platform aims to support public health, retrofit, and housing policy outcomes.
Outcomes and benefits
The project is ongoing but aims to:
- Foster IoT adoption and faster implementation
- Harness the proven experience of a borough team with multiple successful deployments
- Avoid the unnecessary reptation of IoT trials
- Prevent data silos
- Demonstrate technology and data systems that enable a range tangible outcomes
- Generate new data to make strategic decisions
- Unlock supplier investment