From Alerts to Action

Sensor data as part of a wider system 

A consistent theme throughout the session was that sensor data has limited value in isolation. Temperature and humidity readings only become meaningful when interpreted alongside survey findings, repair histories, building characteristics and resident context. 

Damp and mould rarely have a single cause. Overcrowding, underheating, inadequate ventilation, fabric defects and resident constraints often interact. Sensor data helps reveal patterns over time, rather than snapshots. It shows how long a property remains at risk, how quickly moisture is removed, and whether interventions are working. 

This moves organisations away from reactive responses based on complaints alone, towards a clearer understanding of risk progression. It also supports more proportionate decision making, particularly where resources are constrained. 

Understanding what “good” looks like 

One of the most practical contributions of the session was the clear explanation of what healthy and unhealthy environmental profiles look like in real homes. 

Bathrooms and kitchens naturally experience moisture spikes. The issue is not the spike itself, but how quickly humidity returns to a safe baseline. Sensor data can show whether extractor fans are effective, incorrectly set, broken or not being used. It can also highlight when moisture is migrating into other parts of the home, increasing risk elsewhere. 

Bedrooms and living spaces tell a different story. Persistent high humidity, minimal daily variation, or prolonged underheating all point to increased condensation risk. These patterns are particularly important for vulnerable residents, where health impacts may be more severe. 

The learning reinforced that interpreting this data does not require advanced analytics. With basic training and agreed thresholds, frontline teams can identify risk quickly and act with greater confidence. 

From data to decision making 

A key operational challenge discussed was responsibility. Sensor platforms can generate insight, but someone must own the process of reviewing data, linking it to cases and ensuring action follows. 

The most effective approaches described involved small, dedicated teams with clear accountability. Regular review of high risk properties, structured checks against maintenance records, and follow up after repairs were central. Importantly, sensor data was used to confirm whether an intervention had resolved the underlying issue, not simply whether a job had been completed. 

This approach reduces repeat visits, improves learning over time and strengthens evidence for compliance. It also supports a more transparent relationship with residents, where decisions are based on observable conditions rather than assumptions. 

Organisational learning in practice 

The experience shared by Phoenix Community Housing illustrated how sensor data can be embedded within a broader organisational response to damp and mould. 

Their work highlighted the importance of aligning data, policy, resident engagement, repairs and IT systems. Sensors were not positioned as a standalone solution, but as one part of a redesigned process shaped by resident experience and regulatory change. 

Findings from sensor data helped identify systemic issues, such as widespread extractor fan failure or disconnection. This enabled targeted, proactive programmes rather than repeated reactive responses. It also informed tenant engagement and education, grounded in evidence from their own homes. 

Implications for health and wellbeing 

From a Healthy Homes Hub perspective, the value of this approach lies in its preventative impact. Prolonged exposure to high humidity, cold indoor temperatures and mould growth is associated with respiratory conditions, stress and wider health inequalities. Reducing exposure time matters. 

Sensor data supports earlier identification of risk, particularly in homes where issues may not yet be visible. It also helps ensure that interventions improve indoor environmental quality in practice, not just on paper. 

Crucially, this work reinforces the need to consider residents’ constraints. Underheating is often linked to affordability and understanding, not choice. Data can support more constructive conversations that balance asset protection with resident health and dignity.  

The role of technology partners 

The session also drew on learning from ZapCarbon, whose experience across tens of thousands of homes highlighted common pitfalls and opportunities. 

False positives, alert fatigue and lack of integration with operational systems were recurring challenges. Addressing these requires clarity on what data is used for, who uses it and how it informs decisions. Technology can support this, but it does not replace organisational design, training or professional judgement. 

What the sector can take forward 

This masterclass reinforced that compliance with Awaab’s Law is not solely about speed. It is about understanding risk, preventing harm and demonstrating that decisions are informed, proportionate and effective. 

Sensor data can play a meaningful role in this shift, but only when embedded within clear processes and a culture of learning. The focus must remain on healthier homes, not higher volumes of data. 

Practical steps housing providers can take 

• Clarify ownership of sensor data review, with named roles responsible for acting on insights. 

• Train frontline teams to interpret basic temperature and humidity patterns confidently. 

• Integrate data with existing systems, including surveys, repairs and case management. 

• Use data to verify outcomes, checking conditions after repairs rather than assuming resolution. 

• Target prevention, prioritising homes with prolonged exposure rather than visible mould alone. 

Taken together, these steps support a more credible, health focused approach to damp and mould, one that moves from alerts to action and from response to prevention.