Real-World Mould Data and Real-Time Environmental Monitoring via the Internet of Things
The internet of things clearly has a vital role to play in helping landlords monitor their stock for potential problems with mould and damp.
Real-time online monitoring of indoor temperature and atmospheric conditions it makes it easier to
identify problems with heating and ventilation in real time can
identify the need for proactive interventions and to predict where problematic mould might arise.
predict where mould could develop.
automatically schedule maintenance visits using machine learning, when monitoring suggests that a problem may be about to arise.
Real-time monitoring, therefore, has real potential to save landlords money by stopping problems developing and by preventing problems from escalating.
Although real-time environmental monitoring is a powerful tool, its use does not mean that housing providers do not also need to incorporate real-world microbiological data on mould levels into their modelling.
It makes little sense to install moisture and temperature sensors in a property, for example, without first establishing a benchmark for mould levels in that property. And given that most mould growth is not visible, robust testing protocols will still need to be used in cases where the data suggests that a mould problem is emerging.
qPCR testing for hidden mould is the obvious missing brick here: samples can be rapidly taken in the course of automatically-booked physical inspections and the robust data gathered can be fed directly into the models that trigger preventative action and into the housing providers’ monitoring systems.
This will ensure that any remedial action suggested by modelling is indeed necessary – and that pre-existing mould problems won’t inadvertently be missed.
