Whilst contemplating how to reach his ambitious goal of having the cleanest air of any large US city, Bloomberg wrote, “we first needed better data – because if you can’t measure the problem, you can’t manage it.”
To ensure adequate data was collected, Bloomberg placed 150 air-quality sensors at street level around New York City. Using the subsequent data, it was deduced that buildings using dirty heating oils were accountable for more pollution than all of the vehicles on the roads of New York City.
UK affordable housing landlords face similarly complex tasks as those faced by Bloomberg in 2002. Collectively, they manage nearly five million properties in a country where 88 per cent of the housing stock was built before 1990.
It is their responsibility to ensure large property portfolios meet various standards, namely the Decent Homes Standard and Energy Efficiency Standard for Social Housing (EESSH), all whilst ensuring resident well-being is maintained and improved. Ultimately, the provision of data would make these challenges more straightforward.
We believe Switchee is the obvious solution to this dilemma. Switchee uses five sensors that monitor heat, light, motion, air pressure and humidity. Data from these sensors is used to build an occupancy pattern for each home, without the need for resident engagement. Learning occupancy allows Switchee to optimise heating settings, reducing fuel bills by up to 15% and delivering real value for residents.
Meanwhile, the same data can be used to allow landlords to access remote live building KPIs such as thermal performance, condensation risk and heating system alerts. Asset managers can use this information to better understand specific problems and make targeted, proactive improvements – much like the Bloomberg’s analysts in New York City.
At Switchee, it is our mission to combat fuel poverty and empower landlords with remote data insight that save them money and improve well-being for their residents.
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