ISS A/S will use the IBM Watson computing platform to manage its 25,000 buildings all over the world more efficiently. The company also wishes to improve the overall experience of the people working its buildings.
Devices and sensors will be deployed in doors, windows, chairs, meeting rooms, dispensers and air conditioning systems. Data from these embedded devices will be uploaded to the IBM Watson IoT platform and analysed to help the company understand how people use buildings, and adjust services accordingly. [IoT: IBM selected to modernise Fingrid’s electricity grid network]
Jeff Gravenhorst, CEO of ISS, said in a statement: “In today’s highly competitive market, managing and servicing buildings should no longer just be about cost.
“With a dashboard overview of key building metrics displayed on mobile devices, facility managers will benefit from an integrated, real-time view of the services and supplies within their buildings enabling them to adopt a more pro-active, flexible and responsive approach to building management and customised service delivery.
“Putting real time data into the hands of service staff will help to foster more attentive and service-minded employees.”
Energy efficiency through embedded intelligence
[quote] The devices deployed in buildings will be able to tell facilities management personnel, through the analysed data, how many people are occupying the building and where they are, enabling them to use energy more efficiently.
Adding to this, motion sensors in meeting rooms, chairs and tables will help building managers to better manage room occupancy, cancel unwanted room bookings and automate cleaning of building facilities.
Deon Newman, chief marketing officer for IBM Watson Internet of Things said: “There’s tremendous potential for reducing energy consumption.
“Some 43 per cent of global energy is consumed in buildings. So there’s great opportunity for us to do good for the planet, as well as to make the lives of the inhabitants of those buildings better.
“[The platform] was built as a way of dealing with large amounts of unstructured, unpredictable data types and finding patterns in that data.”
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