Intelligent buildings are the future. An intelligent building consists of devices like lifts, chillers, boilers, fire alarms, smoke detectors, carbon monoxide detectors all of which are emitting data. There are multiple times of data
1. State data .For example temperature of a room or pressure of water in boiler
2. Alarms data . For example when certain events of interests are observed, for example a fire alarm goes off.
Using these 2 inputs the context of a device in an intelligent building can be modeled.
Lets take the simple case of understanding the history of a fire alarm which has been installed on a crucial building in the city.
This alarm has been installed for almost 3 years. The technician wants to understand the history behind the device
What is the rate at which alarms are going off ? ( Velocity )
When was the last time this went off ? ( Recency )
How many times did it go off ? ( Frequency )
A big data analytical solution can stream events from this device and help the technician answer previously unanswerable questions regarding the health of a building or a device in the building. So what are the other possibilities M2M and Big Data Analytics unlock for the Building Management Systems
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