Apply Deep Learning to Building-Automation IoT Sensors

In building automation, sensors such as motion detectors, photocells, temperature, and CO2 and smoke detectors are used primarily for energy savings and safety. Next-generation buildings, however, are intended to be significantly more intelligent, with the capability to analyze space utilization, monitor occupants’ comfort, and generate business intelligence. To support such robust features, building-automation infrastructure requires considerably richer information that details what’s happening across the building space. Since current sensing solutions are limited in their ability to address this need, a new generation of smart sensors (see figure below) is required to enhance the accuracy, reliability, flexibility, and granularity of the data they provide. Data Analytics at the Sensor NodeIn the new era of the Internet of Things (IoT), there arises the opportunity to introduce a new approach to building automation…

Link to Full Article: Apply Deep Learning to Building-Automation IoT Sensors

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