There were many projects conducted and there were many applications conducted which had explored the deep learning through the neural networks within the IoT platform to optimize the asset utilization in an office building. The Deep Learning Facility Testbed analyses 35,000 measured data points per minute which work to optimize the maintenance of monitored assets of the building. Because of this amount of data collected, the testbed relies on the artificial intelligence in order to detect the anomalies so that there can be an improved visitor experience with the things like prioritizing the elevator scheduling and also automating temperature and the lighting controls.
The structure of the building varies and it is very costly to design the anomaly detection system in order to fit the building. The testbed application learns as to whether a normal condition would be using the data aggregated from many of the sensors installed in the facility. For instance, the testbed can detect the unusual state of the air conditioning equipment in the kitchen and also the building facility management staff can find out if the air intake ducts in the kitchen have been closed to avoid the odour by the kitchen staff.
It is said that IoT is an important enabler for the energy efficiency but the large building complex requires many sensors to track the ambient conditions, occupancy and the traffic flow. Buildings also have fans, HVAC, light and the elevators which consume ample amount of energy and monitoring these sensors and the assets is not a small task.
Deployment of the IoT system for a smart building will maximise the value to a great extent of the big data collection through the deep learning analytics. The smart building will not only improve the operational efficiency but will also reduce the maintenance costs, which in turn will maximise the use of the assets.
It has been noted according to the Navigant Research Smart Buildings and Smart Cities Q3, 2017 that the global smart buildings for smart cities market has been expected to grow to $10.2 billion by 2026
.In order to make sure that there is full advantage taken of deep learning capabilities, the FM’s should ensure to have an efficient system so that there can be collecting and storing of the facilities management data. There are many facility management professionals who are currently facing the older equipment and the processors which are not up to the modern technology standards. The facility managers should keep in mind that by teaching technology to operate independently, deep learning will help the facility managers to improve the decision speed, consistency and the quality. The smart technology will also reduce the costs immediately.
