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The influx of Internet-of-Things (IoT) enabled processing modules has facilitated new wireless ways to manage building sub-systems such as indoor air quality monitoring devices, lighting, air-conditioning and ventilation. They collectively can be called as Wireless Sensor Actuator Networks (WSAN). In a building environment they can be coupled with personalization for the occupant and - engagement of the occupant to form a human-in-the-loop control.

This project has developed IoT based low-energy edge devices that can perform flexible measurements and remote control using Message Queuing Telemetry Transport (MQTT) protocol for office buildings. The outcomes include:

a)     Wireless Sensor Array (WSN) which measures many indoor environmental parameters including carbon-dioxide, carbon monoxide, ozone, formaldehyde, particulate matter 2.5, temperature, humidity, motion, illuminance, colours, pressure and sound level. The WSN has the flexibility to add new sensors and upgrade the functions of its edge processor.

b)     Background Lighting Controller (BLC) which can be wirelessly instructed to perform intensity control for the LED luminaires used in offices. It minimizes the overall wiring required and is easy to retrofit, unlike DMX or DALI wired systems.

c)     Personalized Task Lighting Controller (PTLC) which can perform intensity control for low power task lights that augment background lighting when background lights are dimmed to conserve energy.

d)     Personalized Fan Controller (PFC) which augments indoor air-conditioning and facilitates setting of higher temperature for background air-conditioning to save energy.

e)     Personalized Ventilation Controller (PVC) which can control a rotatory damper actuator for allowing fresh air delivery in a personalized manner, through air terminal devices.

In parallel to these new IoT devices, a Recommender-system based Visual Comfort and Energy Efficient preference learning (ReViCEE) algorithm was designed to learn user preferences and recommend set-points to end users. Also, energy consumptions of air-conditioning and personalized fans were studied with the help of recurring occupant feedback. The future of these scalable cyber-physical systems developed would require elaborate management software and strengthening of their cybersecurity. They hold great value for evolution of Building Management Systems (BMS) and big-data processing to generate insights regarding the indoor environment and its constituents.