Providing energy-consumption feedback has the potential to change people’s behavior, a reality that has led to significant energy-usage reductions in residential buildings. However, it is challenging to provide feedback in commercial buildings because it is difficult to track occupants’ behaviors and their corresponding energy usage—especially for temporary occupants.
In order to make providing energy feedback possible in commercial buildings, this research aims at proposing a coupled system that monitors the energy load for occupants who have Wi-Fi-enabled devices. The system benchmarks energy loads using an energy monitoring system that simultaneously detects occupancy through Wi-Fi access points. With the information gathered about occupancy and individual occupant’s energy load, this coupled system is able to identify those candidates who – when provided relevant feedback – would have the potential to save energy. A preliminary experiment was conducted in an educational building to illustrate the data processing procedure and to test the validity of the system. The proposed system is the prototype of a coupled system that, in the future, will be able to estimate individual’s energy load through an indoor positioning system and, in turn, provide corresponding energy-consumption feedback.
Research Projects
Developing active building energy management system base on coupled Wi-Fi and BLE indoor positioning system (IPS)
PI, JCYJ20150518163139952, The Shenzhen Science and Technology Funding Programs ( Special Program for Energy Conservation), Oct 2016 – Sep 2018, RMB 340,000
Building occupancy information is the premise of modern building service systems’ control and operation. Inaccurate occupancy information could results in insufficient comfort level and energy waste. Current occupancy detecting system relies on indirect and low resolution environmental sensors, which potentially mislead facility managers and result in inefficiency in building energy use. In this project, we proposed a novel occupancy detecting system through a coupled indoor positioning system. The system integrates Wi-Fi and BLE networks and implements a stochastic positioning algorithm to collect high resolution occupancy data. The system not only able to identify the geospatial distribution of occupants, but also track their movements in a network covered space.
Developing Effective Eco-feedback Platform to Benchmark Building Energy Consumption and Carbon Dioxide Emission and Promote Energy Saving Behavior and Awareness in Hong Kong
PI, #9211074 (25/2014), Hong Kong Environment and Conservation Fund (ECF), Mar 2015 – Mar 2017, HKD 455,000