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.
 Study on the Theory, Models, and Applications of Eco-feedback in Energy Saving Behavior of Building Residents under Complex Social Networks
PI, JCYJ20150318154726296, The Shenzhen Science and Technology Funding Programs, Jan 2016- Dec 2017, RMB 480,000
The exposure and diffusion of energy eco-feedback in building occupant peer networks has been shown to influence an individual’s energy consumption decisions. In this project, we intent to applying the social network theory to explore the possibility of changing occupants’ energy using behavior. Through analysis on mulilayer and large social network, we aim at developing reasonable theory and models to understand the energy consuming pattern under current social environment. Then we will create social network models and simulate the building occupants’ decision making and the information transmission process.
 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
This project aims at developing an effective eco-feedback platform enable building occupants to benchmark their energy consumptions and carbon dioxide (CO2) emission with other similar buildings to promote their awareness and take actions to conserve energy and reduce CO2 emission. The proposed project will have a direct and practical contribution towards the environmental and resource conservation in Hong Kong. The project will also introduce an innovative platform, which also encourages the adoption of new technologies, such as smart energy meters and eco-feedback systems. Starting from middle schools and high schools participants, the project will benefit the whole building industries and energy market in Hong Kong. The objectives of the proposed project are: (1) to develop a platform to automatically collect the data that reading from smart energy meters and allow occupants to access their real-time energy consumption and carbon emission data and also benchmark their performance with other buildings, (2) to investigate multiple type of feedback information and identify the most effective feedback to promote conservation behavior, (3) to sustain the conservation behavior through the design of the platform and feedback portfolio, (4) to release the developed platform to public and disseminate the research results to academic community, industrial practitioners and policy-making organizations.
 Teaching and experiencing international teamwork through virtual environment
PI, #6000519, City University of Hong Kong Teaching Development Grant (TDG), Dec 2014- Dec 2016, HKD 200,000
An increasing number of firms are outsourcing products and services from international vendors. Educators should prepare students with knowledge and abilities to participate in this everlasting global collaboration. However, teaching international teamwork and giving students international experiences is always a challenging task, not only because of geographic distances of global teams, but also the high expense of sending students aboard. Virtual environment, which is widely implemented in game development, offers an innovative technology solution for geographically distributed collaborations. This proposed project offers students a unique opportunity to incubate and develop discoveries and knowledge with their geographically distributed peers in an virtual environment.
The future development of this project will collaborate with a platform called CyberGrid developed by the Civil Engineering Network Dynamic Lab
 Green Connections: Pilot Study on Solid Waste Management on CityU Campus to Minimize Landfill soild waste
PI (with Dr. Xiaowei Luo), #6986020, City University of Hong Kong Campus SustainableFund (CSF), Jan 2015- Jun 2016, HKD 295,900
 Gyroscopic Stabilizers for Construction Cranes and Gondolas
PI, #9231133, Hong Kong Construction Industry Council (CIC), Jan 2015- Jun 2016, HKD 1,070,400
Tower cranes are widely used in construction jobsite for their efficiency. However, tower cranes and construction workers themselves suffer a significant safety hazards from natural sway of payloads. Besides, the external disturbance of wind leads to additional sway and intensifies the oscillation amplitude of crane load on construction site. This project aims at proposing a hybrid control mechanism that combine electronic and mechanical gyroscopes to produce a balancing torque, keeping crane load stable.
 Detecting Awkward Postures in Construction Jobsite through Coupling 3D Sensors and Motion Sensors
PI, #7004182, City University of Hong Kong Strategic Research Grant (SRG), Nov 2013 – Mar 2015, HKD 99,215
Sensing technology is one of the prominent solutions for site observation, but it subject to data inaccuracy and incompleteness caused by occlusions and misrepresentation. The proposed research aims at conducting a preliminary research to develop a coupled system to employ motion sensors to supplement the 3D sensors to improve its detecting accuracy.
 Promoting Student Participation and Enabling Collective and Mutual Learning in Engineering Education through a Social Writing Platform (Wikispaces)
PI, #6000468, City University of Hong Kong Teaching Startup Grant (TSG), Nov 2013 – Mar 2015, HKD 94,172
Learning Management Systems (LMS), such as Blackboard, have proven to be an efficient tool to manage course materials and enhance learning. However, students can barely participate in course material editing, creation and sharing or expressing their opinions through the LMS. Blackboard is also complicated for beginners and impossible for instructors to track the students’ engagement. To facilitate Discovery-enriched Curriculum (DEC) and provide an open access and a free database for students to create, maintain, and share their knowledge and discoveries, Wikispaces, a social writing platform and an educational wiki, will be employed. Through Wikispaces, students not only can benefit from their active participation, but also from collective learning and mutual learning with their classmates. Students can hold their own personal wiki, store materials from other courses, and use the platform even after their graduation. The platform is also able to track the involvement and participation of students for instructors.
Sample course Wikis can be find at this link.
 Tracking Occupancy, Monitoring Consumption Behavior, and Estimating Occupants’ Energy Load in Commercial Buildings: A Wi-Fi Based Indoor Positioning Approach
PI, #7200365, City University of Hong Kong Startup Grant, Oct 2013 – Sep 2015, HKD 191,504
The building occupancy monitoring is the premise of intelligent energy management and occupants’ behavior intervention. Current practice focus on utilizing integrated ambient sensors to identify the occupancy in small spaces, however, it is difficult to track occupancy in large scale commercial buildings due to the space and cost limits. To bridge this gap, this project proposes a coupled system that is able to easily track occupancy, detect occupant’s behavior pattern, and estimate their energy load through Wi-Fi-enabled devices. The system will be able to detect occupancy and monitor the energy using events through a Wi-Fi based indoor positioning system (IPS) and energy management system. With the information gathered from this research, the system will serve as reference for smart energy management and targeted behavior intervention in future development.