Our group aims to improve the performance of building and construction industry through research in advanced technologies and management approaches. The studies cover construction safety management, construction automation, modular construction, building and city energy management and etc.
We have received funding from both industry and government to work on fundamental and applied research.
- Construction Safety Management
- Construction Automation
- IT and Sensing in Construction
- Building Information Modelling
- Green and Intelligent Building
- Intelligent and Automated Jobsites
Current Group Members
Past Group Members
By 2025, global construction is expected to grow 70% according to Global Construction and Oxford Economics. With this growth comes a need to focus on jobsites safety and efficiency because the construction industry has one of the highest accident and fatality rates among other major industries, with more than 60,000 fatal accidents each year worldwide. In Hong Kong, construction job site injuries account for nearly 20% of all work related fatalities and injuries. As one of the most dangerous jobs in the world, this needs should be addressed swiftly.In order to deal with the increasingly complex and challenging construction environment, recent studies have focused on adopting sensing and communication technologies to revolutionize the way of traditional construction safety management. Such applications can provide workers with the communication and information tools for effectively identifying and reporting safety hazards on jobsites. This is a proactive approach that helps workers improve s ituational awarenessthrough an early warning mechanism, for example when a construction worker is exposed to dangerous hazards, alarms will be triggered automatically for both the worker and the supervisor. However, these applications were developed under the assumption that the data collected from sensors is perfect, which is not true. Although sensor networks can provide many benefits, they are more susceptible to malfunctions that can result in imperfect data. Imperfect data may lead to missing detections or false alarms, which drastically reduces the significance of the use of sensors and even results in severe consequences Therefore; there is a great need to create new solutions to make the existing ones more robust, accurate and precise. The research objective of this proposal is to seek new approaches to develop a more reliable and high- performance system for construction safety management. Particular attention focuses on the data processing and decision support level. Data fusion, stochastic programming and optimization techniques will be adopted for algorithm and decision making mechanism development in this project. A testbed with sensing devices to represent the intelligent construction jobsite will be designed and implemented to test and validate the performance of our proposed improvement mechanisms for jobsite autonomous safety monitoring systems. In terms of broader impact, our application can significantly benefit a large industry worldwidefrom improvements in practices. In addition, this research has considerable potential to impact other domains (e.g. productivity analysis) since the problems of imperfect data are generic in information extraction and decision making, Moreover, to ensure significant impact, we will combine the project’s research efforts with both educational efforts and industrial programs.
Hydro turbines are generally considered a clean power producer. There have also been negative consequences, mostly associated with the dams normally required for power production. Dams are altering the natural ecology of rivers, potentially killing fish, stopping migrations, and disrupting peoples’ livelihoods. A new design of hydro turbine based on a different working principle is needed. The proposed new turbine is capable of generating renewable energy in turbulent wind/water and suitable for use in densely populated cities. Due to the recommendation of previous reviewers, the proposal is restricted to water power only. The axis of rotation of the new turbine can be vertical or horizontal. The blades can be supported at multiple locations so that the structure is much stronger than most existing ones which allow for just one point of support at the hub. Therefore, the material requirement is less demanding and cost can be reduced. A small model, as shown in Figure 1, has been built to demonstrate the working principle. In brief, the model, as shown in Figure 2 and illustrated by the plan view in Figure 5, consists of four flat blades, each of which is fixed to one of the four planet gear wheels. Each planet gear wheel is connected to the central gear wheel (the sun wheel) via an intermediate wheel. The tooth numbers of the sun wheel, the intermediate wheel and the planet wheel are in such a ratio that when the sun wheel turns 180 degrees, each planet wheel turns only 90 degrees. Alternatively, the dummy wheel can be substituted by a bicycle or posi-chain (Figure 6) to eliminate noise. When properly aligned, each blade has the maximum exposed area along the flow in receiving the drag force but minimum exposed area moving against it when returning. The device can be completely submerged and works in cyclic flow induced by waves and tides. Research works towards the production of a prototype are described in detail in Part II of this application. The Hong Kong Housing Department has already shown interest in the proposed turbine and they have agreed to support the project by providing space for prototype testing. Yau Lee Construction Ltd has also agreed to provide laboratory space for manufacturing the prototypes. Negotiation is going on to implement a real one in Lamma Island. Some value added applications including water metering without wire and condition monitoring against leakage are investigated.
The objective of the proposed research is to study the theoretical foundation of a personalized construction safety information presentation system (PCSIPS), which changes the way of information presentation to reduce the information and cognitive load at the individual level. The construction industry is increasingly dependent upon the advanced information technologies for information generation and communication. With the wide adoption of these technologies, a large amount and variety of information (e.g., entities’ locations, IDs, environmental data and etc.) can be generated for supporting construction management tasks on jobsites. The collected information has tremendous value but the volume is far beyond construction practitioners’ capacity to fully understand and analyze it. A new challenge has arisen: cognitive overload due to information redundancy. According to the Cognitive Load Theory proposed by Sweller, human cognition has a very limited and finite information processing capacity. There exists an apparent gap between the overwhelming information available on sites and the limited processing capacity. This gap will widen in the future as more diverse real-time information is available due to the increasing adoption of ICT on jobsites. Too much information and inappropriate presentation of the information can lead to cognitive overload, causing decreased performance in safety management tasks and/or having an adverse effect on decision making. To solve this problem, it requires a successful construction safety information delivery mode, in which the right information is delivered to the right person at the right time for the right task, instead of the all the information being delivered at once to anyone regardless of a worker’s duties. Therefore, a PCSIPS for construction safety practitioners that can reduce the personal’s cognitive load is an urgent need. Computer visualization engineering has become critical for supporting efficient and effective construction safety information management, which offers new ways to present information, such as charts and maps etc. It makes information more memorable, and helps construction safety professionals understand complex information more effective and further aids in decision-making. This proposal points at the fundamental understanding about how the diverse information and its presentation affects the cognitive load of different safety management tasks, and how cognitive load is associated with the safety decisions making performance. If successful, a PCSIPS to reduce the cognitive load of safety professionals can be designed and developed, helping the professionals to make decisions more efficiently and discover new knowledge more effectively. In addition, given that the global construction industry is expected to be worth $10.3 trillion in 2020, any effort to increase construction efficiency will lead to enormous cost savings to societies around the world. Although this research focuses on construction safety management, the theory and approach in this proposal can be applied to other domains suffering from information overload.
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