Projects
UAV-Based Emergency Rescue
Led by Professor Mo Li from Computer Science and Engineering, this project aims to provide rapid emergency response in remote hiking areas like Sharp Peak in Sai Kung. Utilizing an open-source UAV platform equipped with electronic layers and multi-layer payload units, it ensures swift delivery of critical medical supplies such as AEDs and EpiPens. Compared to traditional emergency services that can take up to 40 minutes to reach these areas, UAVs can reduce this time to just 10 minutes. The project features intelligent path planning and a comprehensive management dashboard, enhancing the efficiency and effectiveness of emergency rescue operations in hard-to-reach locations.
Development Strategies of Air Transportation Networks
This project is funded by the "Strategic Public Policy Research Funding Scheme" of the HKSAR Government. It aims to enhance air transportation in the region through strategic planning, infrastructure optimization, and technological innovation. The research focuses on capacity expansion, environmental sustainability, and regulatory integration to create a more efficient and interconnected air mobility ecosystem. By addressing key challenges, the project will support the Greater Bay Area's economic growth and global competitiveness.
Air-sea Coordinated Cruising and Risk Avoidance
Under the leadership of Professor Fumin Zhang, this project at a prestigious university focuses on developing a cutting-edge system for coordinated operations between airships and autonomous boats. The system is designed to enhance maritime activities by leveraging drones for a variety of tasks, including monitoring and logistics. By incorporating advanced real-time environmental monitoring, the project aims to significantly improve the safety and efficiency of maritime operations while effectively managing risks. This initiative represents a forward-thinking approach to making maritime endeavors more intelligent and sustainable.
Building the Data Foundation for the Low-Altitude Economy
Under Professor Xiaofang ZHOU's guidance, this project aims to establish a foundational data platform for the low-altitude economy (LAE). The platform will support the LAE system using the OpenSILAS framework, setting a reference for future technologies and applications. It includes layers for access, application, support, data, and infrastructure, ensuring efficient data management and task coordination. This initiative is crucial for advancing the safety and innovation of low-altitude operations.
Flight Safety and Noise Control
Led by Professor Xin Zhang from the Mechanical and Aerospace Engineering department, this project focuses on enhancing flight safety and managing noise pollution. It involves sound source modeling to differentiate between tonal and broadband noise. The project uses advanced simulations to model sound propagation, analyzing how it interacts with urban environments through reflection, refraction, absorption, and shadow zones. The ultimate goal is to develop noise-informed route planning to minimize noise impact on urban areas. This initiative not only aims to improve the safety of flight operations but also to significantly reduce noise pollution, thereby enhancing the quality of life in urban settings.
Digital Twin-based Drone Management Platform
Under the leadership of Professor Jack Chin Pang Cheng from Civil and Environmental Engineering, this project aims to develop a drone management platform using digital twin technology. The platform integrates real-time information of drones with a digital twin for efficient flight path planning and task execution. It utilizes drones equipped with advanced sensors for urban system health monitoring, including LiDAR, cameras, and IMUs, to inspect infrastructure and assess environmental conditions. Additionally, it develops a drone-based rapid urban rescue system with lifesaving equipment, enhancing emergency response capabilities. This initiative promises to revolutionize urban management and emergency response through advanced drone technology and digital twin integration.
Low-Altitude Communication and Networking
Led by Professor Mo Li, this project focuses on developing a low-altitude communication network using LoRa and 5G technologies. It employs CSS spreading to create an interference-resistant network that extends coverage to the university campus and nearby islands. The network supports multi-drone communication, catering to varying latency requirements, and optimizes link resource allocation and parallel demodulation to handle high-traffic, concurrent communications efficiently. This initiative aims to enhance connectivity and data transfer capabilities for low-altitude applications, paving the way for more robust and reliable drone operations.
