Community-Level Low-Altitude Drone Knot for Last-Mile Delivery & Fire Risk Monitoring
Project Description
This project designs and develops an integrated community low-altitude drone hub system to solve two core urban community pain points: efficient last-mile parcel delivery and real-time fire hazard monitoring for residential blocks.
Low-altitude drone station layout optimization: Model community spatial constraints, building height limits, pedestrian activity zones, and delivery demand distribution to generate optimal drone hub deployment plans, balancing construction cost, flight range, and service coverage.
Multi-task autonomous drone fleet control: Develop lightweight path-planning algorithms for hybrid missions—regular parcel distribution and emergency fire patrol. Drones carry visual and thermal imaging sensors to detect abnormal high-temperature zones, smoke, and fire hazards in residential buildings, green belts, and underground facilities.
Smart campus/community sustainable operation module: Integrate solar power supply for drone hubs, low-energy standby modes, and flight energy consumption optimization to align with carbon reduction and sustainable smart community targets.
Risk mitigation framework: Establish flight geofencing, real-time collision avoidance with buildings/obstacles, and fire alert linkage logic to notify property management and emergency responders instantly once risks are identified.
The research combines systems design, robotics, urban spatial planning, computer vision, and sustainable smart infrastructure, providing a complete prototype and decision support tool for future smart community low-altitude air mobility governance.
Low-altitude drone station layout optimization: Model community spatial constraints, building height limits, pedestrian activity zones, and delivery demand distribution to generate optimal drone hub deployment plans, balancing construction cost, flight range, and service coverage.
Multi-task autonomous drone fleet control: Develop lightweight path-planning algorithms for hybrid missions—regular parcel distribution and emergency fire patrol. Drones carry visual and thermal imaging sensors to detect abnormal high-temperature zones, smoke, and fire hazards in residential buildings, green belts, and underground facilities.
Smart campus/community sustainable operation module: Integrate solar power supply for drone hubs, low-energy standby modes, and flight energy consumption optimization to align with carbon reduction and sustainable smart community targets.
Risk mitigation framework: Establish flight geofencing, real-time collision avoidance with buildings/obstacles, and fire alert linkage logic to notify property management and emergency responders instantly once risks are identified.
The research combines systems design, robotics, urban spatial planning, computer vision, and sustainable smart infrastructure, providing a complete prototype and decision support tool for future smart community low-altitude air mobility governance.
Supervisor
XIANG, Changying
Quota
3
Course type
UROP1100
UROP2100
UROP3100
UROP3200
UROP4100
Applicant's Roles
Undergraduate students will take charge of modularized research tasks under supervisor guidance:
Literature review on urban drone delivery, fire monitoring UAVs, and low-altitude hub infrastructure;
Build community spatial datasets (building layout, population density, delivery demand, fire-prone areas) and conduct data cleaning & visualization;
Assist in coding basic path planning and thermal image fire recognition algorithms using Python;
Simulate drone hub deployment schemes via simulation tools, compare service efficiency and cost indicators;
Test small-scale drone prototype flight missions, record sensor data, and summarize experimental results;
Compile mid-term and final research reports, draw system framework diagrams, and participate in UROP project presentation.
Literature review on urban drone delivery, fire monitoring UAVs, and low-altitude hub infrastructure;
Build community spatial datasets (building layout, population density, delivery demand, fire-prone areas) and conduct data cleaning & visualization;
Assist in coding basic path planning and thermal image fire recognition algorithms using Python;
Simulate drone hub deployment schemes via simulation tools, compare service efficiency and cost indicators;
Test small-scale drone prototype flight missions, record sensor data, and summarize experimental results;
Compile mid-term and final research reports, draw system framework diagrams, and participate in UROP project presentation.
Applicant's Learning Objectives
Master interdisciplinary knowledge covering integrated systems design, urban low-altitude mobility, autonomous drone control, and computer vision-based hazard detection;
Gain hands-on experience in data collection, mathematical modeling, algorithm programming, and engineering simulation for smart urban infrastructure;
Learn standardized academic research workflows: literature screening, experimental design, result analysis, and formal technical report writing;
Develop critical thinking to balance technical performance, safety constraints, economic cost, and sustainability requirements for real community engineering scenarios;
Cultivate teamwork and independent problem-solving ability for complex smart city interdisciplinary research projects.
Complexity of the project
Moderate