Introducing MASNRD
Multi-Agent Search and Rescue Drone (MASNRD) is an urban multi-drone search and rescue (S&R) system that uses WiFi-based signal detection to locate victims.
MASNRD can conduct autonomous probabilistic searches for disaster victims with inputs by drone operators, facilitating efficient distributed reconnaissance of large disaster zones. Specifically, MASNRD locates WiFi-enabled devices (such as smartphones) trapped under the debris and provides real-time and accurate data to optimise S&R efforts.
Team members
Instructors:
Malika Meghjani
Writing Instructors:
Tay Zi Dong Patrick
According to the World Meteorological Organization
between 1970 and 2019
MASNRd proposITION
Search & Rescue Optimization
OPERATIONAL IN LOW LIGHT
NON-INVASIVE
PENETRATING DETECTION
MULTI-AGENT SCALABLE OPERATIONS
Our Components
Sensor
Cellular 2.4GHz WiFi signal detection
Mission Control
Real-time control and feedback
Drone
Multi-agent autonomous search
Simulation
Scalable testing environment
Cellular 2.4Ghz WiFi Signal Detection
Sensor Prototyping
Prototype 1: PoC WiFi Detection Sensor
- Detection capability within a 2-meter range
- Missing frequency and signal strength details
Prototype 2: Multi-directional Sensor
- Extended detection range
- Operates within 100 MHz spectral bandwidth
- Missing direction details
Prototype 3:Spectrum Analyser (TinySA)
- Accurate frequency and amplitude analytics
- Wall-penetrating signal detection
- No API for interfacing
Final Prototype:Software-Defined Radio (HackRF One)
- Precise frequency and amplitude analysis
- Customizable frequency channel
- Includes a directional waveguide
Multi-Agent Autonomous Search
Drone
REal-time control and update
Mission Control Graphical User Interface
1. Hotspot selection
2. Clustering
3. Task Assignment
4. Cluster search
Scalable testing environment
Simulation
Physical integration
Real-World Demonstration
Acknowledgements
Mr. Jonathan Tan provided instrumental industry insights and opportunities that have significantly shaped our project’s approach and understanding of its real-world application.
Assistant Professor, Dr. Malika Meghjani, offered invaluable guidance and expertise, driving our project’s success and fostering our personal and professional growth with her dedication and support.
Mr. Tay Zi Dong, Patrick, enhanced our communication skills with his passionate mentorship and meticulous feedback, significantly impacting our project’s presentation and clarity.
Dr. Kwan Wei Lek provided valuable feedback on our presentation and sensor hardware design, which helped improve our project’s quality and effectiveness.
Dr. Foong Shaohui assisted in booking the drone arena, which is essential for the real-world testing and refinement of our prototype.
