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AI for Good Innovate for Impact
Use Case 17: AI-Powered RF Signal Locator for Advanced Search
and Rescue Operations
Organization: Mbeya University of Science and Technology (MUST)
Country: Tanzania
Contact Person(s):
Faisali Malukula Gwaya, faisali4gwaya@ gmail .com
1 Use Case Summary Table
Item Details
Category Climate change and natural disaster
Problem Addressed Challenges in accurately locating individuals during SAR
missions due to insufficient real-time location information.
Key Aspects of Solution AI-based RF signal triangulation; Real-time data analysis and
location prediction; Seamless integration with SAR operational
protocols.
Technology Keywords Artificial Intelligence, RF Localization, Machine Learning, Search
and Rescue, Signal Processing
Data Availability Private (planned data collection during pilot testing)
Metadata (Type of Data) RF Signal Strength, GPS Coordinates, Timestamps, Sensor
Metadata
Model Training and Fine-Tun- Supervised learning models trained on synthetic and real RF
ing datasets, with transfer learning for terrain adaptation.
Testbeds or Pilot Deployments Pilot tests in collaboration with SAR teams under controlled
environments.
Code Repositories Planned: Repository access post-validation.
2 Use Case Description
2�1 Description
This use case proposes an AI-enhanced solution to efficiently locate individuals during search
and rescue missions by triangulating RF signals emitted from mobile devices or beacons.
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