Case Studycomputer visionmmwave radarvirtual fencingembedded iot
Virtual Fencing System Reduces Human–Wildlife Conflict
6.9
Researchers in Kenya designed and implemented an IoT- and machine learning–based virtual fencing system to mitigate human–wildlife conflict, integrating YOLOv11 on a Raspberry Pi 5, RD-03D mmWave radar, NEO-6M GPS and SIM800L GSM for alerts. The model classified giraffes with 70–90% confidence and the system sends SMS location alerts, offering a low-cost, scalable alternative to physical fences for conservancy-adjacent communities.
Key Points
- 1Implements YOLOv11 vision, RD-03D mmWave radar, Raspberry Pi 5, NEO-6M GPS and SIM800L GSM.
- 2Provides species-specific detection (giraffe 70–90% confidence) enabling targeted alerts and reduced false alarms.
- 3Enables low-cost, scalable virtual fences that send SMS location alerts for real-time community response.
Scoring Rationale
Practical, reproducible IoT–ML prototype demonstrates clear utility; limited by localized proof-of-concept scope and shallow evaluation.
Sources
Public references used for this report.
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