Demo: InvisibleFence: Non-Lethal Edge-Optimized AI for Human Wildlife Coexistence and Crop Protection
Human-wildlife conflicts in residential/agricultural settings rely on ineffective deterrents like rodenticides or fences. We introduce InvisibleFence, a modular 3D-printed Vision Pod system with off-the-shelf deterrents. The Vision Pod fuses a 2K camera and 240° motion sensing with an edge-optimized pipeline trained on 44,000 wildlife images of eleven classes—achieving 86.7% mAP. Benchmarking YOLO variants (416p–2K) ensures performance. Upon detection, it sends MQTT commands to drive deterrent units—ultrasonic speakers or lighting/spray modules—that emit tones without affecting humans or pets. InvisibleFence creates adaptive zones that reduce false triggers and limit habituation.
Authors
- Nirmalya Roy (ORCID: https://orcid.org/0000-0003-4827-3393)
- Bipendra Basnyat (ORCID: https://orcid.org/0000-0002-0398-6894)
- Snehalraj Chugh (ORCID: https://orcid.org/0000-0002-1257-5114)
- Milind Rampure
- Elijah Polyakov
Institutions
- University of Maryland, Baltimore County (US)
Publication Details
- Published
- 2025-06-23
- DOI
- https://doi.org/10.1145/3711875.3734379
- Primary Topic
- Insect and Arachnid Ecology and Behavior
- Type
- article
- Field-Weighted Citation Impact
- 0.00