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OVERVIEW:-
Traditional wildlife monitoring is labor-intensive, invasive, and lacks real-time capability, limiting effective conservation. There is a need for an automated AI-based system to accurately detect and track wildlife, providing timely data, early threat detection, and stronger support for ecological research.
Gaps:-
- Lack of real-time monitoring; data is often delayed.
- Poor scalability across large or remote areas.
- Limited integration of multi-source data (satellites, drones, sensors).
- Errors in species identification.
- Complex data management with few user-friendly platforms.
- Minimal community engagement or citizen involvement.
Who Benefits:-
- Rangers and enforcement agencies: quicker detection of threats like poaching.
- Wildlife tourism: healthier ecosystems boost eco-tourism.
- Local communities: gain education, jobs, and incentives for conservation.
- Environmental organizations: better data to guide and prove impact.
Why It Matters To Me:-
Conserving wildlife protects biodiversity, ecosystem balance, and essential services like pollination, climate regulation, and clean water. It also supports sustainable livelihoods, tourism, and fulfills our ethical duty to protect nature for future generations.
Technical Details:-
- Sensors: thermal, infrared, motion detectors.
- Security: encryption, authentication, blockchain.
- Processing: edge/cloud computing for real-time alerts.
- Integration: camera traps, drones, satellites, acoustic sensors, eDNA sampling.
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