Page 268 - AI for Good Innovate for Impact

AI for Good Innovate for Impact

2�3 Future Work

Next Phases:

• Develop machine learning models for predicting future conflicts
• Add smart deterrents (e.g., water cannons, drone surveillance)
• Build mobile app for real-time visualization and interaction
• Deploy admin dashboard for centralized monitoring
• Expand GPS collar deployments and cloud infrastructure
• Integrate new datasets (crop seasons, weather, land use)
Launch wider training programs for communities and rangers

Adapt the platform to other species (e.g., buffalo, hippos)

3 Use Case Requirements
• REQ-01: GPS collars for real-time elephant tracking
• REQ-02: AI-powered geofencing to identify high-risk zone entry
• REQ-03: GSM modules to send alerts and control deterrent systems
• REQ-04: Microcontrollers (Arduino UNO, ESP32) for local processing
• REQ-05: Deterrent devices (flashing lights, bee sounds)
• REQ-06: Solar or battery-powered units for off-grid operation
• REQ-07: SD card storage for logging movement data
• REQ-08: Mobile interface for alert access by local users
• REQ-09: Community training and awareness programs
• REQ-10: Future ML module for predictive conflict prevention

4 Sequence Diagram

5� References

[1] Groom, R.J. & Western, D. (2013). Oryx, 47(1), 34-40.
[2] Fernando, P. et al. (2005). Biodiversity and Conservation, 14(10), 2465–2481.
[3] World Bank (2022). Community-Based Wildlife Conservation Toolkit.
[4] TAWIRI Reports (2021–2023).
[5] United Nations SDGs – https:// sdgs .un .org/ goals

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