Promoting Human-Elephant Coexistence through Integration of AI, Real-Time Alerts, and Rapid Response

Version 1 : Received: 26 June 2024 / Approved: 28 June 2024 / Online: 29 June 2024 (00:05:49 CEST)
Version 2 : Received: 21 August 2024 / Approved: 22 August 2024 / Online: 22 August 2024 (12:00:20 CEST)

How to cite: Rastogi, S.; Bhattacharya, S.; Vimal, K.; Yadav, P.; Singh Negi, H.; Dinerstein, E.; Lee, A. T.; Shah, W. A.; Nagano, Y.; Hirari, S.; Gulick, S. Promoting Human-Elephant Coexistence through Integration of AI, Real-Time Alerts, and Rapid Response. Preprints 2024, 2024062065. https://doi.org/10.20944/preprints202406.2065.v2 Rastogi, S.; Bhattacharya, S.; Vimal, K.; Yadav, P.; Singh Negi, H.; Dinerstein, E.; Lee, A. T.; Shah, W. A.; Nagano, Y.; Hirari, S.; Gulick, S. Promoting Human-Elephant Coexistence through Integration of AI, Real-Time Alerts, and Rapid Response. Preprints 2024, 2024062065. https://doi.org/10.20944/preprints202406.2065.v2

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MDPI and ACS Style

Rastogi, S.; Bhattacharya, S.; Vimal, K.; Yadav, P.; Singh Negi, H.; Dinerstein, E.; Lee, A. T.; Shah, W. A.; Nagano, Y.; Hirari, S.; Gulick, S. Promoting Human-Elephant Coexistence through Integration of AI, Real-Time Alerts, and Rapid Response. Preprints 2024, 2024062065. https://doi.org/10.20944/preprints202406.2065.v2

APA Style

Rastogi, S., Bhattacharya, S., Vimal, K., Yadav, P., Singh Negi, H., Dinerstein, E., Lee, A. T., Shah, W. A., Nagano, Y., Hirari, S., & Gulick, S. (2024). Promoting Human-Elephant Coexistence through Integration of AI, Real-Time Alerts, and Rapid Response. Preprints. https://doi.org/10.20944/preprints202406.2065.v2

Chicago/Turabian Style

Rastogi, S., Sasaki Hirari and Steve Gulick. 2024 "Promoting Human-Elephant Coexistence through Integration of AI, Real-Time Alerts, and Rapid Response" Preprints. https://doi.org/10.20944/preprints202406.2065.v2

Abstract

Human-elephant conflict has become a conservation challenge in Asia and Africa resulting in considerable human fatalities annually. We deployed an AI-embedded camera-alert system in a conflict hotspot in West Bengal, India to determine if AI algorithms could accurately detect elephants and if real-time alerts that triggered a rapid response could prevent serious incidents. The system successfully detected elephants near villages (266 events) and transmitted real-time alerts (x̄ = 42 seconds) permitting quick response by field personnel to prevent conflict (x̄ = 18.2, SD = 12.4 min to arrival). Matriarch herds of elephants were detected mostly at night when human traffic was minimal; lone adult bulls, the class most prone to conflict, were detected day and night. Frequent detections of humans (33,217 events) on routes used by elephants highlighted the value of real-time monitoring especially during daytime. Twelve human fatalities and eighteen serious injuries occurred in the study area between 2019-2023 but none during deployment of the AI system, supporting the hypothesis that alerts integrated with rapid response can reduce conflict. Loss of lives and livelihoods underscore the urgency of applying this approach to other elephant ranges and adapting AI models to conflict-prone species to provide early warning and promote coexistence.

Keywords

Human-Elephant Conflict, Coexistence, TrailGuard AI, Real-time Alert, Rapid Response

Subject

Environmental and Earth Sciences, Sustainable Science and Technology

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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