Promoting human–elephant coexistence through integration of <scp>AI</scp> , real‐time alerts, and rapid response

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 () permitting quick response by field personnel to prevent conflict (, 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 and 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.

Authors

Institutions

Publication Details

Journal
Conservation Science and Practice
Published
2025-11-11
DOI
https://doi.org/10.1111/csp2.70186
Citations
1
Primary Topic
Wildlife Ecology and Conservation
Type
article
Field-Weighted Citation Impact
1.72
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Promoting human–elephant coexistence through integration of AI , real‐time alerts, and rapid response

Steve Gulick, Sayan Bhattacharyya, Andy T. L. Lee, Nitin Sekar et al.
1 citations
Conservation Science and Practice
Wildlife Ecology and Conservation
1.72
article

Promoting human–elephant coexistence through integration of AI , real‐time alerts, and rapid response

Steve Gulick, Sayan Bhattacharyya, Andy T. L. Lee, Nitin Sekar, Eric Dinerstein, Kumar Vimal, Sankarshan Rastogi, Wajid Ali Shah, Yushi Nagano, Sasaki Hirari
article en
1 citations

Abstract

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 () permitting quick response by field personnel to prevent conflict (, 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 and 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.

Conservation Science and PracticeVol. 7(12)
Japan International Cooperation Agency (JP), Conservation International (US), Smithsonian Conservation Biology Institute (US), Government of West Bengal (IN), Government of Uttar Pradesh (IN), Resolve Therapeutics (United States) (US), Singapore Management University (SG)
Openalex Percentile: Top 12%
Wildlife Ecology and Conservation
1.72
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.