New AI Tool Increases Poacher Detection Accuracy
The low-cost system uses thermal video to flag human activity in protected areas, outperforming previous detection methods.
Updated on Oct. 15, 2026 in Artificial Intelligence
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In 2022, developer Anika Puri created ElSa, an AI tool designed to detect humans in thermal drone footage to support anti-poaching efforts. This system provides an automated way to monitor protected areas for illegal activity using affordable, off-the-shelf components.
Why it matters
The system addresses the need for cost-effective wildlife monitoring by reducing the time required for manual footage review. It offers a scalable alternative to high-cost thermal hardware, which is critical given the severe historical decline in forest elephant populations.
The ElSa system achieved 90.9% detection accuracy, representing a fourfold improvement over previous methods. Built with off-the-shelf hardware, the prototype costs approximately $300 to assemble, a significant reduction compared to commercial thermal monitoring systems that can cost $4,800.
The players
Anika Puri
A researcher and 2022 Davidson Fellow who developed the ElSa detection system to aid wildlife conservation.
ElSa
An AI-powered monitoring tool that uses thermal video analysis to detect human presence in protected wildlife areas.
The details
ElSa functions by analyzing thermal infrared video to identify human signatures. The software tracks specific movement patterns, such as speed and turning radius, while distinguishing human behavior from herd behavior. This processing allows the tool to flag potential human activity for subsequent review by park rangers, automating a task previously requiring constant human observation.
Timeline
1986: India prohibits domestic ivory sales.
1989: International commercial ivory trade is banned under CITES.
1991: India bans all imports of African ivory.
2002-2011: Africa's forest elephant population declines by 62%.
2018: Anika Puri observes ivory products for sale in Mumbai markets.
The Tech Race
This project aligns with long-standing efforts to enforce the 1989 CITES ban on international commercial ivory trade through technological intervention. It represents a shift from static regulation to active, automated enforcement in the field.
The system is currently in research-stage testing for real-world deployment in protected African forest regions. Once fully validated, the project aims to equip wildlife management agencies with low-cost monitoring solutions that function with standard, off-the-shelf hardware.
The takeaway
The development of ElSa highlights how low-cost, edge-accessible AI can address complex conservation monitoring challenges. Stakeholders should monitor future performance reports to see if the tool sustains its high accuracy when deployed across varied, high-density wildlife environments.
Further reading
For broader trends in machine vision applications, explore our coverage of Artificial Intelligence.
Source note: This article includes information reported by GG2.
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