AI system
- System
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TrailGuard AI camera-alert system with embedded AI (Intel Myriad processor; detectors trained with CVEDIA synthetic renderings)
- Model
-
Not assessed
- Release
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Exact release not established.
- Application developer
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RESOLVE (design) with CVEDIA Ltd (AI training); units manufactured by Nightjar
- Role
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The camera’s models detected tigers and people and transmitted selected images.
- Configuration
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The deployment used the 2022 pilot units.
- Inputs and outputs
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Not assessed
- Autonomy
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Not assessed
- Workflow
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Camera units with on-device detectors for tigers and humans placed on trails. Cellular or satellite transmission to officials' phones and email. Forest department staff willing to act on transmitted images. Research consortium funding (Tigers United, Clemson, Khosla grant).
- Human oversight
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Not assessed
- Relation to AI
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Embedded AI on the camera selected and transmitted images of tigers and humans within 30 to 42 seconds. That is the mechanism in the developer-affiliated BioScience paper. Whether any alert changed what villagers or officials did is not documented.
- AI contribution
-
Embedded AI on the camera selected and transmitted images of tigers and humans within 30 to 42 seconds. That is the mechanism in the developer-affiliated BioScience paper. Whether any alert changed what villagers or officials did is not documented.
Benefits
- Outcome identifiers
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Not assessed
- Benefit
-
tiger notifications arrived 30 to 42 seconds after detection
- Category
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Improved Environmental Sustainability
- Status
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Not assessed
- Beneficiary groups
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People. Organizations. Society.
- Beneficiaries
-
Not assessed
- Reach
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Not assessed
- Distribution and access
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Not assessed
- Duration
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Not assessed
- Expected?
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Yes
- Costs and harms
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Not assessed
Measurement
- Studies
-
Not assessed
- Study design
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Not assessed
- Measurement
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Not assessed
- Setting and sample
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Not assessed
- Measures
-
tiger notifications arrived 30 to 42 seconds after detection
- Comparison
-
Assumed alternative: conventional camera traps tripped by passing boars or falling leaves
- Results
-
Assumed comparison. Result: almost wiped out false alarms.
- Additional value from AI
-
Not assessed
- Limitations
-
Not assessed
- Denominators
-
Not assessed
- Materials for replication
-
Not assessed
Money
- Kind of value
-
Not assessed
- Amount
-
Not assessed
- Currency and prices
-
Not assessed
- Period and unit
-
Not assessed
- Realization
-
Not assessed
- Recipients and payers
-
Not assessed
- Gross or net
-
Not assessed
- Included costs
-
Not assessed
- Comparison
-
Not assessed
- Method
-
Not assessed
- Return and payback
-
Not assessed
People and places
- Participants
-
Developer: RESOLVE (design) with CVEDIA Ltd (AI training); units manufactured by Nightjar. Operator: Madhya Pradesh and Uttar Pradesh forest departments with Clemson University, Wildlife Institute of India and Global Tiger Forum.
- Jurisdictions
-
Benefit: Kanha-Pench corridor, Madhya Pradesh,
India. Developer: 
United States. Operator: India. - Ownership and control
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Not assessed
- Dependencies
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Not assessed
- Cross-border connections
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Not assessed
- Geopolitical implications
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Not assessed
Follow-up
- Conditions for replication
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Transmission path within cell range or via the slower protocol. Detector accuracy high enough to avoid alert fatigue. Investigative follow-up by forest and police authorities. Battery life and concealment of units.
- Replication attempts
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2 follow-up entries. Benefit recurred: 1. Outcome unresolved: 1.
- Later findings
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6 October 2023. AFP reported that RESOLVE's Eric Dinerstein was widening the TrailGuard rollout to larger animals such as elephants; the BioScience article also notes continued transmission from Kanha-Pench and other reserves.
- Availability
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Not assessed
- Institutional decision
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Not assessed
- Grounds
-
Not assessed
- Action and result
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Not assessed
- Success criterion
-
Not assessed
Evidence
- Source numbers
-
AIBD-0358-source-0001–0002
- Citations
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Numbered references below.
- Language
-
Not assessed
- Source relationships
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Developer, Independent
- Original evidence
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Not assessed
- Access and versions
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Not assessed
- Supported findings
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Not assessed
- Evidence links
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Not assessed
- Evidence strength
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Not assessed
- Missing evidence
-
Not assessed
Grades
- Assessed benefits
-
People. Organizations. Society.
- Depth
-
People: Not assessed. Organizations: 1. Society: Not assessed.
- Reasons
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People: No identified individual beneficiary. Villagers near three units are mentioned only as sources of daily notifications. Organizations: Researchers and forest department officials received tiger alerts 30 to 42 seconds after detection during the two-month pilot. No action taken on an alert is documented. Society: No measured effect on human-wildlife conflict in the two-month pilot of 12 cameras.
- Observed or intended
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Not assessed
- Rubric
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Not assessed
- Assessor and date
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Not assessed
- Alternative assessments
-
Not assessed
- Fill
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Independently reported
Entry details
- Kind
-
Not assessed
- Related entries
-
Not assessed
- Field
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Wildlife protection and human-wildlife conflict. State forest departments and conservation research partners.
- Purpose
-
Real-time detection of tigers and humans for human-wildlife conflict early warning and anti-poaching. The reported detections and follow-up were the intended use.
- Dates
-
Date basis unassessed: 2023 (precision unassessed). Updated: 21 October 2026.
- Stage
-
Not assessed
- Version
-
SHA-256: b8c957579f35…
References
- Other identifiers
-
Not assessed
- Category mappings
-
Not assessed
- Brief
-
Not assessed
- Revisions
-
6 revisions. Latest: 21 October 2026.
Sources
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Peer-reviewed study Developer
Dertien, J. S., Negi, H., Dinerstein, E., Krishnamurthy, R., Negi, H. S., Gopal, R., Gulick, S., Pathak, S. K., Kapoor, M., Yadav, P., Benitez, M., Ferreira, M., Wijnveen, A. J., Lee, A. T. L., Wright, B., Baldwin, R. F. (2023). Mitigating human-wildlife conflict and monitoring endangered tigers using a real-time camera-based alert system. BioScience 73(10), 748-756. doi:10.1093/biosci/biad076
We successfully captured and transmitted the first images of tigers using cameras with embedded AI and detected poachers.
-
News report Independent author
AFP (2023). AI of the tiger: Tiny camera 'protects' predator - and people. Taipei Times, 6 October 2023.
The research claims the cameras were immediately effective, picking up a tiger just 300 meters from a village, and on another occasion identifying a team of poachers.