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Real-Time Intrusion & Unauthorized Zone Detection in High-Security Sub-Stations
An electric utility provider managing 120 unstaffed high-voltage electrical sub-stations protected by perimeter fence security cameras.
Runs onArjuna- false security alarms reduced
- 96%false security alarms reduced
- unauthorized sub-station perimeter breaches within 15 seconds
- 100%unauthorized sub-station perimeter breaches within 15 seconds
How the work runs
The pressure that made this worth automating, the steps the system runs, and what came out the other side.
Pressure & Trigger Points
- Perimeter intrusions by copper thieves and trespassers created severe electrical shock hazards and power grid disruption risks.
- Legacy motion detection cameras triggered thousands of false alarms monthly due to blowing foliage, stray animals, and rain drops.
- Security guards ignored alarm notifications due to severe alert fatigue.
The run · 5 operational steps
Click any step to inspect telemetry signals, model reasoning, and governance gates.
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AI Human & Vehicle Classification
Arjuna filters video streams, distinguishing human trespassers and vehicles from animals, weather, and vegetation motion with 99% accuracy.
Input Signal:
Real-time operational telemetry & queue
Reasoning Pattern:
MCP grounded vector inference
Governance Gate:
Policy constrained with audit write-back
Verified Business Outcomes
- False security alarms reduced by 96%, eliminating dispatcher alert fatigue.
- Intercepted 100% of unauthorized sub-station perimeter breaches within 15 seconds of fence line crossing.
- Prevented copper theft equipment damage, saving an estimated $1.2M in annual replacement expenses.
Capabilities this relies on
- vision perception
- anomaly detection
- alert routing
- policy compliance
- in boundary deployment
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