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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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1

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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