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12 AI Use Cases Connect CCTV Events with Operational Action
FuelTrans combined edge video analytics, central dashboards and auditable workflows to help teams detect, investigate and close safety and operating-procedure exceptions.
Client
Challenge
Safety issues, fuel decantation deviations and departures from operating procedures were identified only after staff manually reviewed CCTV footage. Station teams lacked real-time alerts and a consistent evidence trail to investigate, validate and close exceptions.
Head office had no unified view of camera events, recurring incidents or operational trends across the implemented station scope. Existing CCTV also offered limited actionable information on queues, dwell time and customer movement.
The company needed to turn video footage into timely operational information. The solution had to combine event detection with clear responsibilities, escalation paths and an auditable closure process, while making use of the camera feeds available at its outlets.
Head office had no unified view of camera events, recurring incidents or operational trends across the implemented station scope. Existing CCTV also offered limited actionable information on queues, dwell time and customer movement.
The company needed to turn video footage into timely operational information. The solution had to combine event detection with clear responsibilities, escalation paths and an auditable closure process, while making use of the camera feeds available at its outlets.
Solution
FuelTrans designed a video-intelligence operating model around the CCTV and network video recorder setup at the retail outlets. Cameras covered critical zones including decantation, dispensing and queueing areas, restricted spaces, and entry and exit points. Edge-based AI analysed video locally to identify configured safety, procedural, security and customer-experience events.
Each detected event was time-stamped, classified and routed to a central dashboard with supporting visual evidence. Relevant users could receive notifications, review the evidence, take action and close the event through an auditable workflow. This connected detection with investigation and follow-up.
The delivery approach prioritised use cases according to operational risk, business value and implementation readiness. Site assessments reviewed camera coverage, feed quality, connectivity and visibility of critical zones. Solution design defined camera-specific use cases, alert rules, user roles, escalation paths, dashboard views and evidence-retention requirements.
The solution combined existing IP CCTV feeds, edge AI and computer vision with the FuelTrans Station Manager dashboard and cloud-based event management. Role-based workflows and notification integrations supported the operating model. The team also established KPI targets for camera availability, alert acknowledgement, exception closure, safety-event response and reduced manual review.
Each detected event was time-stamped, classified and routed to a central dashboard with supporting visual evidence. Relevant users could receive notifications, review the evidence, take action and close the event through an auditable workflow. This connected detection with investigation and follow-up.
The delivery approach prioritised use cases according to operational risk, business value and implementation readiness. Site assessments reviewed camera coverage, feed quality, connectivity and visibility of critical zones. Solution design defined camera-specific use cases, alert rules, user roles, escalation paths, dashboard views and evidence-retention requirements.
The solution combined existing IP CCTV feeds, edge AI and computer vision with the FuelTrans Station Manager dashboard and cloud-based event management. Role-based workflows and notification integrations supported the operating model. The team also established KPI targets for camera availability, alert acknowledgement, exception closure, safety-event response and reduced manual review.
Impact
The deployment covered 12 configured AI use cases and reused 100% of the onboarded CCTV feeds within the implemented station scope. This extended the value of the camera estate by adding automated event identification and central review.
All configured events were routed to the central dashboard, establishing an operating model ready for 24-hour monitoring. Time-stamped visual evidence and auditable workflows gave station and head-office teams a common basis for reviewing exceptions and tracking their closure.
The platform brought safety monitoring, operating-procedure governance and customer or queue analytics into one environment. The defined KPI targets provided a basis for measuring response times, closure performance and review effort as the company assessed the value of the deployment and considered further expansion.
All configured events were routed to the central dashboard, establishing an operating model ready for 24-hour monitoring. Time-stamped visual evidence and auditable workflows gave station and head-office teams a common basis for reviewing exceptions and tracking their closure.
The platform brought safety monitoring, operating-procedure governance and customer or queue analytics into one environment. The defined KPI targets provided a basis for measuring response times, closure performance and review effort as the company assessed the value of the deployment and considered further expansion.
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