INFRASTRUCTURE · VISION AI

Real Time Monitoring & Intelligent Asset Tracking at National Scale

Real time monitoring and intelligent tracking systems for enterprise infrastructure. Vision AI and sensor fusion across 4,000+ critical nodes.

Vision AIInfrastructureEdge AI

Timeline 2024
Industry Infrastructure · Vision AI
Services Vision AI · Edge AI · IoT Engineering · Real Time Monitoring
Platform Web · Edge AI · IoT
Technologies OpenCV, TensorFlow, AWS IoT, React, Python, MQTT
Team Size 10 Engineers
Country Global

THE PLATFORM

Vision AI and Sensor Fusion Across 4,000+ Critical Nodes

A national infrastructure authority required real time visibility and intelligent monitoring across thousands of distributed critical assets, including bridges, substations, transport hubs, and utility nodes, spread across a large geographic footprint.

Spritle engineered a Vision AI and sensor fusion platform that processes live feeds and telemetry from 4,000+ nodes, detecting anomalies, predicting failures, and triggering alerts in real time, all from a centralised operations dashboard.

Edge AI inference keeps latency under 20ms per node, enabling immediate response without reliance on cloud round trips for time critical detection.

Problem Statement

The Challenges We Were Solving

Technical 01

Scale Without Latency

Monitoring thousands of distributed nodes in real time demanded edge inference capability. Cloud only architectures introduced unacceptable latency for safety critical detection.

Technical 02

Heterogeneous Sensor Inputs

Assets reported data across incompatible protocols and formats. CCTV feeds, MQTT telemetry, vibration sensors, and thermal cameras all required unified ingestion and processing.

Business 03

Reactive Maintenance Model

Infrastructure failures were addressed reactively, with no predictive capability. Unplanned downtime was costly and, in some cases, a safety risk.

LET'S TALK

Need real time infrastructure intelligence?

Spritle builds Vision AI and Edge AI systems for complex, distributed environments.

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OUR SOLUTION

Unified Vision AI & Sensor Fusion Platform

Spritle built a multi layer monitoring platform combining computer vision, IoT sensor fusion, and edge AI inference, giving operators a single pane of glass for 4,000+ critical infrastructure nodes with sub-20ms anomaly detection.

Edge AI Inference Engine

On device AI models process visual and telemetry data locally at each node, detecting anomalies and triggering alerts in under 20ms without cloud dependency.

Multi-Source Sensor Fusion

Unified ingestion layer normalises data from CCTV, thermal cameras, vibration sensors, and MQTT telemetry, creating a consistent real time state for every node.

Predictive Failure Detection

Machine learning models trained on historical sensor patterns predict component failures 48 to 72 hours before occurrence, enabling scheduled maintenance and preventing unplanned downtime.