The Challenge
Handling the massive ingestion of data points and presenting actionable insights to city planners in real-time without latency.
The Solution
We implemented a scalable cloud infrastructure using edge computing to process data locally before sending summaries to the cloud. A 3D interactive map allowed officials to monitor city health at a glance.
Timeline
February 2023 — August 2024
Key Results
-25%
Traffic Congestion
Reduction in peak hours
+30%
Energy Efficiency
Optimisation of street lighting
1B+
Data Points
Processed daily
Methodology
01
Sensor Integration
Standardised protocols for diverse hardware types.
02
Data Pipeline
Built a streaming pipeline using Kafka.
03
Visualisation
Developed a WebGL-based control centre map.
04
AI Model Training
Trained models to predict traffic congestion.
