AI Enabled Street Lighting Optimization

About the Customer

A United States based technology company building an AI and spatial analytics powered platform to transform outdoor lighting for energy savings, transportation safety, environmental protection, and crime prevention.

Situation

The client needed accurate, AI-ready geospatial datasets to power their lighting optimization platform. This included precise mast angle updates, landscape classification, and standardized pre-audit layers to improve model performance.

Task

• Update mast angles for all identified streetlights.
• Extract and classify roads, intersections, buildings, and landscapes.
• Deliver pre-audit light data, building footprints, and road networks.
• Ensure all outputs meet AI/ML data quality and schema standards.

Action/Approach

• Updated streetlight mast orientations using client inputs and spatial data.
• Performed feature extraction and classification for roads, intersections, and buildings.
• Structured datasets using AI-friendly schemas and applied strict QA/QC checks.
• Used AI-assisted workflows to enhance accuracy, speed, and consistency.

Tools / Software

• QGIS 3.42
• Google Earth Pro
• Google Maps

Result

AABSyS delivered clean, precise, and AI-ready spatial datasets, enabling:

• Improved lighting optimization and energy efficiency
• Enhanced transportation and public safety
• Better environmental and crime-prevention analytics
• Faster and more accurate AI model performance