Illuminating the Future: Enhancing Streetlight Management with Noteworthy AI's Lighting Intelligence Suite

In today's rapidly evolving urban landscapes, efficient streetlight management is paramount for safety, energy conservation, and operational cost reduction. Noteworthy AI's Lighting Intelligence Suite offers a comprehensive solution to streamline lighting audits and asset management through advanced AI-driven features.

Lighting Intelligence Suite

Our Lighting Intelligence Suite is divided into two primary capabilities, each addressing key aspects of streetlight management:

Lighting Audit

Accurate lighting asset data form the cornerstone of effective lighting management. Our system autonomously identifies and maps several types of lights, ensuring your Geographic Information System (GIS) records are precise and up-to-date. This data can then be used to verify billing, plan broader upgrades, and more. 

Key features within Lighting Audit include:

Fixture Type Classification: Understanding the specific types of fixtures within your lighting infrastructure is essential for maintenance and upgrade planning. Our enhanced AI models can now detect and identify various light fixtures with a high level of accuracy, including:

• Street Lights: Standard roadway illumination.
• Area Lights: Security lights, floodlights, and other broader-coverage fixtures.
• Pendant Lights: Hanging fixtures often used for decorative and functional purposes.
• Post-Top Lights: Includes differentiation between colonial and acorn styles, commonly used in pedestrian areas.
• High-Mast Lights: Tall pole-mounted fixtures for large area illumination.

Light Source Identification: Differentiating between light sources is crucial for energy efficiency initiatives. Our improved LED source classification model distinguishes between LED and non-LED street light fixtures.

NEMA Socket Detection: With the rise of smart city infrastructure, streetlights equipped with NEMA sockets are increasingly valuable. Our beta-stage NEMA Socket Detection model identifies the presence of NEMA sockets on streetlights, enabling utilities and municipalities to better plan for smart lighting solutions.

Lighting Asset Tag Detection + Text Extraction: Similar to our asset tag detector for power distribution, this new model automatically detects and extracts text from lighting asset tags, providing key asset information without the need for manual data entry.

NEMA Label Wattage Text Extraction: Understanding wattage specifications is crucial for optimizing energy usage. This model detects NEMA labels on the undersides of streetlights and extracts wattage information with advanced accuracy.

Lighting Inspection

Beyond asset inventory tasks, our Lighting Inspection capabilities focus on detecting inefficiencies and infrastructure issues to optimize performance and reduce costs.

Key features within Lighting Inspection include:

Day Burner Detection: Streetlights that remain on during the day (known as “day burners”) are a major source of energy waste. This day burner detection feature identifies these inefficiencies, supporting cost savings and sustainability initiatives by ensuring lights operate only when needed.

Pole Lean Detection: Identify leaning or misaligned poles for proactive maintenance and safety improvements. This capability helps utilities detect potential hazards before they become critical issues, ensuring a safer and more resilient lighting infrastructure.

Smarter Lighting, Smarter Cities

By integrating these cutting-edge AI-driven features, Noteworthy AI’s Lighting Intelligence Suite is revolutionizing the way utilities, service providers and municipalities approach lighting management. Whether it’s improving asset visibility, optimizing energy efficiency, or enabling future-ready smart city solutions, our technology ensures that streetlight management is more data-driven, efficient, and cost-effective than ever before.

Ready to transform your lighting audits? Contact us today to learn how Noteworthy AI can help you build a smarter, more sustainable lighting infrastructure.