Trailslight provides an adaptive street lighting system that uses sound analysis and on-device AI to classify traffic, weather, and noise in real time, automatically adjusting lamp brightness to cut energy use by 40–60%. The solution includes edge devices, a LoRa-based gateway, and a centralized management platform, all designed to be GDPR-compliant by processing audio locally without recording it.
Funding
Funding not disclosed
Founders
Product
Problem
Public street lighting is often operated at fixed brightness levels regardless of actual road usage, leading to significant energy waste and unnecessary light pollution. Municipalities lack cost-effective, privacy-compliant tools to dynamically adjust lighting based on real-time traffic and environmental conditions, especially across large and dispersed urban infrastructures.
Solution
Trailslight offers an adaptive lighting system that equips each streetlamp with an intelligent edge device capable of analyzing ambient sounds to classify vehicle types, traffic volume, weather events, and noise levels. The system automatically adjusts light intensity in real time according to the UNI 11248 standard, ensuring safety while reducing energy consumption by 40–60%. Data is processed locally on the lamp controller via neural networks, so no audio is ever recorded or transmitted, ensuring full GDPR compliance. A LoRa 868 MHz radio network connects the devices to a centralized cloud platform, enabling remote supervision, data analytics, and integration with other smart city services.
Target Audience
Primary customers are municipal governments, public lighting utilities, and smart city operators seeking to reduce energy costs and improve urban safety through adaptive infrastructure.
Features
- On-device AI sound classification for vehicle detection (motorcycles, light and heavy vehicles), traffic quantification, and weather event recognition (rain, strong wind)
- Real-time adaptive dimming of streetlights based on traffic presence and density, compliant with UNI 11248 standards
- Acoustic environmental monitoring with decibel-level measurement for noise pollution mapping and heatmap generation
- Edge processing architecture that classifies sound locally without recording, ensuring GDPR compliance by design
- LoRa 868 MHz wireless mesh connectivity for secure, scalable communication between lamp controllers and central systems
- Centralized Trailscity Platform for data aggregation, real-time control, and interoperability with existing smart city infrastructure