Terminus Group

Analyzes live traffic sensor data from urban road networks to identify congestion patterns and automatically optimize signal timing and routing. Uses edge AI to process data locally, reducing latency for immediate traffic management decisions.

Collects and analyzes energy usage data from building systems including HVAC, lighting, and power distribution. Provides AI-driven recommendations to reduce energy consumption and operational costs across municipal or commercial building portfolios.

Aggregates and analyzes environmental data from multiple sources including weather stations, pollution sensors, and climate models to provide comprehensive urban environmental insights. Integrates with city planning and sustainability initiatives.

Manages street lighting systems using sensors and AI to optimize lighting levels based on traffic, weather, and time of day. Reduces energy consumption while maintaining safety and visibility.

Connects and manages diverse IoT devices and sensors from multiple manufacturers across urban infrastructure without requiring proprietary hardware. Provides unified data collection, device provisioning, and lifecycle management across heterogeneous ecosystems.

Runs machine learning models and AI inference directly on edge computing nodes distributed across the city, processing sensor data locally without sending all data to cloud. Reduces latency, bandwidth costs, and privacy concerns compared to cloud-only approaches.

Monitors urban areas using computer vision and sensor analytics to detect safety incidents like accidents, fires, or unauthorized activities. Provides real-time alerts to emergency services and law enforcement with location and incident classification.

Collects and analyzes data from distributed air quality sensors throughout the city to monitor pollution levels, identify pollution sources, and provide public health alerts. Integrates with weather data to predict air quality trends.

Monitors parking space occupancy across the city using sensors and computer vision, provides real-time availability information to drivers, and predicts parking availability to optimize parking search behavior and reduce congestion.

Monitors water distribution systems, sewage networks, and utility infrastructure using distributed sensors to detect leaks, predict failures, and optimize maintenance schedules. Provides early warning for infrastructure issues before they become critical.

Uses computer vision and sensor data to monitor crowd density in public spaces, parks, and transportation hubs. Provides real-time alerts for overcrowding and helps optimize public space usage and safety.

Analyzes sensor data from urban infrastructure assets to predict failures, optimize maintenance schedules, and extend asset lifespan. Uses machine learning to identify patterns that precede equipment failures.