HĀLŌ builds AI-enabled video and LiDAR systems that detect wildfire, pavement distress, roadway assets, and traffic and pedestrian conflicts, so agencies can act sooner.
Hālō means to peer, to look closely. Our AI does the same, reading camera and LiDAR data for Hazard, Asset and Lane Observation across Hawaiʻi.
AI early wildfire detection
Computer vision models watch camera feeds from ridgelines and roadside poles for the first signs of smoke and flame, day and night. Each detection is verified before an alert goes out, so dispatchers receive the image, a location estimate and a confidence score, not a false alarm.
AI pavement and roadside asset inventory
Deep learning models trained on camera and LiDAR data find and classify pavement distress and roadside assets while the mapping vehicle drives the network at traffic speed. Every detection is georeferenced, so the inventory loads straight into your GIS or asset management system.
AI traffic and pedestrian safety
AI models detect, classify and track every vehicle, pedestrian and cyclist in roadside LiDAR and video, then flag near misses before they become crashes. LiDAR records shapes, not faces, which suits school zones and neighborhoods.
Multi-sensor AI perception behind all three
Every project fuses RGB video with LiDAR point clouds. Cameras give the AI color and texture to recognize what an object is; LiDAR gives its exact 3D position and size, in daylight or dark. Fusing the two cuts the misses and false alarms that either sensor makes alone.
Most engagements start with a short pilot on one corridor, intersection or ridgeline, so you can judge the AI results before scaling up.
Roadside units or the mapping vehicle capture synchronized video and LiDAR.
AI models find vehicles, people, roadway assets, pavement distress and smoke.
We check AI detections against surveyed ground truth and report accuracy, not just counts.
Detections become maps, tables and alerts in formats your GIS, maintenance and safety teams already use.
Fixed units watch one place continuously. The mapping vehicle covers a whole network in a few days. Both feed the same AI models.
AI asset inventories, pavement condition ratings and safety studies across a network.
AI monitoring of intersections and school zones, with before and after evaluations.
Early AI smoke detection where wildland meets neighborhoods.
Automated watch on line corridors for ignition and vegetation risk.
Tell us about the corridor, intersection or hillside you want to understand. We will reply with a pilot scope, schedule and cost.
Email info@halotechnologies.ai