AI Waste Sorting Automation
Detect, classify, open, and sort mixed waste at line speed.
Byte Motion builds AI-powered waste sorting systems that detect bags, classify mixed waste streams, and guide robotic handling on real conveyors. The result is more consistent sorting, less manual intervention, and better throughput in difficult recycling environments.
Built for unstructured waste flows
Waste sorting is difficult because bag shape, orientation, fill level, and contamination vary constantly. Our systems combine industrial cameras, AI detection, and robot control to keep sorting stable even when inputs are inconsistent.
From detection to action
We connect vision output directly to downstream handling, including bag opening, robotic picking, and line coordination. This reduces manual bottlenecks and keeps material flowing into the next processing stage with better consistency.
Battery detection in waste streams
Batteries are the most dangerous contaminant in mixed waste and a leading cause of fires in sorting plants. At IVAR's waste management facility in Norway, Byte Motion's AI vision system detects batteries of varying shapes, sizes, and colors on the conveyor with over 95% accuracy and guides a robot to remove them — and fire incidents linked to battery contamination dropped to zero within the first months of operation. The same detect-and-remove approach applies to other hazardous or high-value target materials.
What camera does an AI waste sorting system use?
The right AI camera for waste sorting depends on the material and the decision being made. We deploy 2D color cameras for classification, 3D color cameras for bag picking where depth and fill level matter, and high-resolution industrial cameras for small targets such as batteries. Optimus is camera-agnostic, so hardware is chosen per task — and the AI models are trained on images from your actual waste stream, not a generic dataset.
Can a waste sorting robot handle a full municipal stream?
Yes, with the right scope. At a Norwegian municipal facility, a rail-mounted ABB IRB 6700 with a custom multi-bag gripper picks up to four waste bags per cycle, guided by AI classification from 3D color cameras. Halden Municipality uses AI to identify green bio-waste bags among visually similar non-target bags — a distinction manual sorters frequently get wrong under time pressure. Where edge cases resist full automation, our Human Assisted Vision workflow keeps operators in the loop from a screen instead of the sorting line.
Key benefits
- Bag Detection & Opening — Detect sealed bags on the conveyor and support controlled opening workflows before material reaches downstream sorting stages.
- AI Waste Classification — Classify mixed waste items and bags in real time to support more accurate sorting decisions in variable conditions.
- Robot Picking — Send reliable pick positions to robotic handling systems for removing, sorting, or repositioning target material.
- Line Integration — Integrate with conveyors, signals, and plant logic so the waste sorting cell works as part of the full process rather than a standalone demo.
- Battery & Contaminant Detection — Identify batteries and other hazardous contaminants in mixed waste and remove them robotically before they cause fires downstream.