AI Waste Sorting Systems
Byte Motion delivers AI waste sorting systems for municipal and industrial waste operations that need better material separation, safer handling, and stronger performance across mixed, visually inconsistent waste streams.
Waste sorting demands automation that can identify bags, contaminants, and hazardous items under messy real-world conditions. Byte Motion combines AI vision, robotics, and human-assisted workflows to improve sorting quality while reducing manual exposure.
Challenges we solve
- Mixed waste streams vary continuously in color, shape, fill level, contamination, and placement.
- Manual bag sorting is repetitive, hazardous, and difficult to scale consistently across shifts.
- Waste operators need dashboards and operational data, not just robot picks in isolation.
What we automate
- AI classification of waste bags and target materials
- Robotic picking for mixed-waste sorting lines
- Battery detection and hazardous contaminant removal
- Real-time dashboards and human-assisted intervention workflows
Proven results
- 95%+ — Battery detection accuracy achieved: Mixed-waste battery sorting at IVAR reached high detection accuracy in production conditions.
- 4 bags — Picked per cycle in municipal waste sorting: The ABB IRB 6700 waste workflow handles multiple bags per cycle to increase throughput.
- Real time — Dashboard visibility for operators: Supervisors can monitor pick counts, waste types, and operational trends as sorting happens.
What does Byte Motion automate in waste sorting?
Battery removal, waste bag classification, bio-waste sorting, robotic bag handling, and AI-assisted decision support for mixed municipal or industrial waste flows.
Why use AI for waste sorting instead of fixed rules?
Waste environments are highly variable. AI handles visual inconsistency far better than rigid rule sets, especially when item orientation, contamination, and bag appearance change continuously.
Can operators still stay involved in the sorting process?
Yes. Byte Motion supports Human Assisted Vision workflows where operators retain visibility and intervention capability for edge cases while AI handles routine sorting decisions.