In a circular economy, countless small decisions drive the system forward. Whether it’s a returned laptop, a worn pump, or a retired battery pack, each item must find its next destination, whether that be a resale shelf, a repair bench, a remanufacturing line, a parts bin, or a recycler. These decisions are based on the physical condition of each specific item, a factor that requires human or camera-based assessment before any action can be taken.
Linear manufacturing systems were designed for identical products moving in a single direction. Circular technology disrupts this flow by introducing variability. For example, a single phone model may return in various conditions, from cracked and damaged to almost new, all in the same shipment. This variability challenges traditional fixed rules and calls for the implementation of agentic vision, a form of artificial intelligence that combines visual perception with reasoning and action.
This article delves into the value created by agentic vision in circular technology, the decisions it should be responsible for, and where traditional computer vision or human intervention remains essential. As circular tech solutions transition from pilot projects to daily operations, addressing these questions becomes increasingly crucial.
Visual Decision Making in Circular Tech
The magnitude of the material challenge in the circular economy is well-documented. According to the Global E-waste Monitor 2024, published by UNITAR and the International Telecommunication Union, a record 62 million tonnes of e-waste was generated in 2022, with only 22.3% formally collected and recycled.
Limited repair options, short product life cycles, and design flaws contribute to the widening gap in e-waste management. These challenges not only pose policy problems but also impact the efficiency of facilities receiving used products, where the inability to assess items quickly and consistently often leads to downgrading products to scrap unnecessarily, increasing resource consumption and environmental impact.
Visual assessment plays a critical role in the evaluation of items at various stages, from checking screens for scratches to inspecting cores for wear. Each step involves converting visual observations into routing decisions, a process where many circular operations face challenges related to time, consistency, and recoverable value.
Advantages of Agentic Vision in Circular Tech
Traditional computer vision excels in narrow, repeatable checks but falls short when it comes to decision-making. Agentic vision bridges this gap by adding a reasoning layer to the perception process. By combining evidence from multiple images, checking against product-specific rules, querying relevant systems for context, proposing routes based on reasoning, and seeking human review when needed, agentic vision enhances decision-making in circular operations.
Key Decision Points for Agentic Vision in Circular Tech
While circular economy operations vary by product category, five common decision points emerge in electronics refurbishment, industrial remanufacturing, and battery recovery:
1. Intake and Identification
Reverse logistics begin with accurately identifying returned items to prevent downstream errors.
2. Cosmetic and Functional Grading
Consistent grading is crucial for setting resale value and cash flow in refurbishment businesses.
3. Route Selection
Choosing the right route for each item based on its condition and business needs is essential for resource optimization.
4. Disassembly Guidance
Agentic vision aids in planning disassembly tasks, combining high-level decisions with human intervention for precise actions.
5. Hazard Screening
Identifying hazardous components like damaged batteries in real-time enhances safety and environmental protection in recycling facilities.
Implementation and Scaling of Agentic Vision
Agentic vision systems should autonomously handle routine cases, involve humans in medium-confidence decisions, and escalate high-risk situations to supervisors. Local processing with edge computing is recommended for efficient and GDPR-compliant operations.
Getting Started with Agentic Vision in Circular Operations
Start by focusing on one decision with measurable costs, document current processes, collect real-world data, and gradually integrate agentic vision alongside existing workflows. Continuous evaluation and refinement are key to successful implementation.
For more insights and guidance on implementing agentic vision in circular operations, explore Viso’s computer vision solutions and schedule a demo with our team.
