Seeing Waste Differently: How AI Is Entering Solid Waste and Recycling
Artificial intelligence is getting a lot of attention, mostly in industries far removed from solid waste. But the truth is that AI is already shaping parts of our work. From contamination detection to equipment monitoring to documentation that holds up under regulatory review, these tools are beginning to fill the gaps where manual processes fall short. It affects our industry more quietly, but more significantly, than most realize.
Where AI Is Showing Up Today
1. Contamination Detection in MRFs
Many materials recovery facilities (MRFs) are using camera-based systems to flag contamination in mixed recyclables. These tools can identify plastic types, metals, organics, film, and other problem items at high speed. Operators still make the decisions, but they’re reacting to clearer signals.
2. Sorting Assistance
Some facilities are testing AI-supported sorters that help identify items on a conveyor belt. These systems don’t sort on their own. They assist trained staff by pinpointing materials that might otherwise be missed at higher throughputs.
3. Load Screening for Prohibited Materials
AI-enabled cameras can capture images of incoming loads and flag items that don’t belong, like batteries, white goods, oversize materials, and other hazards. These tools help operators focus their attention where it’s needed most.
4. Equipment Health and Predictive Maintenance
Machine-learning models tied to SCADA data can flag unusual pump behavior, blower performance shifts, or rising vibration patterns. For operators, this means earlier warnings before equipment becomes a downtime problem.
5. Operations and Data Integration
Some teams are using AI to pull patterns from large volumes of operational data — rainfall, tank levels, pumping cycles, temperatures, and flow changes. The value here isn’t automation. It’s better visibility into what’s normal and what’s not.
Why It Matters for Landfills and Recycling Facilities
Our industry is dealing with rising contamination rates, more complex materials, and tighter performance expectations. AI tools help fill gaps where manual processes struggle by giving them clearer, faster information. For many operators, there are many ways it can offer value:
• high-volume tasks
• repetitive visual checks
• early warning signals
• documentation for compliance
• support when staffing is tight
One thing is certain: even with all the benefits of AI, technology cannot replace the judgment, experience, or instincts of the people who do this work every day. At ACC, we believe expertise is earned over years — walking sites, solving problems, learning how systems behave in real weather and real conditions. AI can support that work, but it will never be a substitute for the crews who keep facilities running safely and the leaders who make decisions based on what they see and know.
Tools change. The work keeps moving. But the people who carry it out will always be the most important part of the equation.
At ACC, we look at AI the same way we look at any new tool. If it helps operators work safer, make better decisions, or avoid surprises, it’s worth paying attention to. If it adds complexity without value, it’s not. The work keeps changing, but the principles don’t — people and performance still matter most.