One of the most exciting challenges our Pello Technology team at RTS has been working through is what comes after visibility. Pello has given customers a better understanding of what is happening inside their waste and recycling containers—from fullness and service activity to contamination and material conditions.

But as our team worked with that data, we kept coming back to a larger question:

Once you know what is happening at the container, how do you turn that intelligence into action?

That question is important because much of waste collection still operates according to fixed schedules. A location may receive service several times a week regardless of how much material is actually being generated. One container may be ready for service earlier than expected while another may have significant capacity remaining.

For both customers and haulers, that disconnect between scheduled service and actual need creates an opportunity for improvement. At RTS, we believe the next generation of waste intelligence is about closing that gap.

Moving Beyond Monitoring

The first phase of smart waste technology was largely about answering questions:

  • How full is the container?
  • Was it serviced?
  • Is there contamination?
  • What is happening across a network of locations?

Those answers matter. But our team increasingly thinks about the next question:

What should happen because of that information?

That shift—from monitoring toward decision support—is where the technology becomes much more operational. Waste generation is dynamic. It changes based on the location, season, day of the week, customer activity and countless other real-world factors. The more accurately we can understand those conditions, the more intelligently operations teams can respond. That creates potential value across the waste ecosystem.

Customers can gain better insight into whether their service levels align with actual needs. Haulers can make more informed decisions about how they deploy trucks, drivers and capacity. Sustainability teams can better understand what is happening across their portfolios. And the industry as a whole can begin moving away from a model built entirely around fixed assumptions.

Building Technology for the Real World

One of the things I’ve enjoyed most about working on this challenge with the RTS team is that the answer cannot simply be a clever algorithm. Waste is physical. The technology has to account for the realities of containers, sites, drivers, service requirements and changing operating conditions. That means our job is not simply to create more data. It is to make the data useful to the people who actually run these operations.

That distinction is important. The best technology should help experienced people make faster, better-informed decisions. It should identify patterns that would be difficult to see across hundreds or thousands of containers and help teams focus their attention where it matters most.

Human judgment remains essential. AI makes that judgment more informed.

Where Waste Technology Goes Next

To me, this is one of the most exciting things about what we are building at RTS. We are moving beyond the idea that waste technology is simply a sensor attached to a container or a dashboard showing what happened yesterday. The next phase is about creating a more intelligent connection between what is happening in the physical world and what operations teams do next. That is a much bigger opportunity.

It can help customers better align service with actual demand. It can give haulers better operational intelligence. And it can help the industry make decisions using information that, until relatively recently, simply wasn’t available. Our team is still learning every day as we work through these challenges.

But one thing has become increasingly clear to me: The future of waste intelligence isn’t just about seeing more.

It’s about knowing what to do next.