Garbage In, Data Out: 4 Ways AI Can Transform Waste Management

Garbage In, Data Out: 4 Ways AI Can Transform Waste Management

Waste management is one of the foundations of society. Without it, we wouldn’t have functioning cities.

But the amount of garbage that humans produce over time has increased by staggering proportions. According to the World Bank, it will likely continue to do so, increasing 70% by 2050 to 3.4 billion tons.

A recent article in the IEEE Smart Cities newsletter notes that conventional methods of handling garbage may not be able to handle the increase. It calls for increased deployment of artificial intelligence to increase recycling rates and make collection more efficient.

Here’s a look at some of the possibilities:

  • Machine vision for recycling: Separating recyclables from solid waste headed for the landfill is often done by humans. It’s labor intensive, and the cost of labor can exceed the price recycling centers get for materials. It’s particularly hard with different types of plastics.
  • Smart garbage cans and predictive analytics: IoT-enabled public trash cans might be able to send alerts when they’re full. That’s a benefit in itself, especially if it stops people from throwing garbage on the street when there’s no room at the bin. But data from the bins can also be used to create a bigger picture: predicting when trash cans are likely to be full before they are actually full and planning the most efficient pickup routes. The data can also be used to determine the best place for new garbage cans.
  • Route optimization for garbage trucks: Artificial intelligence algorithms can also make garbage collection smarter and greener. AI can map out the best routes for collection trucks, considering how full the bins are, traffic jams and even environmental factors. This might mean less fuel burned and fewer emissions.
  • Predictive maintenance: Trash collection can take a heavy toll on equipment.  To keep trash trucks and smart bins in tip-top shape, AI may be deployed to keep an eye on the condition of equipment and vehicles, predicting when they’ll need a fix. This might mean less downtime and more efficient trash handling.
  • While there are numerous possibilities, improving recycling technology is one of the biggest opportunities in the field.

“The biggest challenge in the recycling process is separating waste for recycling,” said IEEE Senior Member Euclides Chuma. “Although there are automated technological solutions for this separation process, these solutions are expensive. It is necessary to reduce the costs of automatized equipment used in the recycling process. The ability to increase recycling rates  has global impacts.”

Rabindra

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