By Kevin Ebi.
Our efforts to separate pure trash from recyclables, and different types of recyclables from each other, are cutting down on the amount of waste in landfills. But they’re also resulting in waste.
Each bin requires a different truck, and trucks are typically sent to empty the bins on a set schedule that doesn’t usually account for whether the bins are full or not.
Council Associate Partner Enevo hopes to eliminate that wasted effort and fuel by attaching sensors to the receptacles, allowing efficient collection routes to be developed based on need. Based on its experiences so far, it estimates the sensors can help cut collection costs by 40 to 50%.
The company was recently featured in Forbes, bringing even more attention to its efforts to transform the $3 trillion waste management industry. Enevo, which is based in Finland, recently won $8 million international funding to expand its service. It recentlylanded a smart waste collection deal in the Czech Republic. It’s already in use in dozens of cities in Europe and North America.
Next up: using data to spot trends
The profile also discusses the future of Enevo – a future that involves going well beyond knowing which bins are full. It involves making use of all the data it collects to spot trends and predict what will need to be collected and when, before that trash is even generated.
Right now the sensors collect data about how full the bin is and what its internal temperature is. The sensors allow each bin or trash can to connect to the Internet.
Some even post to Twitter. Container 100202100013073 in Korsholm, Finland recently tweetedthat it is 67% full. Container 100202100014041 in Best, Nedeland, tweeted that it’s getting warm inside. Container 100202100014656 in Cleveland tweeted that it won’t need to be emptied again this year.
On Twitter, that data seems almost cute, but Enevo tells Forbes it’s all valuable. The containers that get hot inside fast should probably be picked up first. And the usage data gives them an idea of what’s at each site.
Carried one step further, they could even predict the value of the recyclables at any given location, allowing waste haulers to get even smarter about collection.