How Is AI Helping Businesses Reduce Waste?

AI and Waste Management: A Great Forest summary

Everyone is talking about the potential of AI or Artificial Intelligence to revolutionize every industry, including waste management. But what does AI and waste management really mean for businesses? While AI technology is still evolving, we are already seeing its impact.

  • At some landfills in China, robots capable of searching for and removing compostable material from dumpsites are helping to reduce greenhouse gas (GHG) emissions and waste.
  • At MRFs (Materials Recovery Facilities) across the U.S., smart sorting systems are popping up using lasers to identify and separate materials moving along conveyor belts.
  • In some public areas, for example at an airport in Pennsylvania, smart trash and recycling bins are taking the  guesswork out of recycling–the bin determines if an item placed in it is recyclable and separates it from the trash stream.

In all these instances, the ability of AI to increase the speed and efficiency of waste sorting and processing is undeniable. Technology can help us improve recycling systems, reduce the problem of recycling contamination, and divert more material away from landfills.

But at the big picture level, it will take time for the technology to be perfected as machines learn, as robots are designed to become more adept at separating materials (say, plastic wrap from a plastic container), and as we wait to see which technology becomes widely adopted, and what the costs are.

In the meantime, what can individual businesses do to tap into the power of AI to reduce waste right now?  And what are some of the concerns to look out for regarding AI and waste management? Let’s take a look.

AI and Waste Management: Current Waste Monitoring Applications

With waste costs rising, more businesses are looking into AI-powered smart sensors or waste meters to monitor their waste.

While the assumption is that dumpsters are picked up when they are 100% full, the reality is often far from it. Most businesses are paying to haul a lot of air. It has been reported that the average front load dumpster is 53% full when collected. What’s more, 13% of scheduled pickups do not happen. AI can keep an eye on dumpsters and collect data to help businesses avoid these issues.

Currently, several types of sensors or meters are available that work in a variety of ways: some use smart cameras or ultrasound to offer a view inside dumpsters; some use 3D optical lasers to detect and determine fullness levels by providing a depth map; and others work by recording changes in  temperature, the weight of a dumpster, or using a combination of technology.

Waste sensors or meters can offer real time visuals and information, or they can send data once a day, several times a day, or when they are triggered by the dumpster being moved, such as when a hauler makes a pickup. AI-help monitoring waste comes with these benefits:

  • Right Sizing and Service Optimization­
    Businesses can use the fullness data provided by the sensors or meters to right-size service, such as decreasing bin size and pickup frequency to match waste generation. Optimizing service leads to more efficient and cost-effective waste removal.­
  • Analysis and Reporting
    Waste metrics have become vital as companies develop ambitious sustainability goals and report their performance to agencies like the CDP and GRESB. Verifiable waste data from waste sensors or meters can help in reporting.
  • Hauler Accountability, Fewer Service Issues
    Waste sensors or meters can ensure more regular service by tracking and holding haulers accountable for missed service. With sensors triggered by the dumpster being moved, businesses receive data such as the number of pickups missed each month, which can reveal patterns of service irregularities. With this data, businesses can then work with the hauler to improve performance, or look for and negotiate new service.
  • Track Assets, Prevent Theft and Improper Dumping
    The sensors or meters can help prevent theft by tracking dumpsters, and alerting businesses to unauthorized use of their dumpsters.

Challenges and Considerations

  • Installation
    These sensors and meters need to be affixed to the dumpsters, usually by drilling. If you do not own the dumpsters, you will need the hauler’s permission to install the sensors/meters. Some have concerns about the installation process damaging the dumpsters and may refuse.
  • Costs
    There are often fees associated with installation. In addition, there are subscription and service fees. Contracts generally are for three years. For a company that has a large number of dumpsters, costs can add up quickly. However, the data they offer may be valuable enough to offset some of these costs through service optimization savings.
  • Data Verification and Analysis for Actionable Insights
    All data requires verification and proper analysis. Great Forest analyzes sensor or waste meter data to understand contamination levels (such as if a large amount of recyclable materials is being discarded in the trash, or if there is trash being disposed of in recycling bins) and to spot unusual patterns, irregularities, or sensor mistakes (somethings sensors have blind spots or may malfunction). The data is also used to forecast future waste patterns and predict peak periods in order to adjust waste strategy accordingly. The key is having actionable insights. When paired with expert analysis, data from AI-powered sensors and waste meters can help you reach your sustainability goals faster.
  • AI Data + Waste Audits
    At the moment, while some of these AI-powered devices can detect day-to-day recycling contamination (for example, identifying plastic in a cardboard recycling bin), a hands-on waste audit is still the best method to obtain more accurate data on contamination levels and what is going into all your waste streams. Working together, waste audits and AI-powered data can give a business supercharged insights on waste generation and diversion.

Future Outlook: AI and Waste Management

AI has a lot of potential but it is not a magic bullet that will solve all our waste challenges. In fact, at times, it may even hinder. There is the danger of AI further encouraging the throw-away mentality. The easier it gets to just discard something and assume it gets recycled because of AI, the more likely that products such as single-use items will continue to be widely used.

With the rise of AI, we must work even harder to shift the focus to reducing the amount of waste generated, to move towards Zero Waste. In addition to monitoring waste, AI can also be used, more importantly, to prevent waste in the first place. For example, some food service businesses and grocery chains are using AI to track and predict consumer habits and preferences, and to determine inventory and demand. This helps them understand what to order and when, so they can reduce waste. This has powerful implications in supply chain management and procurement.

Remember, AI alone cannot figure out what matters the most for your business. But with proper verification and analysis, the data can be used by waste experts to set priorities and adjust strategies. Waste and recycling education and training will continue to be important as you incorporate AI into waste management efforts.

Case Study: 175 AI-powered Sensors Superpower Waste Reduction

How can AI help in waste management? Here is an example. Great Forest installed 175 smart wireless waste sensors across 14 residential communities. Using the data, Great Forest waste experts were able to right-sized equipment and service levels to achieve a 14 percent decrease in waste costs, and improve service. Read the case study here

Learn More

Case Study: 175 Waste Sensors Help Residential Properties Reduce Costs and Improve Service

 

 

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