How New-Age Technologies are Changing the Waste Management Landscape

A slew of digital technologies is helping shift several economies towards an alternative and more circular model of consumption – one that focusses on realising a future of zero waste, by repurposing, repairing and recycling existing resources and goods in innovative ways.

Robotics, the Internet of Things (IoT), cloud computing, Artificial Intelligence (AI), and data analytics are among the technologies that have been adopted by companies operating in this emerging niche. These include companies such as Winnow Solutions1, a UK-based food waste solution provider that deploys AI to weigh food waste in industrial kitchens; ECube labs2, a US-headquartered South Korean waste treatment firm whose trash compactor CleanCUBE3 can carry up to eight times more waste than non-compacting bins, lowering collection frequency by up to 80%; and StartRocket4 which intends to use space-grade polymeric foam to remove space trash.

We have identified a few strategic investment hotspots that are expected to disrupt the waste management Industry in the future.

  • Robotics

    Robots have the potential to be used extensively for waste processing and recycling. Recycling robots are quick, precise and capable of processing a large amount of garbage. Furthermore, they can work around the clock with the same level of accuracy. Many of these robots find their application on conveyor belts, operating as synchronised robotic arms that utilise computer vision, machine learning and AI to sort and collect recyclable items from moving conveyor belts. The robotic arms are equipped with pinchers that grab and hurl materials into chutes after analysing their usability by using real-time data gathered via metal sensors, 3D laser cameras and spectroscopic cameras.

    Use Cases: Several companies such as ZenRobotics5, a Finland-based leading supplier of intelligent sorting robots for the waste industry, AMP Robotics6, a US-based technology firm that uses AI-guided robots to transform recycling, and Machinex7, a Canada-based provider of engineering, design and manufacture of custom-built scrap-handling systems, are active in the space and have seen some success with increasing revenue and venture capital investments.

    Denver-based AMP Robotics has installed its AI-guided robotics systems in the UK and Ireland with ReyCo8, a recycling and waste management business in Northern Ireland. AMP claims its sorting technology can pick more than 80 items per minute, twice the pace of a human. Its proprietary technology applies computer vision and deep learning to guide high-speed robotic systems to precisely identify, differentiate and recover recyclables found in the waste stream by colour, size, shape, opacity, storing data about each item it perceives.

  • AI and Neural Networks

    The use of AI in waste management goes beyond mere intelligent garbage cans. Some waste management firms are using IoT sensors to keep track of how full garbage cans are across the city. Municipalities then use this information to optimise garbage collection routes, schedules and frequencies. This helps improve the pace at which waste bins are emptied, reducing labour costs and gasoline usage. IoT sensors, on the other hand, can be used to identify different sorts of garbage.

    Use cases: UK-based Recycleye9 has developed the world’s largest visual AI database of waste goods and low-cost robotics tech. The firm recently raised a GBP 3.5 million investment from Promus Ventures.

  • IoT

    The automated route optimisation of garbage collection vehicles is perhaps the most common IoT application in waste management operations. To collect garbage, these vehicles usually follow a certain path every day. Drivers in sanitation agencies that haven’t yet embraced IoT don’t always know how full a garbage container is until they come across it and that can cost time, fuel and money. Installing sensors in each bin and collecting cloud-based data can facilitate a better garbage management process.

    Use Cases: Amsterdam, one of Europe’s smartest cities, has installed garbage pickup vehicles with a weighing gear that instantly understands how much a container weighs and estimates fill levels with 80-90% accuracy based on prior data. The city has also placed 12,500 sensors in trash cans and tested them with plastic debris. Amsterdam’s goal is to save EUR 3 million in yearly garbage collection expenses by growing the IoT system from a pilot project to city-wide implementation.

    In another example, Poland-based Bin.e10, has developed an IoT-based smart waste bin that automatically sorts and compresses recyclables once they are thrown into the bin.

  • Cloud computing

    Although the concept of sensor-based trash bins that can alert users to waste levels is not new, even the most advanced autonomous waste management systems rely heavily on Cloud computing to create a robust and effective system.

    Use Cases: Sanitation agencies in San Francisco can collect real-time bin data such as weight, volume, expenses and truck number and transmit it back, allowing billing and invoicing activities to be automated even further.

  • Data Analytics

    Closely connected to cloud is the application of big data analytics on waste management, in addition to combined geographic and socio-economic data to better understand waste distribution. Big data can potentially help create, drive and implement cleanliness-related surveys that can assist in identifying the correct location of bins on the streets for more efficient use and streamlining waste collection.

    Use Cases: Solar-powered garbage bins with sensors and compactors have been installed in New York City and San Francisco, where collectors are informed to empty the bins when a particular filling level is reached. In the UK, the Greater Manchester Waste Disposal Authority (GMWDA)11 uses big data to increase waste management efficiency and reduce manufacturing waste, especially the one that comes from packaging materials.

    To learn more about opportunities in the waste management space, download our report Circular Economy Part I: Investment Imperatives in Waste Management and Environment Facilities and Waste Management. To read the report, click here.

Subhjeet Vimal
Associate Specialist

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