With a growing population and increasing urbanization, waste and recycling operators face a tough challenge. Keeping up with current levels of waste production, while also meeting environmental legislation, can feel insurmountable – particularly when working with legacy systems and outdated technology.
Without the right tools, waste operations are hampered by inflexible logistics, inefficient processes and rising costs. Meanwhile current legislation driving increased separation at source and digital waste tracking can present problems.
Perhaps it’s no surprise then that today’s innovative technologies including artificial intelligence and the Internet of Things have the potential to transform the waste industry, simplifying regulatory compliance and streamlining collections through AI-powered waste management.
the role of IoT in waste collection
The Internet of Things (IoT) can be used to enhance various aspects of waste management. When installed in bins, vehicles, or recycling facilities IoT-enabled sensors provide a network of devices capable of collecting and transmitting data in real-time. This information offers insights that can be used to improve collections, increase safety and drastically boost efficiency.
One of the most exciting applications for these IoT sensors is in real-time waste monitoring. When installed in street litter bins, for example, waste bin fill-level sensors can provide data on how often a bin is used, when it is full, and when it has been emptied – all of which can be used to trigger collections. Unsurprisingly, the number of waste collection points fitted with smart waste sensor technology is rising rapidly with 1.25 million smart bins worldwide in 2023.
Smart waste management IoT doesn’t end with waste bins on the street; there are a range of IoT-enabled solutions in operation. For instance, on collection trucks, IoT-enabled GPS sensors can be used to track the route of the truck in real-time, while sensors on the lift apparatus can measure the weight of each container load.
Meanwhile, in underground waste collection systems, IoT-equipped ultrasonic sensors can measure the volume of waste in the container. Access control systems also measure the number of valve openings to record how many loads have been added and temperature sensors within the container monitor heat levels to protect against fire.
In each case, the Internet of Things enables the exchange of information that can be used to improve collections efficiency and streamline waste handling.
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AI and predictive analytics for smarter waste collection
Almost all aspects of waste management can be enhanced with IoT data, but when paired with artificial intelligence (AI), IoT becomes even more transformational.
AI algorithms can analyze IoT-generated data not only to predict waste generation patterns, but also to adjust collection schedules, enabling more accurate and proactive scheduling decisions. When combined with dynamic routing, AI also has the power to reduce unnecessary mileage, cut fuel consumption, and minimize CO2 emissions.
If we take our previous example of IoT-enabled street waste bins, for instance, analyzing real-time data on waste levels not only helps to spot trends and optimize collection schedules but also helps to anticipate demand. By combining this information with real-time data on traffic conditions and GPS tracking of refuse trucks, routes can be adjusted dynamically based on current conditions and demand. If a particular area experiences higher-than-expected waste generation, the system can automatically re-route trucks to prioritize those areas and minimize service disruption.
In fact, AMCS has even been involved in implementing IoT and AI technology to power the most advanced self-driving waste trucks. These autonomous vehicles use AI to automatically collect waste while also continuously recording data for pay-by-weight services with all data managed seamlessly by the AMCS vehicle data hub.
AI for intelligent waste sorting
Another notable AI application is in waste sorting operations. During the collections process, for example, AI-enabled cameras can be used to identify contamination so that customers can be educated and/or penalized regarding their recycling habits.
At the Material Recovery Facility (MRF), AI image processing can be used in conjunction with robotic sorters to improve precision and output quality. Here AI technologies can replace time-consuming and error-prone manual sorting with solutions utilizing AI-powered image recognition to identify different waste materials. This helps to facilitate the efficient segregation of recyclables, organic waste, and non-recyclables, ultimately reducing the amount of waste that reaches landfill.
With AI and IoT technologies in place, you are equipped to manage unpredictable waste streams, including unknown quantities and qualities of material. Not only does this make waste collection and sorting simpler and more cost-effective, it also makes it possible to document, analyze, and evaluate waste streams – right down to the traceability of individual batches – something which undoubtedly supports the shift in European legislation towards a circular, more sustainable economy.
how AI supports circular waste legislation
Recycling legislation provides a framework to reduce waste and promote a circular economy. In the EU, the European Green Deal provides an overarching structure to guide this transition, encompassing a package of initiatives aimed at ensuring that materials are reused, recycled, or composted where possible. There are also strict standards for how to dispose of items responsibly when they can no longer be used, which are set out in the Waste Framework Directive.
Inevitably, this means waste management is becoming more complex, not least because operators must also follow region-specific laws that set recycling targets or specify enhanced waste sorting as part of Extended Producer Responsibility (EPR) schemes.
In France, for example, the Anti Waste and Circular Economy Law (AGEC) is gradually expanding sorting at source, supported by the TrackDéchets digital platform, which is designed to dematerialize tracking slips.
In Germany, the Kreislaufwirtschaftsgesetz (KrWG) enshrines the concept of producer responsibility resulting in disposal systems based on the type and amount of waste produced.
Meanwhile in the UK, a mandatory Digital Waste Tracking scheme comes into effect in 2026 designed to tackle waste crime and ensure that resources are being properly recovered and fed back into the economy.
To manage such schemes effectively, waste operators need to record waste shipments and track the flow of resources in granular detail as well as sorting waste more accurately. If your business still relies on paper-based processes for waste tracking, it will be impossible to meet the comprehensive waste tracking and digital compliance standards required.
Fortunately, advances in IoT and AI technology are stepping up to simplify digital waste tracking compliance, providing data-driven insights that not only improve the quality of secondary raw materials and support regulatory requirements, but also enable you to harness the significant growth potential of the circular economy.
smart waste management for improved sustainability
Clearly, the combination of IoT sensors, data analytics, and artificial intelligence has much to offer in the development of sustainable waste management solutions.
- AI for landfill reduction uses machine learning to enhance waste sorting.
- IoT-enabled waste collection utilizes sensors to track the fill level of waste bins and determine collection requirements.
- Predictive modelling helps optimize waste truck routes and simplify logistics.
- Telematics data and AI analysis can even be used to improve truck maintenance, reducing disruption from equipment failure and extending asset life.
The list of potential applications goes on but the benefits all point in one direction: increased sustainability. For waste and recycling operators, this results in several advantages, simplifying compliance with legislation that is designed to boost circularity, but also offering exciting opportunities to boost profitability.
AI-driven waste sorting, for example, improves recyclate quality and increases revenue potential. Dynamic route scheduling helps reduce waste collection emissions, ensuring a reduced carbon footprint via optimized logistics, but it also results in reduced fuel spend and decreases costs by minimizing the number of trucks needed for waste collection. In each case, improved efficiency has both environmental and operational benefits.
In conclusion, as we look to a future where waste generation is constantly increasing, environmental sustainability and the sustainability of your business are inextricably linked. Accelerating success depends on embracing new technologies and focusing on smart waste management solutions that facilitate both circularity and competitive advantage.
Want to explore smart waste solutions?
Smart sensors for waste bins, IoT-enabled waste collections, and AI-powered waste management are all game-changing technologies. They can supercharge how you collect, move and manage waste resources, paving the way for a business that is smarter, more agile, and ultimately more sustainable, than ever before.
If you would like support to implement these innovative technologies or advice on embedding real-time sustainability tools into your everyday operations, AMCS is available to help. Our platform integrates IoT data, AI analytics, and intelligent automation for real-time decision-making and streamlined operations.
Get in touch with us today to discover smarter ways to manage waste.