Artificial Intelligence is unlocking new potential in waste management. Discover how Wasteer’s latest modules provide crucial data to boost the efficiency and profitability of Waste-to-Energy plants.
Key Takeaways
- Artificial Intelligence revolutionises waste management through Wasteer’s new modules for Waste-to-Energy plants.
- The composition analysis and bunker management modules enhance data collection for thermal waste treatment.
- Enfinium and EEW Group are among customers adopting these AI modules across numerous facilities.
- Dynamic pricing models become possible, allowing operators to charge based on actual calorific values of waste deliveries.
- Bunker management improves combustion stability, efficiency, and contributes to compliance with European waste regulations.
The Berlin-based company Wasteer has expanded its solution portfolio with two new modules based on Artificial Intelligence (AI) designed to improve the data basis for thermal waste treatment plants. The new composition analysis and bunker management modules build on wasteer’s existing camera systems and object recognition software. The data collected helps address key industry challenges, from transparency of calorific values in deliveries to operational planning.
This product extension follows a growth in the company’s customer base. The British Waste-to-Energy plant operator Enfinium is expanding object recognition with wasteer to all its plants in UK. For 15 plants of major customer German EEW Group, the new modules are already being rolled out in addition to object recognition. New customers such as AEB Amsterdam and the Norwegian Returkraft have also commissioned the new modules. In total, Wasteer now monitors waste streams of more than 12 million tonnes per year in over 30 plants across ten countries.
Benedict von Spankeren, CEO of wasteer, explained that the better the input is understood, the better the output can be controlled. “Our technology makes it possible to have a live and continuous overview of which waste is arriving where and in what composition, and helps to recycle it in the best possible way,” he stated.
Data Enables Dynamic Pricing Models
The composition analysis provides information on what an individual supplier delivers to the plant. Wasteer summarises the image data from a delivery into an analysis per truck, providing statements on material proportions, calorific values, and relevant emission parameters. This allows for the clear allocation of results using automatic number plate recognition.
With this information, contracts can be qualitatively evaluated and deviations from agreed calorific values can be identified. Instead of charging flat-rate prices, operators can introduce variable, quality-dependent pricing models where the customer pays based on the actual calorific value of their delivery. It also enables active control of plant utilisation, as operators can run their plants more efficiently by specifically selecting different customers and waste qualities.
Bunker Management for Increased Stability
The bunker management module focuses on control within the plant. Its objective is to continuously analyse the bunker content and provide information for optimal mixing. The system creates a surface profile of the bunker and delivers data-based recommendations for crane guidance. The aim is to achieve stable and predictable combustion processes, lower operating material costs, and higher throughput.
EEW-CEO Timo Poppe commented on the use of the technology. “Artificial intelligence and new technologies are central levers for the transformation of our industry,” he said. “Wasteer’s solutions increase the economic efficiency of our plants and make them fit for the future. The insights provide us with a data basis with which we can sharpen our long-term strategy.”
The portfolio expansion responds to the increasing demand for data-based control instruments in the waste management industry. This is driven by new requirements at the European level, such as for CO₂ pricing in the United Kingdom, and national regulations that bring the exact knowledge of the composition and quality of waste streams into focus.
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