Applications of Artificial Intelligence for Sustainable Waste Management

Dear Colleagues,

Artificial Intelligence (AI) is well-established as a transformative and essential science and technology, benefiting all sectors of industry and society. It is a consolidated paradigm for supporting data-driven sustainability and achieving a circular economy. AI methods and techniques are transforming waste management, shifting from traditional and reactive processes to a smart and proactive strategy.

The integration of machine learning, intelligent optimization, computer vision, internet of things, robotics and other AI techniques provides the accuracy and scalability required to manage resources sustainably. Annual waste generation is expected to surge by 70% by 2050, reaching 3.4 billion tons of global production, and the integration of advanced technologies with AI is an operational requirement to prevent a global waste crisis.

Some of the clearest applications of AI include the smart separation of waste, the intelligent optimization of logistics collection, the sustainable design of products and materials, organic waste prevention and revaluation, and data-driven waste management. Nowadays, robots can perform the precise identification of complex waste materials and their very efficient separation. AI-based systems control networks of Internet-of-Things sensors to provide online monitoring of bins and truck container fill levels. The optimized and dynamic updating of routes revolutionizes the first-mile waste collection, reducing fuel consumption and carbon emissions, lowering traffic congestion, and cutting operational costs. Food waste prevention is going beyond post-consumer management, a terrain where AI plays a vital role in prevention. In the hospitality and retail sectors, AI-driven tools use cameras to track what food is being discarded, allowing chefs and managers to adjust inventory and portion sizes. AI tools are also essential to manage the use of organic waste to obtain renewable energy or compost, enabling the valorization of sources.

Overall, we aim to improve the development and application of AI tools to achieve better and more sustainable management of the waste produced by human activities. The scope of this Issue will include theoretical proposals; analysis and applications of IoT-enabled real-time monitoring of waste generation and collection; machine learning models for waste prediction and route optimization; AI applications for food waste prevention and organic waste valorization; and data-driven approaches for measuring and quantifying the sustainability of waste management processes.

This publication directly contributes to the sustainability mission of the journal by addressing how AI and IoT serve as tools for measuring and monitoring sustainability in waste management. We also welcome works that examine the socio-economic impact of AI adoption in waste management. Specifically, this Issue contributes to Sustainable Development Goals Target 12.3 (halving food waste by 2030), Target 12.4 (environmentally sound management of chemicals and waste), and Target 12.5 (substantially reducing waste generation through prevention, reduction, recycling, and reuse).

Prof. Dr. José Andrés Moreno-Pérez
Dr. Mustapha Maarouf Bassaidi
Dr. Julio Brito-Santana
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• waste management
• waste collection
• waste valorization
• circular economy
• machine learning
• intelligent optimization
• internet of things
• data science
• artificial intelligence