Urban mining and artificial intelligence: Challenges and opportunities
Abstract
This chapter delves into the crucial role of artificial intelligence (AI) in urban mining, addressing resource demands, environmental concerns, and the need for sustainable resource management. Urban mining focuses on extracting secondary raw materials from human-made sources and emphasizes the value of by-products as resources, aligning with circular economy principles. Machine-learning-based modeling plays a key role in tackling the complexities of urban mining, enabling the development of predictive models for efficient postconsumption product and material management. Urban mining goes beyond traditional landfill mining and encompasses diverse sources, categorizing recoverable resources. The chapter explores these sources and reuse techniques, highlighting the transformative impact of data processing, machine learning, and AI on improving urban mining practices. It not only identifies sources but also emphasizes sustainable reintegration strategies and demonstrates how technology contributes to effective resource management. In summary, this chapter underscores how advanced technologies are positively transforming urban mining, making it more productive and sustainable. However, it also acknowledges the opportunities and challenges that arise with these technological advancements.
Document Type
Book Chapter
Date of Publication
1-1-2025
Publication Title
Artificial Intelligence in Future Mining
Publisher
Elsevier
School
Mineral Recovery Research Centre / School of Engineering
Copyright
subscription content
First Page
229
Last Page
247
Comments
Markazi, S. A., Akbarnezhad, S., Ardestani, N. K., & Razbin, M. (2025). Urban mining and artificial intelligence: Challenges and opportunities. In Artificial Intelligence in Future Mining (pp. 229-24). https://doi.org/10.1016/B978-0-443-28911-8.00005-6