## 1 Introduction  
The 21 st century has brought unprecedented challenges to global industries, including rapid societal transformations driven by technological innovation, social changes, and evolving business models. However, this progress presents a critical paradox: the growing scarcity and depletion of natural resources. Among the most pressing issues is solid waste management, which intersects with the environmental, social, and economic dimensions on a global scale. While traditional supply chains are well studied and widely optimized, reverse supply chains for solid waste (RSCSW) remain fragmented and underdeveloped in governance. This condition results in significant gaps in waste recovery and resource reintegration, along with numerous logistical bottlenecks and trade-offs. Several industries, such as automotive, petroleum, agriculture, and fisheries, generate waste streams with distinct challenges and opportunities. The automotive sector, for instance, faces difficulties in managing a variety of complex materials, including heavy metals, plastics, and rubber, while grappling with new trade-offs brought by electric vehicles(EVs), particularly in the recycling of lithium-ion batteries [1]. The petroleum industry, on the other hand, deals with hazardous by-products such as sludge, contaminated water, and used oils, which pose significant environmental risks but can also be transformed into secondary raw materials like synthetic fuels or asphalt modifiers [2]. In parallel, agricultural waste offers opportunities for the production of biogas, biofertilizers, and green hydrogen via syngas-based technologies, while fisheries waste can be repurposed into animal feed or fishmeal [3]. Despite advancements in recovery technologies, these industries continue to experience critical logistical challenges, from inadequate infrastructure to inefficient collection and sorting systems [4]. Addressing these gaps requires strengthened RSCSW governance, technological innovation, and integrated strategies that align with the principles of the circular economy, enabling the reintegration of waste into production cycles and reducing dependency on virgin resources. The generation of solid waste represents one of the contemporary world's most complex environmental, social, and economic challenges. Population growth, excessive consumption, and inefficient material management have intensified waste production, negatively affecting the quality of life, biodiversity, and climate [5; 6; 7; 8; 9]. The Food and Agriculture Organization (FAO) estimates that only 9% of aquaculture waste is properly managed, increasing the environmental footprint of the fishing sector [10]. This thinking is aligned with global decarbonization targets, the Sustainable Development Goals (SDGs) [11]. Studies by [PERSON] et al. [12] and [PERSON], [PERSON], and [PERSON] [13] also highlight specific challenges in waste management in sectors such as healthcare, construction, and the automotive industry. In particular, the construction industry represents one of the most ecologically impactful sectors, due to its high demand for raw materials and massive generation of demolition waste. Materials such as concrete, steel, and ceramics can be reintegrated into new production cycles through circular practices. The use of Artificial Intelligence (AI) techniques, such as object recognition, material classification algorithms, and predictive models, can support waste triage, quality assurance, and logistics planning in construction waste recycling chains. In this context, the circular economy emerges as an essential paradigm to address resource scarcity and ineffective waste management. Unlike the linear model of \"take, make, and dispose,\" the circular economy seeks to keep resources in use for as long as possible, reintegrating waste into the production cycle as secondary raw materials [14; 15; 16; 17].