Application and Impacts of Artificial Intelligence in Urban Waste Management with an Environmental Sustainability Approach (Case Study: Kermanshah)

In recent decades, rapid urbanization and increased consumption have led to the generation of high volumes of municipal solid waste in Iranian cities; an issue that not only imposes a heavy financial burden on municipalities but also carries significant negative environmental impacts. Traditional methods of waste collection and disposal in many cities, including Kermanshah, lack the necessary efficiency and have resulted in resource waste, environmental pollution, and citizen dissatisfaction. In such conditions, leveraging new technologies, especially Artificial Intelligence (AI) and smart waste management systems, can be a fundamental solution for enhancing environmental sustainability and improving urban management. The necessity of this research stems from the fact that despite the expanding application of AI in major world cities, systematic use of this technology in urban waste management has not yet taken shape in medium-sized Iranian cities like Kermanshah. Shortages in digital infrastructure, lack of integrated databases, and deficiencies in human resource training are among the obstacles to implementing smart systems in the city's waste management. The main objective of the research is to investigate the role and potential impacts of AI in optimizing the urban waste management processes of Kermanshah with an emphasis on environmental sustainability indicators. In this regard, the research seeks to evaluate the awareness level of urban managers, infrastructural capabilities, and the feasibility of using new technologies such as Machine Learning, Computer Vision, and the Internet of Things in the processes of waste collection, separation, and recycling. The research method is descriptive-analytical. Research data is collected through library studies, document analysis, and semi-structured interviews with experts in Kermanshah's urban management. Data analysis will be conducted using a mixed-method approach; qualitative data is used to identify main components and quantitative data to assess correlations between variables. Expected findings indicate that the application of AI technologies in urban waste management systems can lead to reduced collection costs, optimized transportation routes, increased recycling rates, and decreased environmental impacts. Finally, suggestions for designing a policy and technical framework for implementing smart waste management in Kermanshah will be presented.

کلیدواژه ها:

Artificial Intelligence ، Urban Waste Management ، Kermanshah ، Environmental Sustainability ، Machine Learning ، Smart City