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Waste management (WM) is one of the most significant environmental problems and a major challenge for any large city, municipality, or even country. Smart waste management (SWM) involves capturing, processing, storing, and visualizing an enormous amount of relevant heterogeneous data in different formats. There are a large number of SWM solutions that operate at different levels and solve different sets of problems, but there is no general description that unites all the accumulated results at any level of operation. The objective of this doctoral thesis is 1) to explore how to develop an Internet of Things (IoT)-based SWM system that improves the waste management processes of a city and 2) to develop an SWM system model and guidelines that combine all the collected knowledge regarding SWM systems elements, technologies, services, and other WM system contexts and provide recommendations to achieve a city’s WM-related goals. This research concludes that to develop an SWM system that improves the waste management processes of a city, it is important to consider 1) WM-related goals and problems of the city, 2) city context (city size and population, climate, etc.), 3) city’s WM system context (existing WM infrastructure and technologies), 4) stakeholders and their needs, 5) residents’ awareness levels, 6) financial aspects, 7) good practices of resolving similar WM-related problems and achieving similar WM-related goals in cities with the a similar context of the city and city WM system. This doctoral thesis offers two core contributions: 1) The SWM system model, which combines all the collected knowledge — WM technologies …