Dynamic Fleet Management and Household Feedback for Garbage Collection

Abstract

We propose a solution for intelligent household garbage collection in smart cities. Garbage containers are assumed to be digitalized with Internet-of-Things sensors that are capable of sensing the fill levels of containers and transmitting this data through LoRaWAN networks to a central server. Data is used for dynamic fleet management and household feedback. We give a number of algorithms for these tasks. Fleet management requires scheduling containers for collections and assigning containers to trucks, as well as routing the trucks. Drivers receive such navigations via pervasive computing devices such as tablets, phones, or watches. Household feedback consists of information about the levels of generated garbage and the associated costs. Households receive this information on their home devices. Thus, unlike present solutions, our solution involves households in the intelligent collection of their garbage.