An IoT solution for load monitoring and tracking of garbage-truck fleets

Maia, Jorge; Silva, Jones Yudi Mori Alves da

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Campo DC	Valor	Idioma
dc.contributor.author	Maia, Jorge	-
dc.contributor.author	Silva, Jones Yudi Mori Alves da	-
dc.date.accessioned	2021-01-28T18:57:24Z	-
dc.date.available	2021-01-28T18:57:24Z	-
dc.date.issued	2020	-
dc.identifier.citation	MAIA, Jorge; YUDI, Jones. An IoT solution for load monitoring and tracking of garbage-truck fleets. In: 2020 IEEE CONFERENCE ON INDUSTRIAL CYBERPHYSICAL SYSTEMS (ICPS), 2020, Tampere. p. 406-410. DOI: 10.1109/ICPS48405.2020.9274699. Disponível: https://ieeexplore.ieee.org/document/9274699.	pt_BR
dc.identifier.uri	https://repositorio.unb.br/handle/10482/39985	-
dc.language.iso	Inglês	pt_BR
dc.publisher	IEEE	pt_BR
dc.rights	Acesso Restrito	pt_BR
dc.title	An IoT solution for load monitoring and tracking of garbage-truck fleets	pt_BR
dc.type	Trabalho	pt_BR
dc.subject.keyword	Internet das Coisas (IoT)	pt_BR
dc.subject.keyword	Azure	pt_BR
dc.subject.keyword	Hub IoT	pt_BR
dc.subject.keyword	Telemetria veicular	pt_BR
dc.subject.keyword	Edge computing	pt_BR
dc.subject.keyword	Computação em nuvem	pt_BR
dc.identifier.doi	10.1109/ICPS48405.2020.9274699	pt_BR
dc.relation.publisherversion	https://ieeexplore.ieee.org/document/9274699	pt_BR
dc.description.abstract1	One of the most significant problems in the modern world is the amount of waste generated by the growing urban population. The destination of this garbage can be recycling, burning or disposal in landfills. A family of four people can produce, on average, 3 kilograms of garbage per day. The collection of this waste is mostly done by trucks that go through the streets of the cities collecting the garbage from door to door, following predetermined routes. When a truck reaches its maximum load, it goes to the unloading site, returning to the route at the same exit point in order to finish that route. The logistical problems involved are several: fines for overloading the truck, late collection times, labor lawsuits, among others. This project proposes a solution based on Internet Things to monitor the location of the truck and its cargo generating maps in near real-time, to allow the dynamic optimization of the routes followed by the various paths of the fleet. Our system consists of an on-board system that measures the truckload and determines its position, sending this data to a cloud computing solution. Several tests were carried out in the field, with pathways from a real fleet, operating on an ordinary working day. The results show that the system developed is viable, successfully meeting the requirements of the application.	pt_BR
dc.description.unidade	Faculdade de Tecnologia (FT)	-
dc.description.unidade	Departamento de Engenharia Mecânica (FT ENM)	-
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