Técnicas de geolocalização em redes LoRaWan como abordagem de tolerância a falhas em dispositivos de rastreamento baseado em GPS
The wide adaptation of the Internet of Things (IoT) concept involves increasing the reliability and availability of its applications in the event of failure. The heterogeneity of IoT components, combined with computationally limited devices integrated to the Internet, pose additional challenges to a...
| Autor principal: | Pastório, André Franscisco |
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| Formato: | Trabalho de Conclusão de Curso (Graduação) |
| Idioma: | Português |
| Publicado em: |
Universidade Tecnológica Federal do Paraná
2021
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| Assuntos: | |
| Acesso em linha: |
http://repositorio.utfpr.edu.br/jspui/handle/1/25629 |
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| Resumo: |
The wide adaptation of the Internet of Things (IoT) concept involves increasing the reliability and availability of its applications in the event of failure. The heterogeneity of IoT components, combined with computationally limited devices integrated to the Internet, pose additional challenges to achieving fault tolerance. Smart cities comprise an IoT scenario where the city is connected. Long-range, low-power networks are used in such applications to provide connectivity. In this context, object tracking is an important functionality used, for example, to track fleet vehicles in real time over the Internet. The use of common location technologies such as GPS results in high energy consumption. Allied to that, or malfunction of a GPS device can compromise the application. This work investigates how fault tolerance in IoT can be efficiently developed through a systematic literature review. Furthermore, to mitigate a GPS failure in tracking devices, this work implements a hybrid location strategy in LoRaWAN networks. The strategy considers that in case of GPS failure, coordinates are estimated using location algorithms. The implementation is compared to a commercial tool, called LoRa Cloud, which only allows for a thousand daily requests. An environment with three gateways LoRaWAN was set up to perform an assessment. The results show errors below 151 and 126 meters in the worst case considering the implementation performed and the LoRa Cloud tool, respectively. |
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