UAV Cloud Platform for Precision Farming

• Autor(a) principal: Pino, Miguel
• Data de Publicação: 2021
• Tipo de documento: Dissertação
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10362/118697
• topic: Cyber-Physical Systems; Unmanned aerial vehicles; Cloud Computing; Precision Farming; Domínio/Área Científica::Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática

A new application for Unmanned Aerial Vehicles comes to light daily to solve some of modern society’s problems. One of the mentioned predicaments is the possibility for optimization in agricultural processes. Due to this, a new area arose in the last years of the twentieth century, and it is in constant progression called Precision Farming. Nowadays, a division of this field growth is relative to Unmanned Aerial Vehicles applications. Most traditional methods employed by farmers are ineffective and do not aid in the progression and solution of these issues. However, there are some fields that have the possibility to enhance many agriculture methods, such fields are Cyber-Physical Systems and Cloud Computing. Given its capabilities like aerial surveillance and mapping, Cyber- Physical Systems like Unmanned Aerial Vehicles are being used to monitor vast crops, to gather insightful data thatwould take a lot more time if being collected by hand. However, these systems typically lack computing power and storage capacity, meaning that much of its gathered data cannot be stored and further analyzed locally. That is the obstacle that Cloud Computing can solve. With the possibility to offload computing power by sending the collected data to a cloud, it is possible to leverage the enormous computing power and storage capabilities of remote data-centers to gather and analyze these datasets. This dissertation proposes an architecture for this use case by leveraging the advantages of Cloud Computing to aid the obstacles of Unmanned Aerial Vehicles. Moreover, this dissertation is a collaboration with an on-going Horizon 2020 European project that deals with precision farming and agriculture enhanced by Cyber-Physical Systems.