A machine learning-based early forest fire detection system utilizing vision and sensors’ fusion technologies

The paper aims at utilizing machine learning (ML) towards designing an early warning forest fire detection system. With the aid of the Internet of Things (IoT) and smart edge computing, an embedded system that utilizes sensors’ fusion technology, machine vision and ML to early detect forest fire has been proposed. Different from most of the proposed fire detection systems in the literature, which either utilize vision or sensors’-based approaches to detect the fire, the proposed system utilizes both approaches jointly, which in turn will make it more accurate for fire detection. Furthermore, this paper focuses on implementing the proposed system utilizing a smart edge node and discusses the incurred technical challenges and how they have been solved.This work has been in part supported by King Abdullah II Fund for development. Grant No.2022/6 and Jordan Design and Development Bureau(JODDB).info:eu-repo/semantics/publishedVersio

Map coverage of LoRaWAN signal’s employing GPS from mobile devices

Forests are remote areas with uneven terrain, so it is costly to map the range of signals that enable the implementation of systems based on wireless and long-distance communication. Even so, the interest in Internet of Things (IoT) functionalities for forest monitoring systems has increasingly attracted the attention of several researchers. This work demonstrates the development of a platform that uses the GPS technology of mobile devices to map the signals of a LoRaWAN Gateway. Therefore, the proposed system is based on concatenating two messages to optimize the LoRaWAN transmission using the Global Position System (GPS) data from a mobile device. With the proposed approach, it is possible to guarantee the data transmission when finding the ideal places to fix nodes regarding the coverage of LoRaWAN because the Gateway bandwidth will not be fulfilled. The tests indicate that different changes in the relief and large bodies drastically affect the signal provided by the Gateway. This work demonstrates that mapping the Gateway’s signal is essential to attach modules in the forest, agriculture zones, or even smart cities.This work has been supported by Fundação La Caixa and FCT - Fundação para a Ciência e Tecnologia within the Project Scope: UIDB/5757/2020. Thadeu Brito is supported by FCT PhD Grant Reference SFRH/BD/08598/2020. Beatriz Flamia Azevedo is supported by FCT PhD Grant Reference SFRH/BD/07427/2021.info:eu-repo/semantics/publishedVersio

A EDUCAÃ?Ã?O PERMANENTE NA SAÃ?DE

Resumo: trata-se de um estudo sobre Educação Permanente na área da Saúde. Descreve-se o pensamento dos autores entre 1990 a 2008, relatando as concepções, transformações, dimensões e proposições da Enfermagem. Os resultados indicam dimensões de educação à distância, qualificação dos profissionais, educação de jovens e adultos e as mudanças curriculares. A Enfermagem destaca-se pelos desafios da integração ensino-serviço para mudanças das práticas do cuidado, com 68% das publicações analisadas. Palavras-chave: Educação permanente. Saúde. Enfermagem