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A mitigação de desastres naturais exige respostas rápidas e confiáveis. No Brasil, a estação de chuvas provoca muitos alagamentos em regiões urbanas e, para monitorar esse fenômeno, foi instalada em São Carlos-SP uma rede de sensores sem fio para acompanhar o nível de água dos rios da cidade. Entretanto, essa rede de sensores está suscetível a falhas que podem comprometer o funcionamento do sistema, e a adoção de mecanismos redundantes e de redes móveis 3G podem acarretar em custos proibitivos à monitoração desses rios, além de não garantirem a operação normal desse monitoramento. Assim, este trabalho apresenta uma solução baseada em veículo aéreo não tripulado (VANT) para reduzir os problemas oriundos das falhas em uma rede de sensores para detectar desastres naturais como enchentes e deslizamentos. Na solução proposta, o VANT pode ser transportado para o sítio do desastre para minimizar os problemas provenientes das falhas (por exemplo, para servir como um roteador ou até mesmo para servir como uma mula de dados e transmitir imagens em tempo real para equipes de resgate). Estudos foram conduzidos em um protótipo real, equipado com o UAV Brain (módulo computacional desenvolvido especificamente para este projeto), para uma análise exploratória do consumo energético do VANT e do rádio transmissor que equipa o VANT. Os resultados mostram que a melhor situação para o rádio comunicador se dá quando o VANT está no ar e com uma antena de maior ganho, e os fatores que mais influenciam no consumo energético do rádio são a altura do VANT e o tipo de antena utilizado. Além disso, tais resultados mostram também a viabilidade desta proposta em redes de sensores sem fio linear e esparsa. The mitigation of natural disasters requires quick and reliable answers. In Brazil, the rainy season causes many flooding in urban areas and, to monitor this phenomenon, a wireless sensor network to monitor the water level of the citys rivers was installed in São Carlos-SP. However, this sensor network is susceptible to failures that may jeopardize the operation of the system, and the adoption of redundant mechanisms and 3G mobile networks may result in prohibitive costs to the monitoring of these rivers, and does not guarantee the normal operation of monitoring. This work presents an aerial vehicle-based solution unmanned (UAV) to reduce the problems originated from failures in a network of sensors to detect natural disasters such as floods and landslides. In the proposed solution, the UAV can be transported to the disaster site to minimize problems arising from failures (eg, to serve as a router or even to serve as a data mule and transmit images in real time for rescue teams). Studies were conducted in a real prototype, equipped with UAV Brain (computational module developed specifically for this project), for an exploratory analysis of the energy consumption UAV and radio transmitter fitted to the UAV. The results show that the best situation for the radio communicator is when the UAV is in the air and with a higher gain antenna, and the factors that most influence on the radio energy consumption are the height of the UAV and the type of antenna used. Furthermore, these results also show the feasibility of this proposal in linear and sparse wireless sensor networks.

Green computing has emerged as a hot topic leading to a need to understand energy consumption of computations. This need also extends to devices with limited resources as are common in the internet of things. RESTful services have shown their potential on such devices, but there are many choices of frameworks for their development and execution. Current research has analysed performance of the frameworks but no attention has been given to systematically studying their power consumption. In this paper we analyse the execution behaviour and power consumption of web services on devices with limited resources and make initial observations that should influence future development of web service frameworks. Specifically, we conduct experiments comparing web services in the Axis2 and CXF frameworks analysing the respective performance and power consumption. Bringing together the best features of small devices and SoC, it is possible to provide diverse, mobile and green applications — however careful selection of development environments can make significant differences in performance and energy consumption.

This paper analyzes the execution behavior of web services on devices with limited resources. The experiments compare web services in the Axis2 and CXF frameworks analyzing performance and power consumption. To determine which framework is better suited for service provision, a testing environment and a performance and energy evaluation between them are presented. We show that the Raspberry Pi can be useful in service-oriented applications for different types of tasks. Bringing together the best features of small devices and SoC, it is possible to provide diverse, mobile and green applications.