Fusão de dados multinível para sistemas de internet das coisas em agricultura inteligente

Abstract

The usage of Wireless Sensor Networks (WSN) to detect and monitor phenomena isn’t a new concept, with studies dating back to 1980, but it has gained momentum with the expansion of Internet of Things (IoT), which aims to enable day to day objects to sense, identify and analyze our world. For IoT to be viable, it is necessary for the objects/sensors to be low-cost, and that implies a series of limitations: low battery, low processing and storage capabilities, low accuracy, etc. In this context, data fusion techniques can be used to mitigate some of these limitations and make the adoption of low-cost sensors viable. This dissertation proposes a data fusion architecture for IoT, improving sensor accuracy, detecting events/anomalies (such as sensor failure) and enabling automated decision making. As a case study, experimental cultures of precocious dwarf cashew and coconut trees were monitored.