The widespread of Internet connection, particularly on small devices (embedded systems), has allowed the development of the Internet of Things (IoT) concept, due to the connection of these devices to web micro services (Cloud), and has had a major role in Industry 4.0 [1]. Through the advances of wireless technologies, these devices were able to have an Internet connection, becoming available everywhere. The creation of Wireless Sensor Networks (WSNs) has enabled the use of networks composed of independent devices (nodes or edge devices), equipped with sensors and actuators, and made it possible to collect information about the environment where they are deployed [2]. The growing necessity of having a wider coverage area for Wireless Sensor Networks, along with the demanding low power requirements on devices has enabled Low Power Wide Area (LPWA) technologies to arise. These technologies are able to reach further coverage than conventional wireless technologies (such as Bluetooth, Wi-Fi, ZigBee etc), as well as raising the energy autonomy of the devices [3], which makes LPWA technologies ideal for wider areas. The recent tragedies of wildfires in Portugal, in both 2017 and 2018, had great impact on economic and social levels. Early detection and alerts about wildfires are crucial to prevent them from spreading [4]. Therefore, by using LPWA technologies in forests, a case study can be made for the wildfire occurrences in forests. Through the use of independent devices equipped with sensors, data can be collected from the environment that might detect that a fire is starting, and then send alerts to fire fighting units. In this Master’s thesis it was developed the architecture of sensor nodes, to be integrated in a Low Power Wide Area Network (LPWAN). By using the LoRa technology to achieve a long range between the sensor nodes and the network coordinator, it is possible for edge devices to collect and send data to upper levels of the network. It was possible to gather information about the environment and further understand LoRa’s potential for sending all the data to the upper levels of the network.