Electrical power quality (PQ) is a crucial competitive and developing factor to all economic activities. The economic impact resulting from a bad PQ would be drastic on all consumers. Computers, uninterruptible and switched power supplies (UPS), and fluorescent lamps/tubes are examples of nonlinear loads that have the consumption of a nonsinusoidal current, which cause disturbances in the power supply system (that may be severe or not). This study discusses residential generic power circuitry analysis and simulation, under nonlinear loads, in connection with undergraduate electrical engineering education. It briefly reviews some of the basic techniques, and presents a software tool that has been found to be very useful in the context. The tool has an easy-to-use, friendly interface, and can be used to teach design techniques or as a laboratory support to study the applicability of known methods to real situations. The students can perform simulations with their own data on Microsoft TM Windows 1 -based platforms. ß
Wireless Sensor Networks (WSN) can be used to acquire environmental variables useful for decision-making, such as agriculture and forestry. Installing a WSN on the forest will allow the acquisition of ecological variables of high importance on risk analysis and fire detection. The presented paper addresses two types of WSN developed modules that can be used on the forest to detect fire ignitions using LoRaWAN to establish the communication between the nodes and a central system. The collaboration between these modules generate a heterogeneous WSN; for this reason, both are designed to complement each other. The first module, the HTW, has sensors that acquire data on a wide scale in the target region, such as air temperature and humidity, solar radiation, barometric pressure, among others (can be expanded). The second, the 5FTH, has a set of sensors with point data acquisition, such as flame ignition, humidity, and temperature. To test HTW and 5FTH, a LoRaWAN communication based on the Lorix One gateway is used, demonstrating the acquisition and transmission of forest data (simulation and real cases). Even in internal or external environments, these results allow validating the developed modules. Therefore, they can assist authorities in fighting wildfire and forest surveillance systems in decision-making.
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