In this research work, we describe the development and subsequent validation of EnerMon a flexible, efficient, edge-computing based Internet of Things (IoT) LoRa (LongRange) System to monitor power consumption. This system provides real-time information and a descriptive analytics process to provide a ‘big picture’ about energy consumption over time and identify energetic waste. The solution is based on Arduinos, current transformer sensors, Raspberry Pi as an application server and LoRa communication alongside a description and information on what is to be expected of it, describing the development process from the design phase to the validation phase with all steps in between. Due to LoRa low debit communication, an edge computing approach was implemented to create a real-time monitoring process based on this technology. This solution, with the help of descriptive analysis, allows the creation of an energetic local footprint, using a low-cost developed solution for less than 80€ per three-phases monitoring device. This solution also allows for easy installation without communication range and obstacles limitations making it easy use in different situations from big complex building to smaller consumers, such as electric boilers, or simply to measure the energetic footprint of tourists in a small local tourist apartment.
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