Optimization of IoT Devices in Smart Home to Minimize Cost Energy Conservation Based on Human Detector

Smart home systems are becoming an exciting new paradigm among researchers and homeowners. In modern society, the use of electrical appliances is an essential element for a comfortable life. However, in many classrooms or dorms, students may waste energy by leaving lighting and air conditioning systems on even when not in use and an optimized distribution of the used sensors is required for the resource-efficient (indoor) location of mobile humans. Indoor positioning, or the location of beacons or sensors inside buildings, may be a challenging and time-consuming process, particularly when done by hand. This topic has already been attempted to be solved by a number of researchers under various use cases and using various approaches. Nevertheless, none of the approaches that are now available use Boolean variables alone to do constraint programming. To address this issue, we are creating a smart IoT system that saves energy by turning on lights and fans when motion is detected in a specific part of a room. To be more precise, we want to optimize the beacons for an indoor locating system that uses trilateration. According to this method, three beacons have to be within range of each potential location inside the structure. The initially determined beacon placements are then further optimized in a subsequent stage. In order to do this, fewer beacons are used. Next, we assess the beacon placements’ quality by comparing them to a manually optimized beacon placement and assessing the quality of many sample places in an existing building. This system uses a PIR sensor for motion detection which makes it cost efficient. The electrical switch is controlled by a5V-1 channel relay connected to an Arduino board in the switchboard.