Smart homes have become a reoccurring topic in our society. Many homes have been modernized in such a way that technology takes a prevailing role. As a result, many electronics technicians have to adapt to the ongoing modernization. With that said, many improvements can be implemented in order for technicians to work more efficiently and flawlessly. One of these improvements could be a localization software that locates IoT devices in a household. As many IoT devices are installed in walls, the respective location cannot be determined without a great margin of error. A software that locates these devices and maps them to the respective household can prove to be very beneficial. In order for such a software to exist we need to determine the distance between IoT devices through some mean. Wi-fi signals consist of Channel State Information (CSI) that could possibly describe the physical distance between devices. This thesis focuses on the evaluation of Channel State Information in Wi-Fi signals and the possibility of using this information to determine the distance of devices to each other. If the CSI information proves to be successful in determining the distance, a complete software will be implemented that calculates the positions of all IoT devices in a local network. For this thesis we will focus on ESP32 microcontrollers that already utilize CSI data for human movement detection.