Fingerprinting-Based Indoor Positioning Using Data Fusion of Different Radiocommunication-Based Technologies

Wireless-radio-communication-based devices are used in more and places with the spread of Industry 4.0. Localization plays a crucial part many these applications. In this paper, novel radiocommunication-based indoor positioning method is proposed, which applies fusion fingerprints extracted various technologies to improve overall efficiency. The aim research apply differences, occur due that different behave differently an space. proposed was validated using training test data collected laboratory. Four technologies, namely WiFi received signal strength indication (RSSI), ultra-wideband (UWB) RSSI, UWB time flight (TOF) RSSI 433 MHz frequency band all their possible combinations, were tested examine performance method. Three widely fingerprinting algorithms, weighted k-nearest neighbor, random forest, artificial neural network implemented evaluate efficiency achieved results show accuracy localization can be improved by combining technologies. combination two low-cost i.e., technology, resulted 11% improvement compared accurate technology. Combining module other less significant since sensor provides lower error rates, when alone.