Battery Driven Embedded System for Indoor Localization of Pneumatic Tools

Sammanfattning: As the rapid progress in technology changes our daily life, it also changes how the Industry works. The new developments enable technologies such as the Internet of Moving Things (IoMT), and through these technologies, new challenges arise. IoMT adds one more vital issue, localization, to be solved in comparison to the Internet of Things (IoT). To enable IoMT in the manufacturing industry, there are still problems that need to be overcome. Critical statements such as power consumption, price, accuracy, data management, and size. In this thesis, an evaluation of a new sensor system for an air pneumatic grinder is conducted. The features of the sensor system are to report data from the grinder to the cloud and to localize the position of the grinder. The focus was to optimize the localization algorithm and power consumption of the system. The localization of the grinder was conducted with a new and improved algorithm, Ring Error Difference System (REDS), introduced in this thesis. The new algorithm increased the previous known iRingLA accuracy from 2.91 m to 2.33 m for Bluetooth Low Energy (BLE) and from 3.99 m to 2.84 for Wi-Fi, according to the experiments performed. The final system was able to estimate the operation runtime with an error of 24 s for an operational runtime of 905 s. The operational lifetime of the system was 242 h and 45 h, respectively, for BLE and Wi-Fi. An optimized software was introduced to decrease power consumption. The optimized version was estimated to have an operational lifetime of 1540 h for BLE, which did not reach the wanted lifetime of 3000 h set by Atlas Copco. Hence, I conclude that the hardware, Wemos ESP32, used in the thesis, is not feasible for this solution. Simpler hardware, than the Wemos ESP32, should be used to be able to reach the goal of 3000 h.