This work proposes an IoT-based indoor asset tracking system for manufacturing, addressing the limitations of traditional methods. It compares the performance of the Raspberry Pi Pico W (Wi-Fi) and the Arduino Nano 33 BLE Sense (BLE) for real-time asset location and status monitoring using beacons and tags. The study found that the Nano 33 BLE Sense, combined with TinyML, offered superior efficiency and accuracy. The system aims to improve productivity and optimize operations through seamless Industry 4.0 integration.