Integration of Multi-Modal Sensors and Images for Monitoring Book Stock Inventory in an Internet of Things- Based Warehouse - Fandi Ishadinata; Supriadi Sahibu; Zahir Zainuddin (Politeknik Negeri Batam, 2026)
Study This designing system supervision inventory stock books in a warehouse based on the Internet of Things (IoT), with combining multi-modal sensors and digital images . The system This developed For increase accuracy recording stock , reduce errors caused humans , as well as monitor condition goods in a way directly Components device hard used includes Raspberry Pi 5 as controller , loadcell sensor for measure weight , ultrasonic sensor For evaluate capacity , and Raspberry Pi camera for needs visual verification . The information generated will sent to the IoT platform via MQTT protocol and visualized with using Node-RED. Approach study following the Research and Development (R&D) model based on ADDIE, including stages analysis needs , design , development , implementation , and assessment system . The results of implementation show that system This capable monitor stock with precise and provide announcement automatic moment capacity storage reaching the minimum limit. The combination of multi-modal sensors and imagery allows manager warehouse For get information about weight , capacity , and appearance condition goods in a way simultaneously , so that decision For filling repeat can done more fast and accurate . Trial show that this IoT technology capable increase efficiency operational , pressing cost power work , and minimize risk lost goods , making them the right modern solution For management inventory in the warehouse.