An IoT Application for Inventory Management with a Self-Adaptive Decision Model

Abstract

Safety storage in large warehouse is an urgent issue to be addressed by both the local authorities and businesses, especially after the Tianjin explosions. This paper proposes an inventory management system for a warehousing company. The system integrates RFID technology and a self-Adaptive distributed decision support model for inbound and outbound actives, inventory location suggestions and incident handling. The model consists of three major components: environment recognition, knowledge merging and the decision making. In addition, a 'self-adaptive' feature is adopted for adjusting the knowledge used in decision making procedure. An experiment is also outlined to validate the utilisations of our model and the proposed system.