An IoT Application for Inventory Management with a Self Adaptive Decision Model
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.
2016 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData)