Integration of WSN and RFID networks, and redundant data filtering

 Radio frequency identification (RFID) and wireless sensor networks (WSNs) are two important and widely applied wireless technologies with limitless future potential. RFID is used to detect object location, while WSN is used for environmental sensing and monitoring. The integration of RFID and WSN not only provides identity and location but also facilitates environmental condition sensing. However, RFID data contains excessive duplication, which results in time delay and increased energy consumption, resulting in wastage of various network resources. This paper proposes a hybrid network designed by the integration of WSN and RFID and consisting of seven types of nodes. In this architecture, the entire network is divided into clusters and this clustering is obtained by particle swarm optimization. In addition, it also proposes an algorithm to overcome the issue of redundant data on this hybrid network. Simulation results show that the proposed algorithm reduces both data redundancy and processing time compared to existing algorithms.