Context aware middleware for RFID based pharmaceutical supply chain

Radio frequency identification (RFID) technology is paramount for the automation and optimization of supply-chain activities. RFID tags can drastically improve the efficiency of inventory management, especially in the pharmacy supply chain. Thus, the drugs tracking can be enhanced in the pharmaceutical manufacturing plants all across the world paving the way for the wide deployment of the Internet of Things (IoT). The connected things in manufacturing processes have gained prominence owing to the growing number of unqualified pharmacies and counterfeit drugs. These sensors continuously generate a large amount of contextual information like locations and time points so as to control and manage drugs quality and distribution. Based on these contextual information, business logic can be implemented efficiently. Collection, modeling, reasoning, and distribution of context in relation to sensor data plays a critical role. In this paper, we propose a context-aware middleware for RFID based pharmacy supply chain, which aims to offer a deeper intelligence for the objects monitoring. A variant of Fosstrack middleware was proposed to offer a deeper intelligence in the RFID based supply chain.