IoT resource discovery based on multi faected attribute enriched CoAP: smart office seating discovery

With the broad spectrum of IoT domains, heterogeneous devices can amalgamate the physical world into a digital era. The current need of the hour is to discover and retrieve the most pertinent devices amongst similar capable devices in an IoT environment. This paper presents a novel, multifaceted approach to finding IoT-based innovative office seating using semantically enriched Constrained Application Protocol (CoAP). The multi-layered approach is implemented where the devices’ specifications are considered for attribute extraction. These attributes are enriched in CoAP protocol. The most pertinent device is retrieved and provided to user space based on multi-attribute-based decision-making. User preferences along with system-generated recommendations, are considered for device ranking. The office seating is modelled as an IoT resource, where in multiple such office seatings in a smart office is considered and the best seating is retrieved. The proposed approach is compared with current state of art and the efficiency of the same is evaluated in terms of bandwidth usage, time of retrieval and accuracy.