Search Engine for Heterogeneous Internet of Things Systems and Optimization

The Internet of Things (IoT) now thoroughly suffuses our world, building on network communication and software technologies to increasingly interconnect sensors and actuators for unprecedented data collection. Yet, massively distributed IoT systems may be isolated in traditional intranets, creating unnecessary redundancy between different organizations that fulfill the same functions. To address these issues and develop an IoT Search Engine that can fully cope with the challenges of modern IoT deployment, in this paper we propose an IoT search engine platform using Python-based COAP (Constrained Application Protocol) which can discover and subscribe IoT sensors within the coverage of IoT search engine gateways. The search engine can retrieve data from sensors of different IoT systems, which we demonstrate using a traffic dataset to simulate autonomous vehicle queries. Our implementation also includes two designed algorithms to demonstrate mechanisms for data and data optimization.