Improve Machine Interpretation and Self Description of Data Using Semantic Web with Special Reference to the Internet of Things IOT

Abstract

Increasing Internet of Things (IoT) adoption has led to deployment in many domains like newlinesmart homes, smart cities, transportation, medical, agriculture, etc. By sensing their newlinesurroundings, IoT devices transmit information via the Internet and this information will be helpful for taking some actions. According to statistics, by 2030, there will be more than 25.4 billion active IoT devices, generating a large amount of raw data being collected by IoT objects. Different IoT sensors and objects generate heterogeneous data, varying in type and format. Therefore, reusing raw data from IoT systems is complex, and interoperability must need. As a result of a lack of interoperability in IoT systems, these systems cannot do their jobs effectively. This problem can be addressed by using newlinesemantic web technologies to create an enriched data format from raw IoT data by newlinemodelling and representing it using knowledge. This research section aims to highlight the best possible outcomes for semantic interoperability for IoT systems, which can serve as a guide for future research through the presentation of a literature review on semantic interoperability for IoT systems, Core newlineconcept of this research is to get a real-time temperature and humidity data of home using DHT11 sensor, Arduino UNO, NodeMCU ESP8266 Wi-Fi Module. Then access, analyze and represent data locally, on the cell phone and in the Cloud. As far as IoT and Semantic Web are concerned, we are collecting DHT11 sensor data and deploying it on the Thingspeak cloud platform, also visualize it there; at last, we import those raw data in newlineprotégé tools and perform knowledge representation of those raw data using Ontology, RDF triple and SPARQL concepts. This research mainly helps those getting raw data without context, so Semantic Web Technologies gives context to the raw data and makes it as Self Described that it could be easily understood and Interpreted by the machine to solve interoperability and heterogeneity problems.