Multiagent Semantical Annotation Enhancement Model for IoT-Based Energy-Aware Data

Abstract

The Internet of Things (IoT) is involved in dealing with physical items, gadgets, vehicles, structures, and different things that are inserted into hardware, programming, sensors, and system availability, which empowers these items to gather and trade information. Improving extraction of sensor-based data for energy awareness and then annotating it and converting it into semantically enabled form for analyzing results with the use of improved tools and applications are the focus of this research. However, as the amount of real time data gets huge, it becomes difficult to track results when needed at once. Reconciliation of heterogeneous information sources into an interlinked data is a standout among the most pertinent difficulties for some learning based systems these days. This paper forms suitable elements by a methodology for adjustment of heterogeneous sensor-based Web assets, where different tools and applications like weather detection for self-observing and self-diagnostics use dispersed human specialists and learning. The proposed general model uses a capability of the Semantic Web innovation and concentrates on the part of a semantic adjustment of existing broadly utilized models of information representation to Resource Description Framework (RDF) based semantically rich arrangement. This work is valuable for sorting out and inquiry of the detecting information in the Internet of Things.

Data Compatibility to Enhance Sustainable Capabilities for Autonomous Analytics in IoT

“…Interoperability is one of the greatest obstructions keeping organizations from receiving the IoT [4]. The absence of similar guidelines and calculations together increment the many-sided quality, wasteful aspects, client disappointment and the expense too.…”

“…These technologies and algorithms support industries and organizations in reducing research costs. The concerned fields for data analytics are Big Data, Internet data analytics are Big Data, Internet of Things (IoT) [4], Machine Learning, Semantic Web (SW) and much more. When SW is used for data modeling, then Resource Description Framework (RDF), as a data model, plays a key role in ontology building, intelligent reasoning and data linking.…”

“…Furthermore, IoT at the point of data representation perspective uses RDF for smart objects while collecting data from sensors [4,5]. Data are collected from IoT sensors and then integrated through Semantic Web technologies to make them semantically readable from SPARQL queries [6].…”

“…IoT is a collection of scattered smart objects and entities distributed with capabilities of sharing information with the use of sensors (as shown in Figure 1). These objects have embedded identification through radio-frequency identification (RFID) technology [4,8]. Despite its extensive spread development, IoT is still in its newborn phase and has considerable room for exploration in a variety of problems like standards, scalability, heterogeneity in different devices, common service description language, domain specific service discovery, and incorporation with current IT systems [9,10].…”