Challenges and Solutions of Big Data and IoT

Challenges and Solutions of Big Data and IoT

Jayashree K. (Rajalaskshmi Engineering College, India), Abirami R. (Rajalaskshmi Engineering College, India) and Rajeswari P. (Rajalaskshmi Engineering College, India)
Copyright: © 2019 |Pages: 9
DOI: 10.4018/978-1-5225-7432-3.ch015
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The successful development of big data and the internet of things (IoT) is increasing and influencing all areas of technologies and businesses. The rapid increase of more devices that are connected to IoT from which enormous amount of data are consumed indicates the way how big data is related with IoT. Since huge amount of data are obtained from different sources, analysis of these data involves much of processing at each and every level to extract knowledge for decision making process. To manage big data in a continuous network that keeps expanding leads to few issues related to data collection, data processing, analytics, and security. To address these issues, certain solution using bigdata approach in IoT are examined. Combining these two areas provides several opportunities developing new systems and identify advanced techniques to solve challenges on big data and IoT.
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Now a days Bigdata and Internet of Things (IoT) have emerge as the important areas in many developing countries with respect to various commercial, industry and also in other applications. The term IoT refers to connection of all physical devices in the world with the help of internet, by which most of the big data are gathered, aggregated and managed. Bigdata also helps in analyzing this data that is gathered and stored to obtain useful results. The driving force behind IoT and bigdata is analyzing and collecting the data based on consumer’s actions, to predict what people would buy and why they buy that particular product. One of the example, is loyalty cards given in grocery shops and other commercial outlets. When users use the card they would identify what and why people buy the product, this information can be helpful to improve the sales as well as profit (Gubbi et al., 2013).

Few commercial and government sectors work in the field of bigdata and IoT to identify the ways to improve the services in the field of agriculture, electricity, forestry, treatment of water and manufacturing sectors from where large amount of data is collected and also the ways to increase the profit rate. The major factors like low rejection rates, increased quality, low downtime, increased throughput, improved security and effective use of resources, labor remains the vital cause to implement IoT and Bigdata (Advantech).

Internet reconstructed the ways of business, global interactions and civilizing reformation. Presently, devices with the help of internet are used to control various automated gadgets paving a way to IoT. Thus even machines have become the users of internet, like the humans using web browsers. Researchers are attracted to IoT because of its increasing opportunities and challenges. It also has an vital impact on future technologies like network, communication and on infrastructure. Hence, the devices will be intelligently connected, controlled and managed. In-spite of few issues related to volume, velocity and variety, the concept of IoT became the most relevant topic because of the usage of mobile devices, various communication devices, embedded technologies, cloud computing concepts and data analytics are being widely used now a days. IoT provides services to any kind of application be it a simple or complex application. Even-though various definitions, contents and comparisons of concepts are given to IoT, it still remains to be a puzzling topic (Acharjya et al., 2016). Research work are being carried out in incorporating various technologies like computation intelligence and bigdata, so that management of data and knowledge discovery can be improved on huge applications like applications that deals with automation.(Mishra et al., 2015).

Knowledge discovery began by identifying how people process the information using frames, protocols, tags and networks. Based on processing of data, knowledge discovery is divided into four phases like a) knowledge acquisition, b)knowledge base, c) knowledge dissemination and d) knowledge application.

In the first stage which is knowledge acquisition, several standard and evaluation techniques are used to discover knowledge from the data. Then various experts systems and knowledge base are used to store the discovered knowledge of the data which is second phase (knowledge base). In knowledge dissemination phase, the data stored in knowledge base are analyzed so that useful information are obtained or extracted by searching documents, knowledge within documents and knowledge,this process is also called as knowledge extraction. Finally, the knowledge discovered has to be applied on several applications. All these phase are done repeatedly to extract he knowledge from the data. Knowledge exploration remains a research topic to deal with the issues related to it. (Kahani et al., 2015).

Thus, this chapter discusses the background of big data and IoT. It also discusses about various challenges of big data and IoT in detail with solution for issues. The various related work and application of big data and IoT would be addressed in this chapter.

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