Abstract
The digitization of modern manufacturing systems has led to a significant increase in data creation, commonly discussed to as Big Data. Despite the existence of various technologies and techniques for collecting such data, its transformation into meaningful information and knowledge is still in its early stages. Advances in sensor networks and Internet of Things (IoT) technology have made it possible to collect enormous amounts of data. However, analyzing such massive quantities of data requires more effective methods that can offer accurate analysis. Artificial Intelligence (AI) techniques, including machine knowledge and evolutionary algorithms, have proven to be capable of delivering precise, fast, and scalable results in big data analytics. Despite the growing awareness in these techniques, there is currently no comprehensive survey available that covers the various artificial intelligence techniques used in big data analytics.
Publisher
Century Science Publishing Co
Reference16 articles.
1. Klein S. IoT solutions in Microsoft’s azure IoT suite. Berkeley: Apress; 2017. The world of big data and IoT; pp. 3–13. 2017.
2. Chang WL, Grady N, NBD-PWG NIST Big Data Public Working Group . NIST big data interoperability framework. Gaithersburg: National Institute of Standards and Technology (NIST); 2015.
3. Feng M, Zheng J, Ren J, Hussain A, Li X, Xi Y, Liu
4. Q. Big data analytics and mining for effective visualization and trends forecasting of crime data. IEEE Access. 2019;7:106111–106123. doi: 10.1109/ACCESS.2019.2930410.
5. Gandomi A, Haider M. Beyond the hype: big data concepts, methods, and analytics. International Journal of Information Management. 2015;35(2):137–144. doi: 10.1016/j.ijinfomgt.2014.10.007. 2015