@article{scholars12306,
            note = {cited By 5; Conference of 3rd International Conference of Reliable Information and Communication Technology, IRICT 2018 ; Conference Date: 23 June 2018 Through 24 June 2018; Conference Code:218299},
            year = {2019},
         journal = {Advances in Intelligent Systems and Computing},
             doi = {10.1007/978-3-319-99007-1{$_1$}{$_3$}},
           pages = {128--138},
           title = {Realizing the value of big data in process monitoring and control: Current issues and opportunities},
       publisher = {Springer Verlag},
          volume = {843},
            isbn = {9783319990064},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85053889319&doi=10.1007\%2f978-3-319-99007-1\%5f13&partnerID=40&md5=d6bf0dda3cc0fdfd0d4008e43d3a8bda},
        abstract = {With the advancement of Big Data, data analytics have benefited many organizations and industries. The continuous improvement of process industries is a challenging task that requires insights for efficient process monitoring with minimum downtime and safer operations. These industries generate a large amount of data i.e. {\^a}??Big Data{\^a}?? every second that contains useful information. For better control, different analysis can be executed using statistical methods, data mining or machine learning. This data can be used for daily process operations and decision making. However, the past literature on Big Data have put limited focus on realizing its implication in process monitoring and control. The paper emphasizes on the issues and opportunities faced by process industries in terms of Big Data collection, storage and analysis for process monitoring and control. {\^A}{\copyright} Springer Nature Switzerland AG 2019.},
        keywords = {Artificial intelligence; Big data; Data mining; Decision making; Digital storage; Intelligent control; Learning systems; Process monitoring; Soft computing, Advanced Process Control; Big Data Analytics; Continuous improvements; Data analytics; In-process monitoring; Process industries; Process monitoring and control; Process operation, Process control},
          author = {Rubab, S. and Taqvi, S. A. and Hassan, M. F.},
            issn = {21945357}
}