The rapid increasing of real-time applications in today’s IoT (internet of things) world progressively lead to several problem issues such as, data volume, velocity, variety, and value. The study reveals that around 80% data in today’s IoT world are unstructured and needs an extensive knowledge exploration framework to turn the massively produced data into cognitive values (knowledge) of goldmines. In contemporary IoT vicinities, the time to get knowledge is very slow and the applicability of the knowledge is very poor, so the knowledge researchers start looking new framework that deals with the problems of semantic knowledge analytics and inference. In a typical semantic knowledge analytic scenario, context specification, rule specification, and frame specification may be used to define the structural relationships of knowledge, where the contexts, rules, and frames are stored as specification of framework and sub-framework. In this work, we investigate the viability of a context and rule Analytic framework (CORA-framework) for trustful knowledge analytic and inference in the cloud centric IoT vicinities. We also investigate a knowledge inference case in order to estimate the probabilistic error analysis based on outlier prospect and the knowledge analytic precision based on the root mean square error prospect. The analysis and discussion suggest implementing an outlier analytic mechanism to increase CORA-framework accuracy with estimating the error prediction outcome.

IoT (internet of things), context and rule specification, outlier analytic, IoT knowledge analytic, cloud

[1] Mishra, Nilamadhab, Chung-Chih Lin, and Hsien-Tsung Chang. "A Cognitive Oriented Framework for IoT Big-data Management Prospective."Communication Problem-Solving (ICCP), 2014 IEEE International Conference on. IEEE, 2014.
[2] S.J. Nasti, M. Asgar, M.A. Butt , "Analysis of Customer Behaviour using Modern Data Mining Techniques", International Journal of Computer Sciences and Engineering, Vol.5, Issue.12, pp.64-66, 2017.
[3] Zarko, Ivana Podnar, et al. "IoT data management methods and optimisation algorithms for mobile publish/subscribe services in cloud Environment. “Networks and Communications (EuCNC), 2014 European Conference on. IEEE, 2014.
[4] Gubbi, Jayavardhana, et al. "Internet of Things (IoT): A vision, architectural elements, and future directions." Future Generation Computer Systems 29.7 (2013): 1645-1660.
[5] Anantharam, Pramod, Payam Barnaghi, and Amit Sheth. "Data Processing and Semantics for Advanced Internet of Things (IoT) Applications: modeling, annotation, integration, and perception." Proceedings of the 3rd International Conference on Web Intelligence, Mining and Semantics. ACM, 2013.
[6] Mishra, Nilamadhab, Hsien-Tsung Chang, and Chung-Chih Lin. "An IoT Knowledge Re-engineering Framework for Semantic Knowledge Analytics for BI-services." Mathematical problems in engineering, vol. 2015, Article id-759425, 12 pages (2015).
[7] Dagnino, Aldo, and David Cox. "Industrial Analytics to Discover Knowledge from Instrumented Networked Machines." Proceedings of the 26th International Conference on Software Engineering and Knowledge Engineering (SEKE’14), Vancouver, Canada. 2014.
[8] Chang, H. T., Mishra, N., & Lin, C. C., IoT big-data centred knowledge granule analytic and cluster framework for BI applications: a case base analysis. PloS one, 10(11), 2015.
[9] Mishra, N., Chang, H. T., & Lin, C. C. Sensor data distribution and knowledge inference framework for a cognitive-based distributed storage sink environment. International Journal of Sensor Networks, 26(1), 26-42,2018.
[10] Mishra N,. "In-network Distributed Analytics on Data-centric IoT Network for BI-service Applications", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN: 2456-3307, Volume 2, Issue 5, pp.547-552, September-October.2017.
[11] Patnaik, B. C., & Mishra, N. “A Review on Enhancing the Journaling File System”, Imperial Journal of Interdisciplinary Research, 2, no. 11 (2016)
[12] Chang, H. T., Yu-Wen Li., & Mishra, N. “mCAF: A Multi-dimensional Clustering Algorithm for Friends of Social Network Services”, Springer Plus, 2016.
[13] Chang, H. T., Liu, S. W., & Mishra, N. “A tracking and summarization system for online Chinese news topics”, Aslib Journal of Information Management, 67(6), 687-699,2015.
[14] Mishra, N., Lin, C. C., & Chang, H. T. “A Cognitive Adopted Framework for IoT Big-Data Management and Knowledge Discovery Prospective”, International Journal of Distributed Sensor Networks, 2015.
[15] Mishra, N., Lin, C. C., & Chang, H. T. “Cognitive inference device for activity supervision in the elderly”, The Scientific World Journal, 2014.
[16] Mishra, N., Chang, H. T., & Lin, C. C. “Data-centric Knowledge Discovery Strategy for a Safety-critical Sensor Application”, International Journal of Antennas and Propagation, Article ID 172186, 11 pages, 2014. doi:10.1155/2014/172186.