A Survey on Real Time Data Analysis from Sensors Using R Programming Techniques
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Health care is a vast ecosystem where automation becomes inevitable. Development of Internet of Things (IoT) in healthcare has drastically changed the conventional model of working towards digital expansion. Transformation of lifestyle has also made a general shift in care from hospital environments to private environments like patient’s home. Nowadays, society prefers personalized care and experience towards them for satisfaction along with preservation of privacy. Healthcare data are broadly classified into numerous fields like personal data, Pharmaceutical data, Clinical data etc. This survey paper focuses on obtaining raw information from various sensors and performs data analysis techniques for inferring knowledge about patient’s data in real time. All these data obtained from the sensors are analyzed for knowledge inference where clustering and classification tends to be useful. In clustering, k-means algorithm is used because of its ability to produce uniform clusters irrespective of the input size and classify the resultant sets using naive Bayes classifiers. Security of data is also improved by using Cloud Storage with Attribute Based Encryption technique. The aim of this paper is to produce more accuracy and higher level of privacy data sets based on comparison.
Akanksha Kapoor, Abhishek Singhal, “A Comparative Study of K-Means, K-Means++ and Fuzzy C- Means Clustering Algorithms”, 3rd IEEE International Conference on "Computational Intelligence and Communication Technology", IEEE-CICT 2017
K. Emura, A. Miyaji, A. Nomura, K. Omote, and M. Soshi, “A ciphertext-policy attribute-based encryption scheme with constant ciphertext length,” in International Conference on Information Security Practice and Experience. Springer, 2009, pp. 13–23
B.Fung, K. Wang, R. Chen, and P. Yu, “Privacy Preserving DataPublishing: A Survey of Recent Developments,” ACM Computing Surveys, 2010
S. Ghosh, S.K. Dubey, “Comparative Analysis of K-Means and Fuzzy C-Means Algorithms” in International Journal of Advanced Computer Science and Applications, Vol. 4, 2013:pp. 35-39
A. Gupta ; H. Shivhare ; S. Sharma, “Recommender system using fuzzy c-means clustering and genetic algorithm based weighted similarity measure” in International Conference on Computer, Communication & Control,2015:pp 1-8
Helger Lipmaa,” Cryptographic Techniques in Privacy Preserving Data Mining”, University College London, Estonian Tutorial 2007
K.M. Kumar, Dr. A. R.M. Reddy, “A Fast K-Means Clustering Using Prototypes for Initial Cluster Center Selection”, IEEE 9th International Conference on Intelligent Systems and Control (ISCO), 2015
Lan Zhou, Vijay Varadharajan, K. Gopinath ,“Secure Role-Based Cloud Storage System For Encrypted Patient-Centric Health Records”, The Computer Journal, Volume 59, 3 November 2016
K. Lin, X.Li, J. Chen, Z. Zhang, “A K-means Clustering with Optimized Initial Center Based on Hadoop Platform” in The 9th International Conference on Computer Science & Education, 2014:pp. 263-266
X. Liu, H. Zhu, J. Ma, J. Ma, and S. Ma, “Key-policy weighted attribute based encryption for fine-grained access control,” in Communications Workshops (ICC), 2014 IEEE International Conference on. IEEE, 2014, pp. 694–699
Z. Min, Kai-fei, “Improved research to k-means initial cluster centers” in Ninth International Conference on Frontier of Computer Science and Technology, 2015, pp. 349-353
S.M. Riazul Islam1, (Member, IEEE), Daehan Kwak2, MD. Humaun Kabir1, Mahmud Hossain3, AND Kyung-Sup Kwak1, (Member, IEEE), “The Internet of Things for Health Care: A Comprehensive Survey”, 2169-3536 2015 IEEE.
Siddhesh Mhatre, Ananth Nimkar, “Comparative Study on Attribute-Based Encryption for Health Recordsin Cloud Storage”, 10.1109/RTEICT.2017.8256677, IEEE,15 January 2018
P. Suganthi, K. Kala, C. Balasubramanian, “Using K-Means Clustering Algorithm for Handling Data Precision”, IEEE, 10.1109/ICCTIDE.2016.7725374, 31 October 2016
M. Yedla, S. R. Pathakota, T M Srinivasa, “Enhancing K-means Clustering Algorithm with Improved Initial Center” in International Journal of Computer Science and Information Technologies, Vol. 1 (2), 2010:pp. 121-125
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