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A Survey on Real Time Data Analysis from Sensors Using R Programming Techniques

S. Keerthana1, K. Manish2, R. Shwetha3, S. Kayalvizhi4, S. Kalpana Devi5

 DOI : https://dx.doi.org/10.18535/rajar/v4i3.05

 Author's Affiliations

1,2,3UG Student, Computer Science and Engineering, Easwari Engineering College, Chennai, India

4 Professor ,Computer Science Department, Easwari Engineering College, Chennai, India

5 Assistant Professor, Computer Science Department, Easwari Engineering College, Chennai, India


 

ABSTRACT

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.