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"I-Care" - Big-data Analytics for Intelligent Systems

A very novel predicament for quantitative data science has been generated by the abundance of large, well-cured data sets in biological and social science, coupled with an extraordinary increase in computational ability. This is the possibility of sophisticated studies combined with remedial understanding. Analytics for intelligent systems should cover architecture of hardware platforms and application of software methods, technique and tools. It is anticipated that adapting dynamic memory information, processing parametric values of large data sheets with optimization, would be faster. The field of Big-Data Analytics under recent trends of Data Science studies various means of pre-processing, analyzing and filtering from huge and semi-structured data sets from different sources which are complex to be handled by traditional data processing systems. In addition to extracting and aggregating data from various main performance measures, this proposal also forecasts potential values for these KPIs (Key Performance Indicators) and alerts them when unfavorable values are about to occur. As AI and ML are implemented through different platforms and sectors including chat-bots, robotics, social media, healthcare, self-driven automobile and space exploration, large companies are investing in these fields, and the demand for ML and AI experts is growing accordingly. Python is becoming the most popular language for AI (Artificial Intelligence and Machine Learning) due to its rich supported tools. This proposed applications "I-Care" (Intelligent Care) provide recommendations to improve Quality of Service of Big-data analytics. So, the proposed paper examines the methodology and requirements, architecture, modeling and analytics with implementation and describes the architectural design and the results obtained by the pilot application using Python and its powerful tools like Pandas and Scikit-Learn.