Integration of SQL Modelling and Graph Representations to Disaggregated Human Activity Data for Effective Knowledge Extraction

Abstract

With high migration of technology to smart living attributes such as smart homes, smart devices, automatic appliances, and activity trackers, and etc, the data processing and analysing are much needed to get the high outcomes with less power usage and clear understanding of usage information. For this multiple author were proposed different ways and even we proposed an effective disaggregated data modelling for behavioural analytics using distributed architectures. Where implementing distributed architecture is first time in the industry, our model has lot of advantages including, high availability, security to data stored and can achieve high speed of huge number data storage and processing with easy integration of open source technologies. In this paper, we are implementing a model for activity labelling based on human actions and enhancing our earlier research model with interfacing the SQL models like Apache Hive and Google Big Query for easy processing with simples queries and making processing and analysing to reach more users with less efforts along with development of effective pictorial representations of resultant data with graph models built by PHP libraries.