Reliability of Smart-Wearables using PSO-GA Optimized Algorithm in Terms of Data Analysis

Abstract

Rapid advancement in the smart-wearable industry has increased the importance of modeling the relationship between the raw data captured by the devices and the useful information obtained by analyzing using a metaheuristic approach. In this paper, a new model to cater to the user-end experience based on the PSO-GA optimized ANFIS approach is proposed. PSO-GA consists of alternating phases of Genetic Algorithm and Particle Swarm Optimization. The proposed model aims at minimizing the function, under dynamic changes while in constant interaction of the fitness-tracker with the human body.