Analysis of social interaction, crowd density and mobility pattern using smartphone sensing

Abstract

The smartphone has become an important part of human life and with their in-tegrated sensor ecosystem, they offer a practical platform for analyzing humanbehavioral patterns. Traditionally, studies done till now in this domain have em-ployed dedicated hardware or regular questionnaires to study human behaviors.In order to better understand the psychology and behavior of college students, re-searchers have used the smartphone as a measurement tool. As college life can bea transition period for any student with respect to psychology and behavior. Us-ing embedded sensors included in standard smartphones, we can leverage thesecapabilities to track social interactions and examine students� social context andnetwork strength.A significant rise has been observed in research interest in crowd behavioranalysis and crowd density estimation, due to its crucial significance in ensuringthe seamless management of events. Indoor localization helps people in navi-gating in indoor spaces. But the wealth of information regarding user�s locationinference is not being used in an efficient manner that is present with the serversof indoor localization architecture. So here we propose a method of extendingindoor localization through Wi-Fi Connectivity information with the combinationof smartphones. We implemented an in-house app, Usage Tracker, that will auto-matically collect data from its built-in sensors to analyze continuous sensing datafrom 35 students of our institute for 5 weeks. After that preprocessing and algo-rithms were applied to infer crowd estimation-related information and individualuser-level social behavior analysis were carried out.