S. Chaudhary, Tanjot Kaur, N. Aggarwal, B. Raman, D. Bansal, K. Ramakrishnan
{"title":"Bus boarding event detection using smartphone sensors","authors":"S. Chaudhary, Tanjot Kaur, N. Aggarwal, B. Raman, D. Bansal, K. Ramakrishnan","doi":"10.1109/COMSNETS.2016.7439930","DOIUrl":null,"url":null,"abstract":"Rapid growth in smartphones industries has made smartphones omnipresent. The incorporation of a number of powerful sensors in the smartphones lately have enhanced their applicability besides their customary use for communications. Sensors in smartphones can be used to detect users activities and localization. But use of all sensors put a lot of burden on smartphone battery. Battery drainage is a big problem and most commuters do not prefer to use power hungry sensors such as GPS. In this paper, we explored the possibility to use the low power smartphone sensors to detect the initial movement of users such as bus boarding movement which can act as a trigger to collect data from other sensors. The proposed approach is implemented as an android app and consists of two modules. First module is based on accelerometer sensors to detect initial staircase pattern movement of user and triggers the second module. Second module detects linear acceleration of user in one direction and movement of bus using accelerometer and GSM sensors. Various experiments are conducted to find the appropriate features to characterize the bus boarding event. Based on these features a scaled training model is generated. This model is deployed along with the Android application to perform event detection on the smartphone itself. We conducted experiments using five different phones and found promising results of detecting the event.","PeriodicalId":185861,"journal":{"name":"2016 8th International Conference on Communication Systems and Networks (COMSNETS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 8th International Conference on Communication Systems and Networks (COMSNETS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COMSNETS.2016.7439930","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Rapid growth in smartphones industries has made smartphones omnipresent. The incorporation of a number of powerful sensors in the smartphones lately have enhanced their applicability besides their customary use for communications. Sensors in smartphones can be used to detect users activities and localization. But use of all sensors put a lot of burden on smartphone battery. Battery drainage is a big problem and most commuters do not prefer to use power hungry sensors such as GPS. In this paper, we explored the possibility to use the low power smartphone sensors to detect the initial movement of users such as bus boarding movement which can act as a trigger to collect data from other sensors. The proposed approach is implemented as an android app and consists of two modules. First module is based on accelerometer sensors to detect initial staircase pattern movement of user and triggers the second module. Second module detects linear acceleration of user in one direction and movement of bus using accelerometer and GSM sensors. Various experiments are conducted to find the appropriate features to characterize the bus boarding event. Based on these features a scaled training model is generated. This model is deployed along with the Android application to perform event detection on the smartphone itself. We conducted experiments using five different phones and found promising results of detecting the event.