Teógenes Moura, G. B. Kalejaiye, Henrique R. Orefice, Matheus Bafutto, Marcelo M. Carvalho
{"title":"发展中地区的社会感知:公交车到达时间预测的挑战","authors":"Teógenes Moura, G. B. Kalejaiye, Henrique R. Orefice, Matheus Bafutto, Marcelo M. Carvalho","doi":"10.1145/3055601.3055622","DOIUrl":null,"url":null,"abstract":"The design of crowdsourcing applications to supplement public transportation information systems have generally assumed availability of high-speed Internet connection coupled with high data sampling and gathering via data-hungry application interfaces. But, in developing regions, low-income users generally avoid the use of data-intensive applications over the Internet connection provided by their mobile operator. Such restriction imposes key constraints and challenges on the design of social sensing applications targetted at low-income communities. In particular, the design of crowdsourcing applications for bus arrival time prediction in developing regions should seek high accurate prediction based on minimal data gathering and infrequent data sampling.","PeriodicalId":360957,"journal":{"name":"Proceedings of the 2nd International Workshop on Social Sensing","volume":"124 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Social Sensing in Developing Regions: Challenges for Bus Arrival Time Prediction\",\"authors\":\"Teógenes Moura, G. B. Kalejaiye, Henrique R. Orefice, Matheus Bafutto, Marcelo M. Carvalho\",\"doi\":\"10.1145/3055601.3055622\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The design of crowdsourcing applications to supplement public transportation information systems have generally assumed availability of high-speed Internet connection coupled with high data sampling and gathering via data-hungry application interfaces. But, in developing regions, low-income users generally avoid the use of data-intensive applications over the Internet connection provided by their mobile operator. Such restriction imposes key constraints and challenges on the design of social sensing applications targetted at low-income communities. In particular, the design of crowdsourcing applications for bus arrival time prediction in developing regions should seek high accurate prediction based on minimal data gathering and infrequent data sampling.\",\"PeriodicalId\":360957,\"journal\":{\"name\":\"Proceedings of the 2nd International Workshop on Social Sensing\",\"volume\":\"124 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-04-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2nd International Workshop on Social Sensing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3055601.3055622\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2nd International Workshop on Social Sensing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3055601.3055622","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Social Sensing in Developing Regions: Challenges for Bus Arrival Time Prediction
The design of crowdsourcing applications to supplement public transportation information systems have generally assumed availability of high-speed Internet connection coupled with high data sampling and gathering via data-hungry application interfaces. But, in developing regions, low-income users generally avoid the use of data-intensive applications over the Internet connection provided by their mobile operator. Such restriction imposes key constraints and challenges on the design of social sensing applications targetted at low-income communities. In particular, the design of crowdsourcing applications for bus arrival time prediction in developing regions should seek high accurate prediction based on minimal data gathering and infrequent data sampling.