Title :
Buy4Me: A Delivery System via Mobility Prediction Based on Mobile Crowd Sensing
Author :
Yichu Qu;Zhiyong Yu;Xianghan Zheng
Author_Institution :
Coll. of Math. &
Abstract :
With the prevalent development of rich sensor-equipped smart phones, mobile crowd sensing becomes a new sensing paradigm beyond traditional sensor networks. In this paper we propose and develop Buy4Me, a delivery system based on mobile crowd sensing. It can be used in different scales, such as a university campus or a city, to make shopping and delivering more convenient. When you need something not near, Buy4Me can recommend a friend to bring it for you without extra work. Users´ mobility histories are analyzed to predict where a user will visit, and whether she will encounter with the others. Then Buy4Me ranks friends by the probability of whether they completing the delivering task, and returns top-k friends. We evaluate the method with the dataset contributed by Microsoft Research Asia, and find that it can achieve acceptable recommendation accuracy.
Keywords :
"Trajectory","Sensors","Global Positioning System","Clustering algorithms","Mobile communication","Urban areas","Prediction algorithms"
Conference_Titel :
Ubiquitous Intelligence and Computing and 2015 IEEE 12th Intl Conf on Autonomic and Trusted Computing and 2015 IEEE 15th Intl Conf on Scalable Computing and Communications and Its Associated Workshops (UIC-ATC-ScalCom), 2015 IEEE 12th Intl Conf on
DOI :
10.1109/UIC-ATC-ScalCom-CBDCom-IoP.2015.218