NDLI: Predicting critical conditions in bicycle sharing systems

Content Provider	Springer Nature Link
Author	Cerquitelli, Tania Chiusa, Silvia Xiao, Xin Cagliero, Luca Garza, Paolo
Copyright Year	2016
Abstract	Bicycle sharing systems are eco-friendly transportation systems that have found wide application in Smart urban environments. Monitoring and analyzing the occupancy levels of the system’s stations is crucial for guaranteeing the quality of the offered service. Advanced data mining solutions tailored to bicycle sharing data analysis are needed to support system managers to react to critical situations (e.g., lack of parked bicycles at a station) that can yield service disruption. This paper presents STation Occupancy Predictor (STOP), a data mining framework to predicting the occupancy levels (i.e., critical or non-critical) of the stations in the near future through Bayesian and associative classifiers. The prediction is made based on the current and past station occupancy values and on the temporal information associated with the predicted time instant. A classification model per station is generated on the collected data to support domain experts in understanding the underlying events. The model allows predicting short-term station occupancy levels and characterizing system usage to support planning maintenance activities in the medium term as well. As a case study, STOP has been thoroughly evaluated on real data acquired from the bicycle sharing system of New York City. The results demonstrate the effectiveness of the STOP system.
Ending Page	57
Page Count	19
Starting Page	39
File Format	PDF
ISSN	0010485X
e-ISSN	14365057
Journal	Computing
Issue Number	1
Volume Number	99
Language	English
Publisher	Springer Vienna
Publisher Date	2016-07-01
Publisher Place	Vienna
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Information Systems Applications (incl.Internet) Software Engineering Bike sharing system Computer Application in Administrative Data Processing Classification Computer Science Artificial Intelligence (incl. Robotics) Urban data mining Computer Communication Networks Information systems (hypertext navigation, interfaces, decision support, etc.)
Content Type	Text
Resource Type	Article
Subject	Theoretical Computer Science Computational Theory and Mathematics Computational Mathematics Numerical Analysis Computer Science Applications Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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