9:00 - 10:00 Introduction
+ Paper presentations: Transport (1.1,
1.2)
10:00 - 10:30 Coffee break
1
10:30 - 12:00 Paper
presentations: Urban living (2.1,
2.2, 2.3)
12:00 - 13:30 Lunch break
13:30 - 15:00 Paper
presentations: Crowdsensing
(3.1, 3.2, 3.3, 3.4)
15:00 - 15:30 Coffee break
2
15:30 - 16:30 Keynote: Urban Analytics through the Lens
of Crowdsourced Data (Prof.
Cecilia Mascolo, University of Cambridge, UK)
16:30 - 17:00 Best Paper
Award + Wrap-up
1. Transport:
1.1 Predicting Taxi Pickups in Cities: Which Data Sources Should We
Use? (Austin Smith:University of New Hampshire; Andrew Kun:University
of New Hampshire; John Krumm:Microsoft Research) [
pdf]
1.3 GTFS-Viz: Tool for Preprocessing and Visualizing GTFS Data (Mudtana
Worapun:Chiang Mai University; Narumon Kunama:Chiang Mai University;
Santi Phithakkitnukoon:Chiang Mai University; Merkebe
Demissie:University of Calgary) [
pdf]
2. Urban living:
2.1 Smart Urban Planning using Big Data Analytics based Internet of
Things (Muhammad Babar:National University of Sciences and Technology;
Fahim Arif:National University of Sciences and Technology) [
pdf]
2.2 TweetCount: Urban Insights by Counting Tweets (John Krumm:Microsoft
Research; Andrew Kun:University of New Hampshire; Petra
Varsanyi:University of New Hampshire) [
pdf]
2.3 TripRec: Trip Plan Recommendation System that Enhances Hotel
Services (Nonnadda Silamai:Chiang Mai University; Narongchai
Khamchuen:Chiang Mai University; Santi Phithakkitnukoon:Chiang Mai
University) [
pdf]
3. Crowdsensing
3.1 How does coffee shop get crowded?: Using WiFi footprints to deliver
insights into the success of promotion (Pichaya Prasertsung:Sirindhorn
International Institute of Technology; Teerayut Horanont:Sirindhorn
International Institute of Technology) [
pdf]
3.2 Mining Crowd Mobility and WiFi Hotspots on a Densely-populated
Campus (Mengyu Zhou:Tsinghua University; Kaixin Sui:Tsinghua
University; Dan Pei:Tsinghua University; Thomas Moscibroda:Microsoft
Research) [
pdf]
3.3 Lessons Learned Using Wi-Fi and Bluetooth as Means to Monitor
Public Service Usage (Lu Bai:University of Sheffield;Neil
Ireson:University of Sheffield;Suvodeep Mazumdar:University of
Sheffield;Fabio Ciravegna:University of Sheffield) [
pdf]
3.4 Wi-Crowd: Sensing and Visualizing Crowd on Campus using Wi-Fi
Access Point Data (Adiporl Binthaisong:Chiang Mai University;Jaruwan
Srichan:Chiang Mai University;Santi Phithakkitnukoon:Chiang Mai
University) [
pdf]
Keynote Speaker