9:00 - 10:30 Introduction
+ Paper presentation 1: Urban living (papers 1.1 - 1.2)
10:30 - 11:00 Coffee break
1
11:00 - 12:00 Paper
presentation 2: Urban living (papers
1.3 - 1.6)
12:00 - 13:30 Lunch break
13:30 - 15:00 Paper
presentation 3: Urban mobility (papers
2.1 - 2.4)
15:00 - 15:30 Coffee break
2
15:30 - 16:30 Keynote talk
16:30 - 17:00 Best Paper
Award + Wrap-up
Urban Living
1.1
Seamless Internet connectivity
for ubiquitous communication. Ryo Yanagida (University of St
Andrews) and Saleem Bhatti (University of St Andrews). [
pdf]
1.2
iCoff: Towards Building an
Intelligent Coffee Plate System to Enhance Coffee Shop’s Customer
Experience. Thanakrit Jitapinyakul (Chiang Mai University),
Panuwat Phunsuk (Chiang Mai University) and Santi Phithakkitnukoon
(Chiang Mai University). [
pdf]
1.3
Designing
interactive interfaces
by keeping the natural beauty of public places. Linda Hirsch
(Ludwig-Maximilian University). [
pdf]
1.4
Inferring the Character of Urban
Commercial Areas from Age-biased Online Search Results. David
Lee (Korea Advanced Institute of Science and Technology) and Seolha Lee
(Seoul National University). [
pdf]
1.5
Safe Street Rangers:
Crowdsourcing Approach for Monitoring and Reportng Street Safety.
Peerawit Naprae (Chiang Mai University), Panurat Sutigoolabud (Chiang
Mai University) and Santi Phithakkitnukoon (Chiang Mai University). [
pdf]
1.6
An IoT and Blockchain-based
Approach for Ensuring Transparency and Accountability in Regulatory
Compliance. Niaz Chowdhury (The Open University). [
pdf]
Urban Mobility
2.1
Deep Learning Models for
Population Flow Generation from Aggregated Mobility Data. Can
Rong (Peking University), Jie Feng (Tsinghua University) and Yong Li
(Tsinghua University). [
pdf]
2.2
How to get in Touch with the
Passenger: Context-Aware Choices of Output Modality in Smart Public
Transport. Christine Keller (Hochschule Karlsruhe, University
of Applied Sciences) and Thomas Schlegel (Hochschule Karlsruhe). [
pdf]
2.3
A Vision-based Deep On-Device
Intelligent Bus Stop Recognition System. Gautham Krishna Gudur
(Ericsson), Ateendra Ramesh (SUNY at Buffalo) and Srinivasan R (SSN
College of Engineering). [
pdf]
2.4
Detecting Abnormal Behavior in
the Transportation Planning using Long
Short Term Memories and a Contextualized Dynamic Threshold. Thananut
Phiboonbanakit (Sirindhorn International Institute of Technology),
Van-Nam Huynh (Japan Advanced Institute of Science and Technology),
Teerayut Horanont (Sirindhorn International Institute of Technology)
and Thepchai Supnithi (National Science and Technology Development). [
pdf]
Keynote Talk
[TBA]