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Masanori Futamata

dblp:279/2792 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Smart cities and intelligent transportation · 100%
Computer graphics and multimedia
1 paper
Visualization and visual analytics · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Smart cities and intelligent transportation
public transit
0.412020
Itocon - a system for visualizing the congestion of bus stops around Ito campus in real-time: poster abstract · SenSys 2020
Visualization and visual analytics › interactive visualization
real-time visualization
0.112020
Itocon - a system for visualizing the congestion of bus stops around Ito campus in real-time: poster abstract · SenSys 2020
YearPublicationVenuePosition
2020 Itocon - a system for visualizing the congestion of bus stops around Ito campus in real-time: poster abstract
abstract
Due to the spread of COVID-19, we are desired to avoid crowded places including public transportation. Kyushu University has the largest campus in Japan, called "Ito campus", and the population there is about 20,000 in which 23% of students and 46% of staff use a bus for reaching the campus. The lectures in the first half of 2020 have been conducted online, but we plan to resume face-to-face lectures gradually. At that time, we expect the bus stops and buses to be crowded, especially during rush hour. In this paper, we introduce a system, called Itocon, to visualize the human congestion of bus stops around the campus.
Ryo Takahashi 0001, Kenta Hayashi, Yudai Mitsukude, Masanori Futamata, Shunei Inoue, Shuta Matsuo, Shigemi Ishida, Yutaka Arakawa, Shigeru Takano
SenSys4