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.
Itocon aggregates the sensing data from various sensors deployed around the target bus stops, and calculate and visualize the congestion degrees in real-time. Itocon is developed as a web application to avoid requesting the application install. We hope all the people who use a bus change their moving time based on the congestion information for avoiding human crowds. We explain the details and the future prospects of Itocon.
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Cross Ref
- Ramesh Nagarajan. [n.d.]. Get Around Safely with These New Google Maps Features. https://www.blog.google/products/maps/get-around-safely-these-new-google-maps-featuresGoogle Scholar
- Atsushi Shimada, Kaito Oka, Masaki Igarashi, and Rin-ichiro Taniguchi. 2017. Congestion Analysis Across Locations Based on Wi-Fi Signal Sensing. In Proc. Int. Conf. Pattern Recognition Applications and Methods. Springer, 204--221.Google Scholar
- Ryo Takahashi, Shigemi Ishida, Akira Fukuda, Tomoki Murakami, and Shinya Otsuki. 2019. DNN-Based Outdoor NLOS Human Detection Using IEEE802.11ac WLAN Signal. In Proc. IEEE SENSORS 2019. 1--4.Google Scholar
Index Terms
Itocon - a system for visualizing the congestion of bus stops around Ito campus in real-time: poster abstract
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