| 研究課題/領域番号 |
18K11255
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| 研究機関 | 東京大学 |
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研究代表者 |
杜 平 東京大学, 大学院情報学環・学際情報学府, 特任准教授 (10462912)
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| 研究期間 (年度) |
2018-04-01 – 2022-03-31
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| キーワード | Internet-of-Things (IoT) / 3C Sensing / Context-aware / Privacy-Preserving |
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| 研究実績の概要 |
In the third fiscal year, we focus on developing context-aware IoT system on campus for population estimation to slow the spread of COVID-19. We design and deploy sensors and base stations at specific locations to monitor the communication from nearly devices installed COCOA App and count the number of devices to estimate the population density.
Totally, we have deployed more than 200 sensors and 30 base stations in the classrooms, libraries, and cafeterias on four campuses in the University of Tokyo. Our web service of the population estimation has about 1000 page views per day. The feedback shows the service is highly-evaluated by students and administration. Moreover, we have been invited to deploy our 3C systems in business facilities. The details of our 3C sensing system have been written as a manuscript "Privacy-Preserving BLE Scanning for Population Estimation to Mitigate the Spread of COVID-19”, which has been submitted to Globecom 2021.
Currently, the 3C sensors are added afterwards, but it should be assumed that the infrastructure itself can detect population density in the 5G area. We have also done some research in the 5G network slicing that is assumed to support IoT in a 5G slicing. The results have been published as two international conference papers and one technical report.
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| 現在までの達成度 (区分) |
現在までの達成度 (区分)
2: おおむね順調に進展している
理由
We have done more development work and more publication than listed in our proposal. Our work has been highly evaluated by industry and academics.
Our context-aware IoT system has a strong practical value in helping people to monitor the “new lifestyle” when people are gradually returning to the office instead of working at home. We design and deploy 3C BLE-Lora sensors and Lora-LTE base stations to monitor the communication from nearly devices installed COCOA App and count the num- ber of devices to estimate the population density. Deploying 3C sensors requires more important aspects than technology to be classified, such as consensus building and compatibility of privacy and anonymity. Totally, we have deployed more than 200 sensors and 30 base stations in the classrooms, libraries, and cafeterias on four campuses in the University of Tokyo. Our web service of the population estimation has about 1000 page views per day. The feedback shows the service is highly-evaluated by students who are gradually back to school. Moreover, we have also been invited and deployed 3C sensors in multiple business facilities.
In academic research, we have published 2 international conference papers, and 2 technical reports in this fiscal year. And one paper is under review.
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| 今後の研究の推進方策 |
In the future, we will focus on promoting our system to more areas and provide more services to help people avoid densely areas. Since we will coexist with COVID-19 for quite a long time especially in developing countries, we hope that our research provides a cost-effective solution for population density monitoring without sacrificing privacy. Moreover, we will try to integrate our 3C systems into our Local 5G box, where the Local 5G infrastructure itself can detect population density itself.
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| 次年度使用額が生じた理由 |
Due to the pandemic of COVID-19, we cannot go to aboard to attend the international conference as planned. We have just submitted our submission about our IoT system to an international conference and we need fund support to attend it. We plan to submit more papers about our 3C sensing IoT system.
We plan to continue providing the 3C sensing service running on campus in the University of Tokyo. The ongoing IoT lifestyle monitoring (3C sensing) system needs the continued fund support to maintain and improve it.
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