IWIN2024にて戸川さんと加藤さんの2名が発表してきました．
戸川さんはこの発表で「IWIN2024 Excellent Paper Award」を受賞しました

戸川「A Proposal of Smartphone Beacons in Stay Estimation System using BLE」

発表概要

People spend 88.9% of their day indoors and are mainly active indoors in physically separated spaces such as their own rooms, laboratories, and conference rooms. Therefore, room-level location information, rather than highly accurate location information, is also valuable. We have proposed a stay estimation system that receives signals from BLE beacons carried by each user and estimates the room location using receivers installed in the environment. However, conventional methods using only physical beacons have problems such as battery replacement, time-consuming initial setup, and users moving from room to room without a physical beacon. In this study, we implement and evaluate smartphone beacons that have high tracking performance, do not require initial setup or battery replacement, and consumes little battery power. Smartphones are often carried around at all times, so they are considered to be highly trackable. We implemented an application that automatically sets the content of physical beacon advertisements and continues to advertise BLE signals periodically. In evaluation experiments, the application was found to have high tracking performance and low battery consumption.

報告と感想

M1の戸川浩汰です。 今回初めての英語発表でした。 質疑応答ももちろん英語で行われかつ15分と長めでしたのでとても不安でした。しかし、発表原稿を覚えていたおかげでよく使う文法や単語が頭に入っていたのでなんとか切り抜けることができました。また、他の発表にも何回か英語で質問できたのでよかったかなと思います。 さらに、賞をいただけたことはとても嬉しく今後の研究に対する大きなモチベーションとなりました。これからもより一層研究に励みたいと思います。

加藤「A Study of Web System for Comparison and Analysis of Cooking Actions Based on Activity Sensing」

発表概要

There are various methods for sharing cooking recipes. Consequently, systems that allow users to share their impressions of the outcome and taste through photos and text have become widespread. However, there is no mechanism for comparing cooking actions with others or with one’s past self. This study aims to realize a system that allows users to share and compare cooking actions, enabling self-analysis and reflection through the visualization of actions during cooking. We extracted features related to stationary actions and movements between fixed points. For station aryactions, specifically cucumber slicing, we obtained the average pace, average acceleration, and the standard deviation of acceleration. For movements between fixed points, focusing on hamburger steak preparation, we extracted features such as dwell time and location transitions. We investigated whether self-analysis could be conducted and whether there were any changes in cooking skills through the comparison of cooking actions using graph displays. As a result, while the graphical display prompted self-analysis and led to a change in awareness, no growth trend was observed with a displaying only once.

報告と感想

M1の加藤風真です．今回の発表は初めての英語発表でした． 国際発表なので論文・スライド・発表原稿の全ての作成において大変でしたが，無事発表を終えられて安心しています． 質疑応答では自分の英語力の無さから回答が難しい部分があり，今後の課題となりました． これからも，今回の経験を活かして研究を進めたいと思います．