研究業績リスト
その他
Building Digital Scent Technology Based on Odor Reproduction
作成日時 08/2025–03/2030
Offer Organization: Japan Science and Technology Agency, System Name: Future Society Creation Project, Category: -, Fund Type: -, Overall Grant Amount: - (direct: -, indirect: -)
その他
Advancement of Olfactory Interface Technologies: Automatic Content Creation Using AI
作成日時 04/2022–03/2025
Offer Organization: Japan Society for the Promotion of Science, System Name: Grants-in-Aid for Scientific Research Grant-in-Aid for Scientific Research (C), Category: Grant-in-Aid for Scientific Research (C), Fund Type: -, Overall Grant Amount: - (direct: 3300000, indirect: 990000)
その他
作成日時 04/2019–03/2022
Offer Organization: Japan Society for the Promotion of Science, System Name: Grants-in-Aid for Scientific Research Grant-in-Aid for Early-Career Scientists, Category: Grant-in-Aid for Early-Career Scientists, Fund Type: -, Overall Grant Amount: - (direct: 3200000, indirect: 960000)
Toward establishment of olfactory augmentation technologies as a new modality of human augmentation, we have developed several types of olfactory modulators in this research project. By collecting odor molecules wafting in the air onto the adsorbent, we can increase the concentration of the odor vapor. By presenting this concentrated odor vapor, we can make the user feel as if their olfactory sensitivity is enhanced. The mixing ratio of odor molecules can be modulated by using adsorbents having affinities to different classes of odor molecules. Olfactory perception can be also modulated by presenting thermal and/or wind stimuli to the user even if the same odor is presented. We have fabricated the prototype systems of these olfactory modulators and have experimentally shown their feasibility.
その他
作成日時 04/2019–03/2022
Offer Organization: Japan Society for the Promotion of Science, System Name: Grants-in-Aid for Scientific Research Grant-in-Aid for Scientific Research (B), Category: Grant-in-Aid for Scientific Research (B), Fund Type: -, Overall Grant Amount: - (direct: 13400000, indirect: 4020000)
Landfill sites are large sources of greenhouse gases including methane produced through biological decomposition of organic waste. In this research project, we have developed elemental technologies toward realizing drones that can detect such greenhouse gases and autonomously locate their sources. In order to detect a gas source on the ground, we have proposed to utilize the airflow field produced by a multi-rotor drone hovering at a low altitude. Experimental results have shown that gas puffs wafting near the ground can be effectively collected to the gas sensor onboard the drone using the airflow produced by its rotors. To realize small infrared gas sensors that fit on a drone, we have developed a miniaturized infrared light emitter by using MEMS technologies. We also have succeeded in high-precision gas-source localization using particle filters and super-resolution gas-distribution measurement using deep learning.
その他
An Exploration of Primary Odors That Enables Reproduction of Arbitrary Odors
作成日時 06/2017–03/2019
Offer Organization: Japan Society for the Promotion of Science, System Name: Grants-in-Aid for Scientific Research Grant-in-Aid for Challenging Research (Exploratory), Category: Grant-in-Aid for Challenging Research (Exploratory), Fund Type: -, Overall Grant Amount: - (direct: 4900000, indirect: 1470000)
In this research project, fundamental investigations have been conducted toward the development of devices that can reproduce arbitrarily specified smells and present them to the user. In the proposed system, a mixture of various odorant vapors is generated, and its smell is examined by using an electronic nose system. Thus, the process of exploring the appropriate vapor mixing ratios to reproduce the desired smell is automated. When odorants with low volatility are used, sufficiently strong smell cannot always be generated. Therefore, an odor concentrator device has also been developed.
その他
作成日時 2017–2018
Offer Organization: 科学技術振興機構, System Name: 戦略的な研究開発の推進 戦略的創造研究推進事業 ACT-I, Category: -, Fund Type: -, Overall Grant Amount: - (direct: -, indirect: -)
ガスの挙動は、移流拡散方程式などの非線形方程式に従うため、これを逆解析してガスの発生箇所や発生濃度を推定するのは困難です。そこで、現実環境における測定で得られたデータを基に機械学習を行い、限られた測定点におけるデータからケミカルシグナルフローの逆解析を可能にし、詳細なガス発生量マップの推定を可能にします。本研究は、地雷の自動探索や、ゴミ埋立地の有害ガスモニタリングなどへの応用が期待されます。