Nishi, Hiroaki

写真a

Affiliation

Faculty of Science and Technology, Department of System Design Engineering (Yagami)

Position

Professor

Related Websites

External Links

Career 【 Display / hide

  • 1999.04
    -
    2002.02

    Real World Computing Partnership

  • 2002.02
    -
    2003.03

    Hitachi, Ltd., Central Research Laboratory

  • 2003.04
    -
    2004.03

    大学助手(有期)(理工学部システムデザイン工学科)

  • 2004.04
    -
    2005.03

    専任講師(理工学部システムデザイン工学科)

  • 2010.04
    -
    2014.03

    National Institute of Informatics, Invited Associate Professor

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Academic Background 【 Display / hide

  • 1994.03

    Keio University, Faculty of Science and Engineering, 電気工学科

    University, Graduated

  • 1996.03

    Keio University, Graduate School, Division of Science and Engineering, 計算機科学専攻

    Graduate School, Completed, Master's course

  • 1999.03

    Keio University, Graduate School, Division of Science and Engineering, 計算機科学専攻

    Graduate School, Withdrawal after completion of doctoral course requirements, Doctoral course

Academic Degrees 【 Display / hide

  • 博士(工学), Keio University, 1999.12

 

Research Areas 【 Display / hide

  • Manufacturing Technology (Mechanical Engineering, Electrical and Electronic Engineering, Chemical Engineering) / Communication and network engineering (Communication/Network Engineering)

  • Social Infrastructure (Civil Engineering, Architecture, Disaster Prevention) / Social systems engineering

  • Social Infrastructure (Civil Engineering, Architecture, Disaster Prevention) / Safety engineering

  • Informatics / Computer system (Computer System Network)

Research Keywords 【 Display / hide

  • ASIC / CPLD design

  • Community/Cluster Energy Management System

  • Smart City / Smart Community

  • Internet backbone router

  • Internet backbone router or switch architecture

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Books 【 Display / hide

  • 地球とつながる暮らしのデザイン

    NISHI HIROAKIet al, 株式会社シナノ, 2016.05

    Scope: 家のエネルギーの使い方のシンフォニー(pp.227-232)

  • Smart Grid Research: Vehicular - IEEE Smart Grid Vision for Vehicular Technology: 2030 and Beyond Roadmap

    Hiroaki Nishi, Koichi Inoue, IEEE Standards Committee, 2015.06

  • Anonymization infrastructure and open data in smart sustainable cities

    Jie Chang, Lei Gu, Wei Liu, Kanae Matsui, Hiroaki Nishi and Cuijuan Xia, Approved Deliverable of ITU-T (Telecommunicatino Standardization Section of ITU) Focus Group on Smart Sustainable Cities, 2015.04

  • スマートメータ―からの情報をどう匿名化するか-電力自由化時代の個人情報の活用法- 『インプレス SmartGrid ニューズレター』2014年7月号

    NISHI HIROAKI, 株式会社インプレス, 2014.07

  • IEEE SMART GIRD VISION FOR VEHICULAR TECHNOLOGY: 2030 AND BVEYOND

    NISHI HIROAKI, IEEE Standard Association, 2014.02

    Scope: Chapter 1: Social, Economic, and Political Implications, Chapter 6 Sy stems, Operations, and Scenarios

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Papers 【 Display / hide

  • Air-Conditioning Control with Spatial Recognition Using Stereo Infrared Array Sensors

    Takayama Y., Saito S., Sakuma Y., Nishi H.

    IECON Proceedings (Industrial Electronics Conference) (IECON Proceedings (Industrial Electronics Conference))  2021-October 2021.10

    ISSN  9781665435543

     View Summary

    Depending on the location of the air conditioner and the shape of a room, air-conditioning control may be inefficient resulting in temperature imbalance. When attempting to solve this problem, it is vital to understand the spatial structure of a room (including its size and shape) and the location of air conditioners and then automatically control the airflow and direction according to the structure. However, such a method for recognizing spatial structures has not yet been established. In this paper, we propose a spatial recognition method using stereo infrared array sensors (SIRA sensors) installed in an air conditioner. Our system detects objects in the obtained thermal images and estimates their distances using triangulation. In addition, the room's size and shape are estimated based on the assumption that the room size lies within the detection range. The distances to the front and left/right walls were estimated in one-meter-wide classes. The estimation accuracy was compared using two types of IRA sensors: thermopile array sensors and thermal diode infrared sensors. Regarding the distance estimation of persons from the captured stereo thermal images, the average error rate was 12.5% for both types. The distance to each wall was estimated within a 1 m error range for the thermal diode infrared sensor. Moreover, applications of the proposed spatial recognition to air-conditioning control were demonstrated. Specifically, we propose a method to control the airflow direction and volume by considering the room's geometry. An L-shaped room was modeled and simulated. From the results, the spatial recognition reduced the unevenness in temperature by adjusting the airflow based on the room shape. These results indicate that the proposed method can be practically used for spatial recognition to efficiently improve user comfort by controlling air-conditioning based on the spatial structure and eliminating uneven temperature.

  • Time Synchronization of IEEE P1451.0 and P1451.1.6 Standard-based Sensor Networks

    Nishi H., Song E.Y., Nakamura Y., Lee K.B., Liu Y., Tsang K.F.

    IECON Proceedings (Industrial Electronics Conference) (IECON Proceedings (Industrial Electronics Conference))  2021-October 2021.10

    ISSN  9781665435543

     View Summary

    This paper introduces the time synchronization approaches to the Institute of Electrical and Electronics Engineers (IEEE) P1451.0 standard-based sensor networks for Internet of Things (IoT) applications. A time synchronization architecture of IEEE P1451.0 standard-based sensor networks is described including two-level time synchronization systems in IEEE P1451.0 and P1451.1.X standards-based wide-area network (WAN) and IEEE P1451.0 and P1451.5.X standards-based local area networks (LANs). However, this paper mainly focuses on the time synchronization approach of IEEE P1451.0 and P1451.1.6 standards-based WANs and provides two implementations of time synchronization of IEEE P1451.0 and P1451.1.6 using wireline and wireless networks with their preliminary results to verify that the time synchronization approach of IEEE P1451.1.6 functions properly. In addition, the time synchronization transducer electronic data sheets (TEDS) of P1451.1.6 is described.

  • Recommendation System for Energy Consumption Behavior Change on Residents' Response and Stress

    Takayama Y., Sakuma Y., Nishi H.

    IECON Proceedings (Industrial Electronics Conference) (IECON Proceedings (Industrial Electronics Conference))  2021-October 2021.10

    ISSN  9781665435543

     View Summary

    Home energy management system (HEMS), enabled by the development of the Internet of Things (IoT), issue behavior change recommendations to encourage residents to reduce their energy consumption. Receiving these suggestions from HEMS makes it easier for them to set specific reduction goals and raise their awareness of energy saving. This feedback will lead to effective power reduction in the household sector. However, each user has unique preferences, and uniformly generated recommendations may not be followed if they do not match the preferences of the specific user. In addition, frequent recommendations that are not aligned with their preferences may stress users and decrease their motivation to reduce energy consumption. This paper presents a practical method of making behavior change recommendations reflecting users' response rates and considering their stress. Targeting the action of opening a window, we illustrate how our system induces behavioral change. To increase the users' response rate and reduce their stress, we adjust the recommendation for each user from two perspectives. First, assuming that users open windows mainly depending on the external temperature, humidity, wind, and weather, we introduce the k-nearest neighbors (k-NN) classification using these parameters as the explanatory variables to predict the possibility that the user accepts the window-opening recommendation. Generating recommendations only when the predicted probability is high enables building a unique recommendation system considering user preferences. Second, if the recommendations are sent frequently, users may become tired of following them; this leads to a situation in which users ignore recommendations or turn off their notifications. To avoid such a situation, we propose adjusting the delivery interval according to the users' response rate. When we schedule the notification cycle, we introduce a forgetting curve, assuming that the users' stress on the recommendation decreases over time. We conducted a simulation using historical weather data. The response rate and thermal sensation of users with different variations were set, and the delivery timing of the recommendation was changed according to these factors. The proposed methods are expected to effectively generate behavioral changes by having users take medium-to long-term initiatives without lowering their motivation.

  • Dataflow Management Platform for Smart Communities using an Edge Computing Environment

    Shimahara S., Nishi H.

    IECON Proceedings (Industrial Electronics Conference) (IECON Proceedings (Industrial Electronics Conference))  2021-October 2021.10

    ISSN  9781665435543

     View Summary

    As various data services are provided to realize Society 5.0, the usage of personal data is estimated to increase along with the explosive increase in data traffic. It is important that the protection of privacy keeps pace with increases in the exchange of data containing personal information. Starting from the enforcement of the General Data Protection Regulation (GDPR), stricter privacy protection regulations are expanding to more countries. These restrictions require that personal data should be hidden or anonymized before they are propagated over the network. The secondary usage of data is assumed in smart communities, and systems that can protect privacy are required for secure network infrastructures. In this study, we propose an edge-based computing platform that manages the privacy of users on the network of a smart community. For the platform, we prepared three models: The Basic, Preceding Packet, and Piggyback models. These are considered OpenFlow models, and the network efficiency for each was evaluated.

  • Efficient GAN-Based Unsupervised Anomaly Sound Detection for Refrigeration Units

    Hatanaka S., Nishi H.

    IEEE International Symposium on Industrial Electronics (IEEE International Symposium on Industrial Electronics)  2021-June 2021.06

    ISSN  9781728190235

     View Summary

    A smart factory or Industry 4.0 is creating an epoch for manufacturing and its production lines. It reduces the total cost by monitoring and predicting the expected faults of factory lines and products. One of the essential challenges is to develop a technology to detect and predict abnormalities at an early stage without human resources. For this reason, the automation of anomaly detection is now attracting attention. Many statistical and machine-learning methods have been studied for anomaly detection. In this study, we focus on a refrigeration system for large storage, where the failures of the system will cause enormous losses. Moreover, this type of system was independently designed according to the environment, location, and storage items. Under this condition, it is difficult to train discriminative models for anomaly detection using training data that include failure data. In addition, it is indispensable to provide a basis for determining whether the system is abnormal to achieve future treatments. Therefore, deep generative models are used to achieve unsupervised abnormality detection. Because the sensing system's cost for detecting system failures should be reduced, the proposed system uses low-cost microphone arrays to monitor sounds and source locations. The system also provides a rationale by visualizing and mentioning irregular sounds. Furthermore, this study compared various deep generative models in terms of accuracy and showed that the Efficient GAN-based method achieved the highest accuracy.

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Papers, etc., Registered in KOARA 【 Display / hide

Reviews, Commentaries, etc. 【 Display / hide

Research Projects of Competitive Funds, etc. 【 Display / hide

  • Smart Community Information Platform for Providing Critical Services

    2017.04
    -
    2020.03

    MEXT,JSPS, Grant-in-Aid for Scientific Research, Grant-in-Aid for Scientific Research (B), Principal investigator

Intellectual Property Rights, etc. 【 Display / hide

  • 電力制御システム

    Date applied: 2010-108910  2010.05 

    Patent, Joint

  • 人数推定装置及び人数推定方法

    Date applied: 特願2009-292481  2009.12 

    Patent, Joint

  • 換気量推定装置及び換気量推定方法

    Date applied: 特願2008-180072  2008.07 

    Patent, Joint

  • マニピュレーター装置

    Date applied: 2007-103550  2007.04 

    Date announced: 2008-259607   

    Patent, Joint

  • マスタスレーブ装置、マスタ装置、スレーブ装置、制御方法及びコンピュータプログラム

    Date applied: 特願:2006-302787  2006.11 

    Patent, Joint

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Awards 【 Display / hide

  • 社団法人情報処理学会 計算機アーキテクチャ研究会若手奨励賞

    澤田 純一,西 宏章, 2012.01, 社団法人情報処理学会計算機アーキテクチャ研究会, 「低遅延匿名化処理機構における情報損失度改善手法の提案」

    Type of Award: Award from Japanese society, conference, symposium, etc.

  • 社団法人情報処理学会CS賞

    石田慎一, 原島真悟, 鯉渕道紘, 川島英之, #H西宏章, 2011.07, 社団法人情報処理学会, 「コンテキストスイッチを利用したルータにおけるTCP ストリーム再構築のメモリ削減手法」

    Type of Award: Award from Japanese society, conference, symposium, etc.

  • 第144回SLDM研究会優秀発表学生賞

    石田慎一, 原島真悟, 川島英之, 鯉渕道紘, 西 宏章, 2010.09, 社団法人情報処理学会システムLSI設計技術研究会, 「パケットデータ管理基盤における情報抽出処理の効率化技法」

    Type of Award: Award from Japanese society, conference, symposium, etc.

  • 社団法人情報処理学会ユビキタスコンピューティング研究会優秀論文賞

    上吉 悠人,峰 豪毅,西 宏章, 2008.07, 「クラスタ型エネルギーマネジメントに向けた大学キャンパスのエネルギー計測システム」

    Type of Award: Award from Japanese society, conference, symposium, etc.

  • 財団法人ファナックFAロボット財団論文賞

    水落 麻里子,辻 俊明,大西 公平,西 宏章, 2008.03, マルチレートサンプリング手法を用いた加速度制御系の実現

    Type of Award: Award from publisher, newspaper, foundation, etc.

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Other 【 Display / hide

  • 2014年

     View Details

    ITU-T Focus Group - Smart Sustainable City

  • 2010年

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    IEEE2030 Standard

 

Courses Taught 【 Display / hide

  • SEMINAR IN SYSTEM DESIGN ENGINEERING

    2022

  • MULTI-MEDIA SYSTEMS DESIGN

    2022

  • LABORATORIES IN SYSTEM DESIGN ENGINEERING 2)

    2022

  • INDEPENDENT STUDY ON SCIENCE FOR OPEN AND ENVIRONMENTAL SYSTEMS

    2022

  • GRADUATE RESEARCH ON SCIENCE FOR OPEN AND ENVIRONMENTAL SYSTEMS 2

    2022

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Social Activities 【 Display / hide

  • 一般社団法人 おもてなしICT協議会 代表理事

    2016.05
    -
    2019.03
  • CANDER TPC member

    2016
    -
    Present
  • 総務省「本格的なIoT時代に対応した情報通信技術の研究開発・標準化動向及びその推進のための調査・分析」事業における「IoT利活用のための共通ICT基盤の研究開発・標準化動向の調査検討グループ」グループ長

    2015.11
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    2016.03
  • FPGA4GPC Program Committee Member

    2015.03
    -
    Present
  • NEDO ノーマリーオフコンピューティングの普及検討委員会 委員

    2015.02
    -
    2015.05

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Memberships in Academic Societies 【 Display / hide

  • 電信通信情報学会シニア会員, 

    2016.12
    -
    Present
  • 情報処理学会計算機アーキテクチャ研究会, 

    2009.09
    -
    Present
  • 建築学会, 

    2008.10
    -
    Present
  • 電子情報通信学会コンピュータシステム研究専門委員会, 

    2005.05
    -
    Present
  • 計測自動制御学会, 

    2003.05
    -
    Present

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Committee Experiences 【 Display / hide

  • 2017.11
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    Present

    IEEE 2668 (IDEX) Standards Committee Member, IEEE 2668 (IDEX) Standards Committee Member

  • 2017.11
    -
    Present

    IEEE P21451-1-6 Standards Committee Member, IEEE P21451-1-6 Standards Committee Member

  • 2017.10
    -
    Present

    IEEE P1451.0 Standards Committee Member, IEEE P1451.0 Standards Committee Member

  • 2017.10
    -
    Present

    IEEE P1451-99 Standards Committee Member, IEEE P1451-99 Standards Committee Member

  • 2017.06
    -
    Present

    Urban Technology Alliance, Urban Technology Alliance

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