NexGen IoT Acceleration Lab(Advance Project Acceleration WG)

IoT Support Committee (Third Meeting)

AgendaDate:

9:00-10:30, Tuesday, December 6, 2016

Location:

Ministry of Economy, Trade and Industry
Main Building B2F Auditorium

Proceedings:[Handouts]
Material #1:
Material #2:

Activity Report and Future Action Plans
of NexGen IoT Acceleration Lab

Member List
Activity Report and Future Action Plans
of NexGen IoT Acceleration Lab
Reference Material #1:
Lists of projects to be supported/selected
through 2nd IoT Lab Selection
Reference Material #2:
Implementation State of IoT Lab Demonstration
by Themes

Provisional Edition
Material ＃1

NextGen IoT Acceleration Lab IoT Support Committee Member<Chairman>
Kazuhiko Toyama

Representative Director and CEO,
Industrial Growth Platform, Inc.

<Member>
Fujiyo Ishiguro

President and CEO, Netyear Group Corp.

Hiroaki Nakanishi

Chairman of the Board, Representative Executive Officer,
Hitachi, Ltd.

Dr. Jun Murai

Dean/Professor, Faculty of Environment andInformation Studies, Keio University

Junichi Tsujii

Director, Artificial Intelligence Research Center

Makiko Eda

Representative Director and President, Intel K.K.

Makoto Takahashi

Executive Vice President, Representative Director,
KDDI CORPORATION

Marco Annunziata

Chief Economist, General Electric

Masaaki Tanaka

Senior Global Advisor，Pricewaterhouse Coopers International

Paul Daugherty

Chief Technology Officer, Accenture plc

Peter Fitzgerald

Japan Managing Director, Google Inc.

Shinichi Koide

Executive Vice President, salesforce.com, inc.
Chairman and CEO, salesforce.com Co., Ltd.

Soichi Kariyazono

Chairman, Japan Venture Capital Association

Tadao Nagasaki

Representative Director and President,
Amazon Web Services Japan K.K.

Taizo Son

President & CEO, Mistletoe, Inc.

Takayuki Hashimoto

Vice Chairman, IBM Japan, Ltd.

Takeshi Natsuno

Guest Professor, Graduate School of Media and Governance,
Keio University

Taro Shimada

Senior Executive Operating Officer & Division lead,
Digital Factory / Process Ind. & Drives Division, Siemens K.K.

Tatsuya Harada

Professor, School of Information Science and Technology,
The University of Tokyo

Tony Blevins

Vice President, Apple Inc.

Dr. Udo Wolz

President and Representative Director, Bosch Corporation

Wayoh(Kazuhiro) Suzuki

Managing Director, Strategic Solution and Business,Development, Cisco Systems G.K.
Wataru Baba

Vice President, Chief Innovation Officer, SAP Japan Co., Ltd.

Yasufumi Kanemaru

Chief Exective Officer, Future Architect, Inc.

Yasuyuki Higuchi

Chairperson, Microsoft Japan Co., Ltd.

Provisional Edition
Material #2

Activity Report and Future Action Plans of
NexGen IoT Acceleration Lab(Discussion Issues)
December 6, 2016
Commerce and Information Policy
BureauMinistry of Economy, Trade and Industry

Activities of NexGen IoT Acceleration Lab

Today’s Discussion Topics
Activity Report
In order to create new IoT business models, and discover and develop IoT
platform creators so that they can serve as a driving force for new growth, theIoT Acceleration Lab aims to① provide short term project support and business matching support,② expand activities to mid and long term project support and regional/global
collaboration, and link these activities organically.
Future Action Plans
 How to build platforms for large companies, venture companies, andoverseas companies to collaborate with each other.。
 At this time, determine which areas or what specific solutions for social
problems to place importance on.
＜Keyword＞ ・・・ P30～37
 Award type support (Task setting) Platform construction
 Participation of overseas companies
 Regulatory reform for broad areas
 Human resource development
 Linkage with private sector VC support
 Reinforcement of distribution inside and outside 内外への発信強化

2

IoT Acceleration Consortium

3

In response to the era of IoT/Big Data/AI, the “IoT Acceleration Consortium” was established as an organization led by the private
sector to promote use of IoT in industry, government, and academia beyond the framework of individual companies andindustries.（Established on Friday, October 23, 2015)
Makes proposes on technological development use of IoT, solutions for policy issues, etc. Presently, there are more than 2500
member companies.

GeneralMeetingChairperson
Vice Chairperson

Steering Committee

Chairperson

Jun Murai

Dean/Professor, Faculty of Environment and Information Studies, Keio University

Vice
Chairperson

Hiroo Unoura
President and CEO of NTT
Hiroaki Nakanishi Chairman of the Board, Representative Executive Officer, Hitachi, Ltd.

(15 members)

Steering Committee Members

2,544 members
such asparticipatingcompanies, etc.
(As of October 31)

Hideyuki Okubo
Noboru Koshitsuka
Mitsunobu Koshiba
Hiroshi Saito
Masao Sakauchi
Toshiyuki Shiga
Hiromichi Shinohara

Chairperson

Jun Murai

Dean/Professor, Faculty of Environment and Information Studies, Keio University

Executive Vice President, Mitsubishi
Electric
Professor, University of Tokyo Graduate
SchoolPresident, JSR
Vice President, Hitachi
Chairman, National Institute of Information
and Communications Technology
CEO and Chairman of Innovation Network
Corporation of Japan
Vice President, NTT

Osamu Sudo

Professor, University of Tokyo Graduate School

Hikaru Domoto

Vice Chairman, NHK

Hideyuki Tokuda
Sawako Nohara
Chikamoto
Hodo
Izumi Hayashi

Professor, Keio University Graduate School
President & CEO, IPSe Marketing, Inc.
Chairman, Accenture

Yutaka Matsuo

Associate Professor, University of Tokyo

Lawyer(Smart IoT Acceleration Forum)

Advanced Model Businesses
Promotion ＷＧ(IoT Acceleration Lab)

IoT Security ＷＧ

Development, demonstration andstandardization of IoT-related
technologies such as networks

Support creation of advanced
model businesses, improvementof business environment throughregulatory reform, etc.

Review guidelines on
network connection of IoT
equipment, etc.

Technology Development ＷＧ

Coope-ration

Data Flow
Promotion ＷＧ
Review tasks of areas withhigh data flow needs, etc.

Coope-rationMinistry of Internal Affairs and Communications, Ministry of Economy, Trade and Industry, etc.

IoT Acceleration Lab

4

The IoT Acceleration Lab supports the following projects through (1)financial support, (2)regulatory support (review ofregulations, establishment of rules), and (3)business matching– Short-term outstanding projects by individual companies and– Mid and long-term projects participated by multiple companies
Aiming at social implementation
Presently, there are more than 2500 member companies.

Details of support

IoT Acceleration Consortium
General assembly
participated by
600 companies, 760
persons

Steering Committee (15members)

Regulatory support

Financial support

Corporate
collaboration support

IoT Lab Demonstration(Test bed demonstration)
Tech. Dev. WG IoT Acceleration
Lab(Smart IoT
Acceleration
Forum)Development &demonstration,andstandardizationof IoT-related
technologies suchas a network(Advanced Project
Acceleration WG)

Creation ofadvanced project,
Improvement of
biz environment
such as regulatory
reformIoT LabConnection→Support mid and long-term thematic projects
by multiple companies(Business matching)Specific WG

IoT Lab Selection
Establishedaccording toissues・ Security WG・ Datadistribution WG

SupportCommittee• Provide advice, andadministrative recommendations on
regulations and systems, etc.
to IoT projects(IoT Project Selection Meeting)→Support short-term individual project→Organize matching
events forcompanies, researchorganizations, andmunicipals.

[Topics (Draft)]
Manufact
uring (*)
Agriculture

Mobility
Logistics

MedicalhealthPublicinfrastructure/
construction

Administ-rationIndustrial
safetyEnergyFinance(**)

Educational
services

Smart
house

Tourism* Work closely with Robot Revolution initiative**Work closely with Study Group on FinTech

IoT Support Committee Members＜Chairman＞
Kazuhiko Toyama

Representative Director and CEO, Industrial Growth Platform, Inc.

＜Members＞
Fujiyo Ishiguro
Udo Wolz
Makiko Eda
Yasufumi Kanemaru
Soichi Kariyazono
Shinichi Koide
Taro Shimada
Wayoh (Kazuhiro)
SuzukiTaizo Son
Makoto Takahashi
Masaaki Tanaka
Junichi Tsujii
Tony Blevins
Tadao Nagasaki
Hiroaki Nakanishi
Takeshi Natsuno
Takayuki Hashimoto
Tatsuya Harada

Wataru Baba
Peter Fitzgerald
Yasuyuki Higuchi
Paul Daugherty
Marco Annunziata,
Jun Murai

President and CEO, Netyear Group Corp.
President and Representative Director, Bosch Corporation

Representative Director and President, Intel K.K.
Chief Exective Officer, Future Architect, Inc.
Chairman, Japan Venture Capital Association
Executive Vice President, salesforce.com, inc.
Chairman and CEO, salesforce.com Co., Ltd.
Senior Executive Operating Officer & Division lead,
Digital Factory / Process Ind. & Drives Division, Siemens K.K.
Managing Director, Strategic Solution and Business,
Development, Cisco Systems G.K.
President & CEO, Mistletoe, Inc.
Senior Managing Executive Officer, Representative Director, KDDI CORPORATION
Senior Global Advisor，Pricewaterhouse Coopers International
Director, Artificial Intelligence Research Center
Vice President, Apple Inc.
Representative Director and President, Amazon Web Services Japan K.K.
Chairman of the Board, Representative Executive Officer, Hitachi, Ltd.
Guest Professor, Graduate School of Media and Governance, Keio University
Vice Chairman, IBM Japan, Ltd.
Professor, School of Information Science and Technology, The University of Tokyo
Vice President, Chief Innovation Officer, SAP Japan Co., Ltd.
Japan Managing Director, Google Inc.
Chairperson, Microsoft Japan Co., Ltd.
Chief Technology Officer, Accenture plc
Chief Economist, General Electric
Dean/Professor, Faculty of Environment and Information Studies, Keio University

5Activities of IoT Acceleration Lab (Outline)6

 In order to create new IoT business models, and discover and develop IoT platform creators so that they can serve as adriving force for new growth, the IoT Acceleration Lab aims to provide short term project support and business matchingsupport, and expand activities to mid and long term project support and regional/global collaboration, and link these
activities organically.
Regulatory reform,
standardization, etc.

Corporate collaboration support① IoT Lab Selection (IoT Project Selection Meeting)② IoT Lab Connection (Solutions/matching)

Financial support

Short-term projects

Scout and select advanced IoT projects to provide
financial support, mentor support, deregulation
support Sun

Until now, established matches in the areas of tourism,
manufacturing, healthcare (medical care and health), sports,
logistics, distribution, infrastructure, smart-homes, mobility.

②-1 Big Data Analysis Contest

Mid & longterm PJ③ IoT Lab Demonstration (Test bed demonstration)
Mid and long term demonstration involving
multiple companies according to theme

Competition fordeveloping algorithms
online utilizing tourism
big data provided bycompanies②-2 Collaboration with
CEATEC
Exhibition
by selection
winners,
Connection,
etc.

Regional④ Local IoT Acceleration Lab
Select regional efforts for creating IoT business as ”Local IoT Acceleration Labs”, and carryout matching, projects (product development, events, etc.), demonstration tests, etc. at
the regional level. At present 29 regions have been selected.

Global

①、②、②－１…Started from 2015③～⑤、②－２…Started from 2016

⑤ IoT Lab Global Connection (Global IoT Acceleration Lab)
Aim at matching of overseas companies and Lab members,
and collaborations with other global organizations.

Activities and Future Schedule

7① IoT Lab Selection
February 7
July 13
March 13

1st IoT Project Selection Meeting
2nd IoT Project Selection Meeting ★1
3 rd IoT Project Selection Meeting ★3② IoT Lab Connection
January 28
July 31
October 5
March 13

1st matching event [Themes: Factory and tourism]2nd matching event [Themes: Healthcare, sports, logistics, distribution and infrastructure] ★1
3 rd matching event [Theme: Smarthome and mobility] ★2
4 th matching event [Theme: Fintech, education and agriculture] ★3[Big Data Analysis Contest]
February ７
1st Award-giving Ceremony
October 5
2nd Award-giving Ceremony ★2[Held jointly with CEATEC】
October 4-7 Exhibition by selection winners ★2③ IoT Lab Demonstration[FY2017 Demonstration]
May 31
Deadline for application
From June
FS (feasibility study) survey
From April
Start demonstration[FY2016 Demonstration]
From April Start public invitation and demonstration④ Local IoT Acceleration Labs
July 31
March 13

1st Selection
2nd Selection ★3⑤ IoT Lab Global Connection
October 4-7
March 13

1st matching [ASEAN, India, Israel] ★2
2nd matching ★3※Events marked with the same numbers (★１, ★２, ★３) are held at the same timeOutline of IoT Lab Selection (Advanced IoT Project Selection Meeting)8

 Scout and select advanced IoT projects to be supported such as ①Financing, ②Mentor dispatching, ③Deregulation and standardization, jointly by government agencies, financial institutions, venture capitals, etc.
 Select advanced projects from the perspectives of growth, leadership, repercussion, social development,
etc. Selected and awarded during the “3 rd IoT Project Selection Meeting” held on March 13.
 Changes made from the 1st and 2 nd meetings were new horizontal platform framework and regional
economic revitalization framework were set.

TargetGroupsand
Items
Evaluated

Target groups: All advanced projects using
technologies such as the IoT(All types of businesses, including large enterprises,
small and medium enterprises (SMEs), and individuals)
Items evaluated: The following are evaluated(1) Growth potential (2) Openness(3) Sociality(4) Feasibility of realization
The following three types of support are available (multiple
types allowed)

SupportDetails

Sharing
Application
Content(1) Financial support(2) Continuous, one-on-one support from mentors(3) Support related to regulatory reform and standardization(Support in completing procedures for use of systems such as
the System to Remove Gray Zone Areas and the System ofSpecial Arrangements for Corporate Field Tests, research anddemonstrations for regulatory reform and standardization, etc.)

If an applicant desires, it is possible to share the contents of
one’s application with
(1) participating support organizations and(2) Lab members.
*Entities which are not selected for the final selection can transmit
the details of their projects to supporting institutions, Lab member
companies, etc.

3rd Advanced IoT Project Selection Meeting Schedule

Nov. 1- Dec.15

Start accepting applications

Late Jan. (Scheduled)
Screening results
announced

1st Screening (documents)

Early to mid Feb（Scheduled）

2nd Screening(Non-disclosed presentations)

Selection Meeting
Mar. 13@Hitotsubashi Hall [Open presentations](Final presentation screening)
5-10 candidates

March to April
onwards[Financial Support]
Decide support for
projects one by one[Support for[Mentor Support]
regulatory reform,
Decide support foretc.] Start
projects one by one
discussions

IoT Lab Selection Awarded Projects

9

The first and second Lab selections gathered a total of 405 applications, from which 29 finalists wereselected. Presentations open to the public were given by the finalists and outstanding projects were awarded
prizes. Support for finalists have also started. For details of projects, refer to Reference Material #1
Funding support：A total of 16 companies applying for NEDO/IPA support (NEDO: 8 companies, IPA: 8 companies）have been selected for funding. Projects to receive
funding support by other participating support organizations are also gradually being decided..
Mentor support： Four companies have already been selected. Another four are currently being screened for selection.
Regulatory support, etc.：Clarification of deregulations based on the system for resolving gray zones and revision of laws and regulations have started for four companies.

★Grand Prize★
UniFa Corporation★Second Prize★
Phoenix Solution Co., Ltd.

★Second Prize★
Zenrin Co., Ltd.

-Supporting the digitalization of services formonitoring the premises of nursery schoolsActivities at nursery schools are supported using
smartphones/sensors/robots, etc. So that eveninexperienced nursery school teachers are able totake care of children safely.
Specifically, the company is currently developing
services such as the digitalization of
handwritten documents which tend to poseas huge work burden (Communication
notebook/afternoon nap check table,temperature sheet, etc.)m ）and support formonitoring of children during their afternoon
naps which have the risks of fatal accidents(using video camera/bed sensor).

-World’s-first RFID tag that is readable eventhrough the metal to which it is attached--Demonstration project concerning information on
three-dimensional aerial maps toward therealization of safe drone flight over city areasThe company is aiming to develop an automatic
drone flying support system as an infrastructure forrealizing “contact flight in manned regions such ascity areas, etc.” as the ultimate usage of drones.
(Level 4)

Phoenix has developed special metal tags which can beread using normal readers, especially behind metals andin laminated states. The company aims to apply it to supply
chains for improving work efficiency and reducing
management costs in industries using high volume of metallic
materials such as manufacturing, construction, lease,
distribution, infrastructure and facilities, etc., and also further
expand uses through linkage with sensors, drones, etc. This is
the first technology of its kind in the world. By developing
various types of tags, the companies is aiming at extensive
dissemination around the world, and realizing the IoT of metal
products.
RFID tag

Progress of project

Progress of project・Selected for IPA fund/mentor support
・Resolves gray zones of Child Welfare Act

・NEDO funding decided (Compact metal
RFID)

In this project, the company
aims to realize “3D maps of thesky” including recommended
flight routes and obstacles, aswell as develop technologies
enabling safe drone flight inmanned regions by he real-timetracking of drones deviated fromtheir routes by gathering andanalyzing drone probe
information.

Progress of project・NEDO funding decided (3D map
construction technology)★Special Jury Prize★
exMedio Inc.
-Technology for recognizing ophthalmic disorders using images
and data from medical interviewsFor non-ophthalmic disorders, develop AI enabling automatic identificationand diagnostic support of eye diseases using images and medical
examination data, and mount to mobile apps “Memiru chan”.

Progress of project・Selected for IPA fund/mentor support

IoT Lab Selection Business Development of Projects Selected in 1st Selection10

 New business has been developed through the projects selected in the 1st Lab Selection.
★Grand Prize★ Liquid Inc.
Project support
・NEDO Funding support (Ikebukuro Project)
・Resolves gray zones of Hotel and Ryokan
Management Law★Second Prize★ Aba Inc.
Project support

・Mentor support★Second Prize★ Routrek Networks, Inc.
Project support
・ IPA funding support(Outdoor cultivation algorithms)-Personal authentication of tourists to Japan using fingerprint. (Forsettling payments, personal identification)Business Development
・Has started services at tourist resorts such as
Yugawara in collaborations with JTB
Corporate Sales..

-Excretion detection seat Lifi for reducing nursing burdenBusiness Development

・Through business collaborations, Paramount
Bed is manufacturing and selling Lifi.

-Agriculture system which optimally controls drop culture waterand fertilizersBusiness Development
・ Tied up with Israel’s Netafim to operate Zero Agree in Vietnam.
・ Has agreed to capital tie-up with Oisix★Special Jury Prize★ EverySense Japan, Inc. -Aiming to be platform creators of data transactions using
Project support
・ Establishment of rules (Authorization of agreements ondata mediation business at Data Distribution Promotion
WG)

ZEROBILLBANK
Has tied up with MUFG and Kabu.com Securities tointroduce corporate coin “OOIRI” mainly in the
Otemachi area.

systems mediating transactions between corporate big data andindividual dataBusiness Development
・ Launched IoT information distribution market “EverySense”

StroboDeveloped home IoT device window sensor “leafee mag”.
Carrying out cloud funding.

IoT Lab Selection List of Finalists

11

1st Selection Finalists
ApplicantPersonal authentication of foreign tourists byfingerprints (payment・verification)
Excretion detection sheet “Lifi” to decrease
the burden of nursing★Second Prize★
Routrek Networks, Inc.

Agricultural system optimizing control ofwater and fertilizer for drip irrigation★Special Jury Prize★
EverySense Japan, Inc.

Commercialization of data exchange market
in Japan and US
Build trading system for real time sensor
data distribution
Convert individual ideas and actions tovisible values (coin) utilizing blockchain
To be a global player of SNS big data fromJapan
Smart chair visualizing body conditions bypressure sensors

ZEROBILLBANK LTD
Hottolink, Inc.
Strobo Inc.
BSIZE Inc.
AFRO Co., Ltd.
Social Impact ResearchCo., Ltd.

ApplicantName of Project★Grand Prize★
Liquid. Inc.
★Second Prize★
Aba Inc.

OMRON Corporation

2nd Selection Finalists

Realize new communication business for IoT
Business optimization of taxi using
smartphone
Automated system that can be used byanyone to provide asset management advise
for achieving profits and social development

Project★Grand Prize★
UniFa Corporation

Supporting the digitalization of services formonitoring the premises of nursery schools★Second Prize★
Phoenix Solution Co., Ltd.

World’s-first RFID tag that is readable eventhrough the metal to which it is attached★Second Prize★
Zenrin Co., Ltd.

Demonstration project concerning informationon three-dimensional aerial maps toward therealization of safe drone flight over city areas★Special Jury Prize★
exMedio Inc.

Technology for recognizing ophthalmic
disorders using images and data from medical
interviews

Orylab.Inc.

Realize a community for conveying ourexistence using avatar robot OriHime

GNN Machinery Japan

Raw concrete quality continuous management
system (Smart agitator)

DeNa.Co.Ltd.

Realize personal shopper service forreinforcing regional consumption eco systemsmart-FOA

IoT age data flow information infrastructure“FOA system” for boosting the manufacturingindustry in Japan

Konica Minolta, Inc.

Home medical care support system by noncontact respiratory sensing.

Graduate School ofInformation Science andTechnology, Hokkaido
University

Realize individual medical services utilizing
health data

Aerosense Inc.

Realize safe, simple, and high precision 3Dmodeling operations

Cerevo Inc.

Realize inexpensive home security

JVC KENWOOD

Build health management and remotediagnosis service by self recording breathingsoundsSONY Corporation

Realize display devices suited to the IoT era

Wireless Power Transfer
Consortium for Practical
Application (WiPoT)

Practical Applications(WiPoT)
Practical demonstration of long-distancemicrowave radio transmission system
Individual exercise program based on
physical conditions

Space Market, Inc.

Realize regional revitalization by space
sharing business and create microentrepreneurs

ABEJA

Research and development of data systemcapable of comprehensively managing
complicated data for IoT society

Acadia Systems Inc.

Specific Progress of Finalists (Reassessment of Regulations)

12Regulation support on 4 cases developed through IoT Lab Selection
Liquid. Inc.

-Personal authentication of tourists to Japan using
fingerprint. (For settling payments, personal identification) Development of biometric authentication system capable of personal identification just from fingerprints. By categorizing
fingerprints using artificial intelligence according to characteristics, the system is able to realize 1 million authentications in just 0.05
seconds. Currently, this takes about several hundred seconds. Authentication using two fingers reduces the risks of mis-authentication by
1/1 trillion. Already, the company carries out verifications of personal identification and payment settlement, etc. using fingerprints only at
hotels and shops (no passport and credit cards needed) for tourists to Japan by working together with leading hotels, etc. in this project.

Resolved grayzone！

Clarified how to use the fingerprint authentication system developed by Liquid forchecking passports at check-in.

AFRO Co., Ltd.

-Enhancement of work efficiency of taxis using smartphones-

Development of application mounting taxi meter functions to smartphone. Application connected to the car for enhancing
driving and work efficiency by not only acquiring information on driving distance and calculating taxi fares, but also automating
daily reporting work normally done by hand (taxi usage information, and immediate tracking of the service status of taxis (place,whether customer on board, etc.). These sophisticated functions can be realized at much lower costs than building a special device.

Resolved grayzone！

Clarified the specific requirements for “electronic sealing” of taxi meters.

UniFa Corporation-Supporting the digitalization of services for monitoring

the premises of nursery schools The company is currently developing services such as the digitalization of handwritten documents which tend to pose as huge workburden (Communication notebook/afternoon nap check table, temperature sheet, etc.)m ）and support for monitoring of children during
their afternoon naps which have the risks of fatal accidents (using video camera/bed sensor). Activities at nursery schools are supported
using smartphones/sensors/robots, etc. So that even inexperienced nursery school teachers are able to take care of children safely.

Clarified that digitalization of “account books” based on the Child Welfare Act is possible.

SONY Corporation-Development/commercialization of display

devices suitable for IoT ageAim to commercialize laser type display devices which do not require focusing (focus free) and considered to be aneffective display device for the IoT community, and promote its spread in the IoT age.

Resolved grayzone！
Partially revised
ministerial ordinances
related to Consumer
Product Safety Act

IoT Lab Connection

13

Matching Events for Promotion of Corporate Collaborations (Solutions Matching)The matching event was held for enterprises aiming to create new business models such as member
companies with seeds or needs, and associations and municipalities to meet others with related businessmodels, technologies, and services to promote the creation of businesses leading to ideas required forrealizing the business models and applying them in society.



The theme of the first event (January) was (1)Tourism (2)Manufacturing. That of the second event (July) was(1)Healthcare (medical care/health) and Sports, and (2)Logistics, distribution and infrastructure. Thatof the third (October) was (1)Smart homes (2)Mobility and this event was held at the CEATEC hall.

Details of 2nd event
Date: Sunday, July 31, 2016, 10:30-16:45
Venue: Tokyo Hitotsubashi Hall (Hitotsubashi University)
Co-hosts: IoT Acceleration Lab and METI
Support entity: Ministry of Land, Infrastructure, Transport andTourism / Japan Sports Agency
Participating municipalities: Tokyo, Chiba Pref. Chiba City,
Kanagawa Pref. Kawasaki City, Nagano Pref. Matsumoto City,
Mie Pref.Hyogo Pref. Kobe City, Shimane Pref., Fukuoka Pref.
Fukuoka City

② Presentation Matching (1:N Matching)
Popular matching companies, etc.
presented their seeds and needs to
the general public. Meetings were
held with interested enterprises atthe venue.

7 government agencies andcompanies presented
Approx. 300 participants① Business Matching (１:１ Matching)
Based on the needs and seeds
submitted by the participants society.
in advance, a list of matchingcompanies was created prior to theevent. 15-minute private sessions
were held on the day.

Approx. 183

companies/organizations participated.
Approx. 518 matches were carriedout③ Municipalities Booth Matching（Municipalities ：N Matching）
Booths were set up bymunicipalities.
Companies/organizations
interested in municipality’s seeds
and needs held meetings at thevenue.

8 municipalities set up booths

IoT Lab Connection

14

Matching Events for Promoting Corporate Collaborations (Solutions Matching)[1st event] Thursday, January 28, 2016 ＠Tokyo Hitotsubashi Hall (Hitotsubashi University)
Theme: Tourism, manufacturing (Smart factories)
About 190 companies/organizations participated, and about 550 matchings were carried out.
(Average of questionnaire results)
No. of companies who interchanged with each other: 10.6 companies
No. of companies planning to continue interchange: 3.6 companies[2nd event] Sunday, July 31 ＠Tokyo Hitotsubashi Hall (Hitotsubashi University)
Theme: Healthcare (medical care/health), sports, distribution, logistics, infrastructure
About 183 companies/organizations participated, and about 518 matchings were carried out.
Average of questionnaire results）
No. of companies who interchanged with each other: 6.8 companies
No. of companies planning to continue interchange: 3.4 companies[3rd event】 Tuesday, October 4, 2016 @CEATEC JAPAN 2016
Theme: Smart home, mobility
About 135 companies/organizations participated, and about 454 matchings were carried out.
（Average of questionnaire results）
No. of companies who interchanged with each other: 6.8 companies
No. of companies planning to continue interchange: 3.0 companies→ Total for 3 events
About 508 (375 when overlaps are excluded) companies/organizations participated, and about 1,522 matchings were carriedout.
(Average of questionnaire results）
No. of companies who interchanged with each other: 8.1 companies
No. of companies planning to continue interchange: 3.3 companies
According to the information from the 36 companies responding to the secretariat’s survey,
about 16 collaborative partnerships were formed.

Lab member companies who have never participated in matching events to date 1,779/2,123 companies（Approx. 83.8％）

Results of Past IoT Lab Connection

15■ NTT DoCoMo × Niigata Institute of Technology × Japan GE × Oki Electric※Starting point of matching is NTT DoCoMO and Japan GE
Image ofNTT DoCoMo which proactively participates in collaborations between different industries, realization
Niigata Institute of Technology which has a strong network with regional manufacturing
companies, Japan GE which has an IoT platform for analyzing sensor data of plants, andOki Electric which has wireless units and modules have jointly launched “Smart Factory
City in Kashiwazaki” in the aim to optimize the whole supply chain by sharing data
Ordersexceeding the realms of companies. As part of efforts to promote the understanding of received
these activities, the companies plan to start study groups for local companies.

Apply and spread

ResaleEnergy, production process, asset/maintenance management, ERP
Personnel development, Healthcare, Logistics, Financial screening■ Mintomo x Nuance Communications Japan
Collaboration between Mintomo, a venture company developing apps strong in gamification, andNuance, developing voice and fingerprint recognition technologies, making use of the respective
characteristics of the two companies. To prevent the reselling of tickets which is now a social problem,
they are developing a digital ticket “KOE-PASS” which allows use only by the purchaser by voicerecognition.

Others…
■Software development ventures × companies owning device
Started reviews aiming to combine data gathered from apps and from different devices to enhance the forecast
accuracy of applications.

■ Facilities related companies ×leading Internet companies
Started reviews aiming to create new values anticipating future changes in social structures.

■ Device manufacturers × leading companies
Started reviews leading to demonstration tests in the fields of leading companies using new devices developed.

■ Companies owning sensors × leading manufacturers
Started reviews towards new product development using sensors.

In addition to the above, relations are continuing amongst many companies.

IoT Lab Connection Big Data Analysis Contest

16

Algorithm development contests where participants compete over the analysis of big data provided by companies, etc.
and the accuracy of data analysis using this data are held online to enable ease of participation. Participants are invitedwidely from the public including students. By analyzing the challenges and data of industry, the contest aims to discover
outstanding data scientists, match them with data providers, etc., and at personnel development. The first contest (December
2015 to January) was themed on tourism and aimed at the development of algorithms for predicting the number of tourists.
The second content was themed on distribution and retail (development of sales forecast algorithm/new productdevelopment).

〈Outline of 2nd Contest〉
Co-organizers: IoT Acceleration Lab, Ministryof Economy, Trade and Industry (METI)
Supporting organizations: Ministry of
Education, Culture, Sports, Science andTechnology (MEXT), National Institute ofAdvanced Industrial Science andTechnology (AIST), Research Organizationof Information and Systems (ROIS)
Design/operations：Opt Holdings
Date： July 7, 2016 to September 1, 2016

Forecast

Sales data
Data on monthly sales of concerned sweets by store, gender, age for past 12 months

Product data
Information on production characteristics of original sweets (47 in total) and healthy sweets (26 intotal) (Nutritional composition, descriptions, etc.)

Store data
Information on about 1,400 stores sampled (Including store attributes such as area, location patterns.
Excludes store names.)

SNS data
Change in number of postings including words related to healthy foods (Blog, twitter, bulletin boards)

Food information data
Information such as nutritional composition and materials, etc. of all 80 products centering aroundhealth-oriented foods

External data (Collected freely by analysists)

No. of participants：150

No. of applications：2,226(Multiple applications allowed)

Data for learning

Evaluation data

June 2015 to May 2016 (one year)

June 2016[Sales forecast]○ Compete over precision to forecast sales data of the latest month from data
[New product development]○ Compete over product development proposals for new sweets liked by men
in 30’s from data.
→ University students and working adults won the prizes

Actual data on
private label
sweets sold at
Natural Lawson
was provided.

IoT Lab Connection Feedback on Big Data Analysis Contest

17

 Big data analysis is participated not only by universities, but by many company employees.
Personnel specializing in machine learning make up about 30% of all participants.
 Participants are able to experience data analysis using raw data which is directly linked actual
business. The contest has received many favorable comments as a place for practicing data analysis.

Attributes of applicants
Out of the 150 applicants,••

Voices of applicants•

I was able to experience actual business issues
and learn the importance of practice thantheory and logic. I truly learnt a lot.

•

Through this contest, I had the opportunity toobserve people buying sweets in myneighborhood, conduct questionnaire surveys
on my friends, and so on. Because the themes
were related to everyday life, data processing
and the results obtained were all very
interesting. The whole work was very fun.

•I hope to continue participating in this event. It
would be nice if there are more of suchopportunities in the future.

Less than 50% are in their 20”s

60% are full-time employees,of which more than 60% are IT••

companies
57％ are university graduates
Field of specialty includes machinelearning 30％,
data mining 22％,time series analysis 10%

IoT Lab Demonstration (Test-bed Demonstrations)18

 IoT Lab Demonstration is demonstration project by multiple companies aiming at mid and long termsocial implementation. They aim to form a platform for sharing and using data exceeding the realms ofoffice, company, and time by identifying competitive areas and collaborative areas. For details of projects,
refer to Reference Material #2.

Flow of IoT Lab Demonstration① Invite themes② FS survey(Discover potential needs)(Review demonstration architecture)・Invite themes to be

・FS survey will be implemented

implemented by IoT
Acceleration Lab members, etc.

Efforts until now

・Reflect in estimate
requirements, etc. of theby clarifying the scope to be
implemented by the government demonstration projects (Testbed demonstrations), andand that to be implemented by
implement.
the private sector.

・Based on the proposals,

・Themes were invited
between April 28 and May
31 , 2016, and 25 were
proposed.
（Proposed themes）
・Infrastructure/construction
・Manufacturing
・Medical/healthcare
・Logistics/distribution
・Smart homes
・Agriculture
・Industrial safety
・Tourism
・Administration③Test-beddemonstration

FS surveys will be
conducted on 13
themes.
６
４
４
３
３
２
１
１
１

（Examples of themes）
・Smart home・Aircraft
・Security・Distribution
・Development of mines,
etc.

④Evaluation/
follow-up
・Implement evaluation andfollow-up by support
committee, etc.

・A responsible support
committee will be set up foreach theme. In the future, thecommittee will hold meetings
twice a year to report the stateof implementation, andcomments from responsible(Ongoing demonstration themes） committee members will be・Manufacturing (Smart factories) reflected in future efforts.
・Social infrastructures
・Responsible AI center・Industrial safety
researchers will be appointed
・Administrationfor each theme. Comments on
・Medical/health careuse of AI will be reflected in・Distribution/space
future efforts, etc.
・Service
・In addition to themes thathave been implemented sofar, demonstrations related
to the smartphone andaircraft areas, etc. will be
carried out.

Through the demonstrations, the Japanese government is ①Reassessing regulations according to
new technologies such as IoT, and ②establishing minimal rules for companies to follow, such as
standardized data formats, equipment ID management and authentication rules.

Local IoT Acceleration Labs

19

 Regional efforts to promote IoT business as local IoT Acceleration Lab.
Selection Criteria(3 criteria for selection as
Local IoT Acceleration Labs)

1. Regionality
2. Enthusiasm and continuityof municipalities (Scenario
for independence, key
persons)
3. Sense of unity withdiversity

XX Prefecture/City/Town IoT Acceleration Lab

Venture companies
in region

Schools/universities
in region

Various projects by various participants
Utility companies
in regionVenture companies
in region

Matching
Projects(product development,
events etc.)

Public institutein region

Selection
SupportPermission to use Logos
Sending mentors
Project supports
Service provision fromsponsors

Demonstration
Core companies
in region

Investors/funds/
financial institute in region

Participation to IoT
Acceleration Lab
project

IoT
Acceleration
Lab
METI

Matching
Project Support
Demonstration
System reforms

Liaison office : local governments, local trade associations etc.

Support for Regional IoT Acceleration Lab
1. Grant rights to use “Local IoT Acceleration
Lab” mark2. PR to IoT Acceleration Lab members in mailmagazines, Lab events, etc.
3. Dispatch mentors contributing torealizing/developing regional
projects/companies, etc.
* Review support by cooperating companies and linkage withvarious grant systems according to business progress.

Latest Schedule
Jun. 10 Start invitation to apply(Regions submit to METI)(Note 1) No deadlines are set for the invitations.
Applications are accepted and screened all year
long.
(Note 2) After selection, mentors and cooperatingcompanies are gathered..

Jul. 31 1st Selection (18 prefectures 11
cities/towns)
Mar. 13 2nd Selection

First Selection of Applicants for Local IoT Acceleration Labs

20

• 29 regions were selected as “Local IoT Acceleration Lab”. In the future, these local IoT
Acceleration Labs and the IoT Acceleration Lab will work together to support andencourage IoT efforts around the country through the dispatch of mentors, etc.

（Selected 29 regions）
Sapporo City, Hokkaido Prefecture / Kushiro City, Hokkaido Prefecture / Shihoro Town, Hokkaido Prefecture
Miyagi Prefecture / Aizuwakamatsu City, Fukushima Prefecture / Ibaraki Prefecture / Toyama Prefecture
Ishikawa Prefecture / Kaga City, Ishikawa Prefecture / Fukui Prefecture / Ina City, Nagano Prefecture
Gifu Prefecture / Shizuoka Prefecture / Aichi Prefecture / Mie Prefecture / Kyoto City, Kyoto Prefecture
Osaka City, Osaka Prefecture / Kobe City, Hyogo Prefecture / Nara Prefecture / Wakayama Prefecture
Shimane Prefecture / Hiroshima Prefecture / Kochi Prefecture / Fukuoka Prefecture
Kitakyushu City, Fukuoka Prefecture / Fukuoka City, Fukuoka Prefecture / Kumamoto Prefecture
Kagoshima Prefecture / Okinawa PrefectureLocal IoT Acceleration Labs

21

Summary of Regions Selected in 1st Selection
 Local IoT Acceleration Labs can broadly be divided into ①Support types and ②Projecttypes. Diverse efforts are selected according to regional characteristics and tasks, andsupported

Support Type Labs

Project type labs

Labs which are formed mainly by municipalities
to support companies attempting to carry out
IoT business.

Labs comprised mainly of companies to carryout one specific project.

i) Business contest labs
Focusing on projects, these labs screens degree ofcompletion and innovativeness throughcompetition and supports/awards outstanding
projects.

ii) Personnel development labs
Focusing on personnel, these labs aim to foster
outstanding IoT personnel in the labs.

iii) Test-bed labs
Labs which prepare test beds for companies
belonging to the labs to freely participate indemonstrations in the aim to create outstanding
projects through trial and error.

(E.g.) Hokkaido Shihorocho
・The agricultural IoT device “e-kakashi” developing PS
solutions is installed demonstration farms owned by
the local Shihoro High School.
The accumulated environment datais biologically and physically analyzed
and students learn skills cultivated byusing the data. It contributes to thefostering of outstanding agricultural
personnel.

・By formularizing cultivation methods (=recipes) using
data, aim to transfer cultivation techniques through thehigh school students, and improve productivity of thewhole regions through cross-section development tofarmers in the region.

⇒ Aim to construct an eco system for creating new IoT business that are independent in the region.

Local IoT Acceleration Lab Advanced Project ①：

22

Business Contest type Lab【テストベッド型ラボ】■ Osaka City, Osaka Prefecture
・ In Osaka City, small and medium sized companies make up 98% of allcompanies. In order to create new businesses and services using IoT sothat these small and medium sized companies can acquire the ability
to make profits and gain competitive strength, the entrepreneur
development program “AIDOR” dedicated to IoT business has beenlaunched
・ Led by the Advanced Telecommunications Research InstituteInternational(ATR) which conducts studies in the IT area and Osaka Urban
Industry Promotion Center which provides supports for various businessneeds from startup to business transfer, the program aims to brush up
businesses by mentoring, etc. It aims to contribute to economic growthin Osaka City by creating new businesses, fostering business minds,
etc.

Embodies ideas

Those wanting tostart IoT business
Those wanting tostart new businessBusinessideas

Brush up business plan/prototypes

IT and software related professionals

Hardware related professionals

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Support required for hands-on support
Capital procurement, prototype development,
marketing, etc.

Pitch

Pitch
d A B
e n u
s d s
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s
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Improvement

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n

Mentoring【テストベッド型ラボ】【市のテストベッド化とICTオフィスによる産業集積】■ Kobe City, Kobe Prefecture
・ Amidst the major structure changes of industry and society due to theprogress of IoT, AI, and big data technologies, Kore City aims toinvigorate Kobe’s economy, by supporting IoT startups by mainly
launching acceleration programs.

Operating company

Partner companies
Provide acceleration
program・Kobe City became the first city in Japan to invite the “500 Startups”
program to Japan. This program is a top level accelerator(organization to support the development of startups) in the world
which provides accelerator programs in Silicon Valley. Kobe City aims
to gather many outstanding young generations from inside andoutside the country to trigger the flow of people and make Kobe
a city where it is easy to start business.

Start - up

・Mentoring
・Activities fund・Demonstration venue Produce growth-type entrepreneurs
 Trigger innovation in various fields

Dispatchofmentors

Local IoT Acceleration Lab Advanced Project ②：

23

Test-bed type lab【テストベッド型ラボ】■ Aizuwakamatsu City, Fukushima Prefecture
・ Aizuwakamatsu City aims to reinvigorate the region through high quality jobs with higher income than Tokyo byconcentrating the IT industry in the area, making use of the locational strength of the University of Aizu, a university
specializing in IT.
・ It is reviewing the following to establish the city as a mecca for data analysis and usage as “Smart City Aizuwakamatsu”.
① It aims to make open data obtained from sensors installed in the city, (E.g.: traffic information on public transportation,etc.）and create test-beds of streets so that companies can investigate the feasibility of using the data for their business.
② It is reviewing the construction of ICT offices which can be leased by IT companies and IoT related companies in
the region.
・ Accenture will set up an office at the site to intensively support the city’s efforts and leadthe collaboration. (Currently more than 30 companies are discussing collaborations）
ICT offices (image)【テストベッド型ラボ】【市のテストベッド化とICTオフィスによる産業集積】■ Kitakyushu City, Fukuoka Prefecture
・Kitakyushu provides support on the promotion of projects and business startups from various perspectives to IoT projects
contributing to resolving regional issues. Support includes knowhow and technical support, providing test-bed venues, financial
support, providing and running local information infrastructures, and support is provided through the “e-PORT Partner”
collaboration consisting of industry, academia, government, private sector, and financial sector.

・In particular, it is currently carrying a test-bed project led by YASKAWA Information Systems andHuman Media Creation Center/KYUSHU to create live and excitement in areas around the
Kitakyushu Stadium, which is home to the local professional soccer team “Giravanz KitaKyushu”(completed in March 2017).
・ Installing beacons and sensors in central areas, it aims to reinvigorate the region andresolve administrative issues by creating live and visualizing the flow of people.

Kitakyushu Stadium (image)23

IoT Lab Global Connection

24

Matching of Overseas IoT Ventures and Japanese Companies
•
•

•
•

Invite global companies to Japan and promote global collaborations of Japanese companies in order to construct eco
systems through the formation of IoT projects centering around Japanese companies.
First, IoT venture companies wishing to collaborate with Japanese companies will be broadly invited from three regions
ASEAN, India, and Israel. 164 companies applied, of which a total of 29 companies were selected through voting by IoT
Acceleration Lab members. Business matching was carried out between these companies and Japanese companies at the
CEATEC JAPAN venue.
The overseas venture companies set up exhibition booths in the venture areas at the CEATEC JAPAN venue.
Local embassies, experts, etc. were invited to briefings held on economic situation, etc., lectures were given on investment
opportunities and government support policies, and pitch meetings were held by overseas companies.

① Business matching (1:1 matching）
Combinations of overseas andJapanese companies whose seeds
and needs met were set beforehand,and matching was carried out for
20 minutes each.

41 Japanese companies andorganizations participated.

214 matchings were carried out.
② Exhibition boothOverseas ventures set up exhibition booths.

③ Pitching session

The Israeli Embassy in Japan and
NASSCOM talked about thecountry’s economic situation, andgovernment support.
Overseas companies appealed
their technologies in the pitchingsession.

This session as held for each of the
3 regions.
The audience totaled about

325 people

Date: Tuesday, October 4 to Friday, October 7, 2016
Venue: CEATEC JAPAN 2016 Hall (Makihari Messe)
Co-organizers: IoT Acceleration Lab, Ministry of
Economy, Trade and Industry (METI)
No. of participating countries: 29 from overseas, 41
from Japan.

IoT Lab Global Connection ①

25

List of Participating Companies
Israeland Details
of Support ～～ 第2回 from
IoT Lab
Selection
ファイナリスト一覧
・55 companies applied from Israel, of which 10 companies were selected after strict screening. In the future, collaborations will
be accelerated while using funds, etc.

Company name

Outline of project

Vayyar Imaging

3D image sensor capable of internaltransmittance, component detection.

Perytons

Cyber security of networks for IoT
terminals

Powertags

Low cost high precision tracking tags

Sol Chip Ltd.

Ultra-small solar power general panel
for IoT terminals

SCADAfence

Cyber security for industrial networks

HearTracker

Wrist band device for detecting
irregular pulse

3D Signal

Industrial equipment maintenancesolutions using ultrasonic dataン

Magna BSP

Traffic monitoring camera system withhigh precision/low mis-detection rate.

Voiceitt

Realizes smooth communication for
persons with speech impedimentusing vocalization and conversation
assist devices.

Details of support○NEDO grants
Joint project with Israel Industrial Technology
Research Development Center. Support projects
including R&D themes such as new energy,
energy saving, smart community, environment,
robot, machine systems, electronics/information,materials/nanotechnology, biotechnology, etc.
Provides funds with 50 million yen as the upper
limit per year. (Maximum 3 years)
Started from 2014 (Up to now held 3 public
offerings, next offering is not decided.)○ JST Funding (for University)
Joint project with Strategic International
Research Cooperative Program. Support
research themes on ICT for resilient society.
Provides funds with 18 million yen as upper
limit in 3 years.
Started from 2009 (Up to now held 6 public
offerings, next offering is not decided.)To find partners, the “Program to Introduce
Israel Ventures for Global Companies” by the
Israel Innovation Authority can be used.

IoT Lab Global Connection ②

26

List of Participating Companies
India
and Details
of Support～ 第2回 from
IoT Lab
Selection
ファイナリスト一覧～
・64 companies applied from India, of which 10 companies were selected after strict screening. In the future, collaborations will
be accelerated through Japan-India JWG.

Company name

Outline of project

Flutura Business Solutions
PrivateIoT platform for optimizing industrial
machinery.

Linkeddots Engineering
Solutions Private

Management of room entry/exit using
beacon, etc.

LOCANIX

Development of data analysis andmanagement system using telematrix
which is already being used for 90% of
ice cream deliveries in Gujarat.

SenseGiz

IoT platform centering around smart
home.

Preva Systems

IoT platform centering around
distribution, education, and healthcare

Stesalit Systems

Specializing in agricultural IoT.
Individual development from device toapplications.

Teevr Data Pvt

Cuts communication costs by 90% using
unique data compression technology.

Yuktix Technologies

Applied data analysis using large-scale
wireless network.

Srishti ESDM

Settlement system applying the IDs andbiodata of India already possessed by
the company.

TartanSense

Provider of serial image analysis using
UAV

Efforts made for collaboration○Japan-India JWG
This JWG was installed as a framework forpolicy dialogues participated by industry andgovernment from the viewpoint of further
accelerating collaborations between Japanand India in the IT and electronics industry
and strengthening competition of both parties
based on the ministerial talks between former IT
Ministry of India Mr. Shival and former Minister of
Economics, Trade and Industry Mr. Shigeki in
February 2013.The Japan side top is METI
Commerce and Information Policy Bureau Chief
while the India side is Communication and IT
Ministry Electronic Information Technology
Bureau (DeitY) director.
Consists of three layers:① Private sector meetings② Public and private sector meetings③ government level meetings.
Meetings held to date
1st meeting：November 2013 ＠Deli
2nd meeting：October 2014 ＠Tokyo
3rd meeting：November 2015 ＠Deli
4th meeting November 2016 ＠Tokyo planned.
Bilateral discussions between Japan and India on
hardware, human resources, and businesscollaborations

Scene of 2nd Japan-India JWG

IoT Lab Global Connection ③

27

List of Participating Companies
ASEAN
and Details
of Support～ 第2回from
IoT Lab
Selection
ファイナリスト一覧～
・45 companies applied from ASEAN, of which 10 companies were selected after strict screening. In the future, collaborations
will be accelerated through Japan-ASEAN new industry creation support projects, etc.

Company name

Outline of project

Glueck Technologies

Determines gender and emotions using
image processing technologies andoptimizes outdoor advertisements.

Electronic Nose

“Electronic nose” which imitates theolfactory sense of mammals including
humans, and identifies smell.

DF Automation & Robotics
Sdn Bhd

Manufactures mobile robots fortransportation which can be navigatedwithout guide tapes.

VP9 Vietnam Joint Stock
CompanyInexpensive high speed video streaming
using outstanding compression algorithm.
Awarded research prize by the World Bank.

Datamicron Systems Sdn
Bhd

Already have customers in seven countries
for patented large volume high speed
communication technologies.

Pipeline Network

Capable of high volume communication with
communication module using HetNet.

Reneon Technologies

Technologies for reducing power costs ofgeneral households and commercial facilities
and CO2 using energy management
platform.

Techcare Innovation

IoT balance board which can carry out
rehabilitation effectively.

SOPHIC MSC SDN BHD

Provides diverse solutions in data analysis
from manufacturing to agriculture.

Angkor E&C (Cambodia) Co.,Ltd.

Provides solutions for preventing car theft.
Capable of tracking from PC andsmartphone .

Details of support○Support creation of new industries
in Japan and ASEAN
To foster new industries, businessorganizations in Japan and ASEAN will work
together to promote corporate
collaborations (matching), policy
recommendations (deregulation, etc.).
To support these, governments will establish
systems, provide financial support, etc.

Joint verification projects, etc. will also be
carried out with local companies so thatbackbone and small and medium sizedcompanies in Japan can contribute to theadvancement of industrial structures of
ASEAN, and deepen economic cooperation
between Japan and ASEAN.

International Collaborations with IoT Acceleration Consortium•

28

The IoT Acceleration Consortium promotes collaborations with overseas in the IoT test-bed demonstrations
and in the review of standardization that follows. It aims to create and spread global IoT business by
Japanese companies.

•

On October 3, 2016, the IoT Acceleration Consortium signed an MOU with U.S. IoT related organizations Industrial
Internet Consortium（IIC） and OpenFog.

Industrial Internet Consortium (IIC)＜Outline of organization ＞
Established in March 2014 by fivefounding members AT&T, CISCO, GE,
IBM, and Intel. Aims to promoteindustrial IoT (Internet of Things).
＜Aim of MOU＞
Share demonstration environment and implement
demonstrations based on common architecture
understanding, to enable creation of efficient andeffective global IoT solutions.

OpenFog Consortium＜Outline of organization＞
Established in November 19, 2015 mainly
by ARM, CISCO, Dell, Intel, Microsoft, andPrinceton University. Aims to accelerate
open architecture and distributed(processing) computing development (Fogcomputing technology).
＜Aim of MOU＞
Promote collaborations in the demonstration andstandardization, etc. taking into account distributed
computing aiming at IoT solutions for fields which
particularly require real time and large volume dataprocessing.

Joint activities will include






Identifying and sharing best practices
Collaborating on test beds and research and development projects
Realizing interoperability by harmonizing architecture and other elements
Collaborating on standardization
Other activities to which both parties agree

Future Action Plans of NexGen IoT
Acceleration Lab(Discussion Topics)

IoT Acceleration Lab Challenges and Discussion Topics
How we lead it to platform in collaboration with large companies,
advanced technology ventures and global companies.
[Case example]○ Mechanism where venture companies and global companies with unique technologies
can join the projects carried out in Demonstration

Example of participation of Selection finalists in Demonstration
Liquid Marketing which won the Grand Prixof the first Lab Selection is participating in
the Demonstration “IoT-Based Service
Demonstration Project ”. Partnering with JTB,
this cutting edge project could not havebeen realized with conventional
collaborations between large companies.

30

IoT Acceleration Lab Challenges and Discussion Topics
How do we attract overseas companies to Japan[Case Example]○ Invite overseas companies test-bed demonstration in collaboration with IIC.

Collaboration with IIC and OpenFog
Conclusion of MOU with overseasorganizations.

Exhibiting Japan Pavilion at CｅBIT in Germany
Members of IoT Acceleration Labs to exhibit at
CeBIT in Hanover, Germany as Japan Pavilion.

Collaboration with overseas ventures and Japanese companies
Matching with companies in ASEAN, Israel, and India werecarried out this year.

31

IoT Acceleration Lab Challenges and Discussion Topics
How do we find the regulatory reforms and rules which will leadto proposals made to the government, not limiting efforts to
those by individual companies?
[Case Examples]○ IoT Regulatory Reform Selection
Setting up a framework for conducting surveys on ideas with economical
impact acquired from new businesses from the technical feasibility and legal
aspects, inviting demonstration themes for reviewing regulation and rules
which pose as challenges in the implementation of IoT, and carrying out
regulatory reform selection.
○ Regulations Customer Desk at private incubation facilities, etc.
Setting up customer desks at private incubation facilities, where consultation
meetings by lawyers, etc. are held, to activate the projects which have cometo a deadlock although they were promising business models due tohindrance by regulations.

32

IoT Acceleration Lab Challenges and Discussion Topics
To excavate leading-edge companies, how do we reassess the
project selection method and support method.
[Case Example]○ Award type support projects
Setting up award type supports providing the funds to the companies which
has been awarded for the best results on a theme.

DARPA Robotics Challenge
Contest for competing over the
performance of disaster relief robots
operated by remote control sponsored
by DARPA giving away prizes totaling
3.5 million dollars.
Participating by universities, privatecompanies, national research centers,
etc. from all over the world, tocompete and create innovation.

33

IoT Acceleration Lab Challenges and Discussion Topics

34

How do we lead to human resource development as the IoT
Acceleration Lab?
[Case Example]
Providing the opportunities for outstanding human resources to use their skills in collaboration
with Mitou Kaigi (Meeting of outstanding exploratory IT Human Resources), etc.
Creating environments for exploratory IT humanresources to play an active role
In last year’s Mitou Kaigi meeting, IoT
Acceleration Lab member companies and
Mitou Kaigi members were matched as a trial.
As a result, opportunities for members to play
an active role in unexplored areas were bornand members were able to secure outstanding
personnel.

Foster personnel linking software, hardware,and businessAs many IoT startups are launched by software engineers,
they come to a bottleneck in hardware development. There
are very little private sector efforts linking software andhardware.

Foster AI engineers

Foster data scientists

Use working space where AI engineers gather and offer
advise from non-Japanese famous researchers

Setting up a framework that enables to evaluate skills ofdata scientists, such as Big Data Analysis Contest

IoT Acceleration Lab Challenges and Discussion Topics

35

How do we tie up with support activities for IoT startups in private
sector ?
[Case Example]○ Collaboration with private sector startup support
Linking with Selection as step-up for entrepreneurs developed with startup supports fromprivate sector.

Docomo Innovation Village

KDDI∞Labo

III / Mirai

Main activities○ Village alliance
Creates joint services by DoCoMoand venture companies.
○ Village social entrepreneurs
Support for social entrepreneurs(advice from specialists)○ Village community
Provide open innovation communities

Main activities○ KDDI and partner companies support
innovative ideas of entrepreneurs andventure companies from seeds to start
stages.
○ Provides the environment for developing
programs aiming for commercialization,
also support mentoring by KDDI
employees, advice and management byspecialists.
○ After the program ends, implement
funding and business alliance with KDDIaccording to the feasibility ofcommercialization, etc.

Main activities○ 異業種連携の事業開発コンソーシアムIIIによるインキュベーション・アクセラレーションプログラム「未来」の運営（専門家によるビジネスプランの作成支援・メンタリング等）○ ベンチャーと大企業とのネットワーキング・ビジネ
スマッチング・共同研究・新規事業開発の推進
およびVCとのマッチング○ イノベーションに即した法制度・ルール整備を行う為の政策提言・官民プロジェクト政策提案

IoT Acceleration Lab Challenges and Discussion Topics

36

How do we link each activity of the IoT Acceleration Consortium andIoT Acceleration Lab?
[Case Example]○ Setting up mechanism to review the cases of uses of Selection finalists with priority in Data
Distribution Promotion WG○ Setting up mechanism to link IoT Acceleration Lab Selection with the Selection carried out
by Local IoT Acceleration Labs

ユースケースの提供

ＩｏＴ推進ラボ

連携イベント開催（成果の普及）データ流通促進ＷＧ

ルールやガイドラインの提供

How do we provide test-beds (servers, systems, data, actual fields,etc.) that allow companies to challenge IoT business?
[Case Example]○ Carry out Selection of test-bed users to participate, inviting test-bed providers

IoT Acceleration Lab Challenges and Discussion Topics

37

How do we use and expand the results of Demonstration?
[Case Example]○ Collaboration with Demonstration and private sector platform.

To promote open data of companies and municipalities, there is aneed for efforts which allow people to feel the value of data and new
methods of using the data.
[Case Example]○ Holding workshops to provide the opportunity to discuss about new data usages, gathering
information on open data by companies and municipalities.

How do we provide more information inside and outside thecountry?
[Case Example]○ Video distribution of the project results of finalists, etc.

今年4月に支援委員ウド
ヴォルツ氏の協力でＩｏＴ推
進ラボの政府広報動画を配信

Provisional Edition
Reference Material #1

IoT Acceleration Lab
2nd Selection Meeting for Innovative IoT Projects

IoT Lab Selection

List of Supported Projects

0- Contents ① 【Grand Prize】 UniFa Corporation [Supporting the digitalization of services for monitoring the premises of nursery schools ２
centering on the monitoring robot MEEBO]② 【Second Prize】 Phoenix Solution Co., Ltd. [World’s-first RFID tag that is readable even through the metal to which it is
attached]３③ 【Second Prize】 Zenrin Co., Ltd. [Demonstration project concerning information on three-dimensional aerial maps toward
the realization of safe drone flight over city areas]

４④ 【Special Jury Prize】 exMedio Inc. [Technology for recognizing ophthalmic disorders using images and data from medical
interviews]

５⑤ OryLab Inc. [Realize a community for conveying our existence using avatar robot OriHime]

６⑥ GNN Machinery Japan [Raw concrete quality continuous management system (Smart Agitator)]

７⑦ DeNa Co., Ltd. [Realize personal shopper service for reinforcing regional consumption eco system]

８⑧ smart-FOA [IoT age data flow information infrastructure “FOA system” for boosting the manufacturing industry in Japan]

９⑨ Konica-Minolta Inc. [Home medical care support system by non-contact respiratory sensing]10⑩ Aerosense Inc. [Realize safe, simple, and high precision 3D modeling operations]

11⑪ JVC KENWOOD Corporation [Build health management and remote diagnosis service by self recording breathing sounds] 12⑫ Space Market, Inc. [Realize regional revitalization by space sharing business and create micro-entrepreneurs]

13⑬ ABEJA, Inc. [Research and development of data system capable of comprehensively managing complicated data for IoT
society]14

GrandPrize

UniFa Corporation- Supporting the digitalization of services for monitoring the premises of nursery schools -Outline of Project
The company aims to resolve the problem of lack of nursery school teachers which is a social issue, andsupport activities at nursery schools using smartphones/sensors/robots, etc. so that even inexperienced
nursery school teachers are able to take care of children safely.
Specifically, the company is currently developing services such as the digitalization of handwritten
documents which tend to pose as huge work burden (Communication notebook/afternoon nap checktable, temperature sheet, etc.) and support for monitoring of children during their afternoon naps whichhave the risks of fatal accidents (using video camera/smart bed sensor).
Nursery School Children Monitoring Concept

Outline of Required Support
・ Financial support（Public support for technologicaldevelopment, etc.）
・ Escort-type support such as guidance, advice bymentors.
・ Deregulation（Legal position of digitalization ofrelated documents, etc.)

Future Vision
By realizing both high quality nursery care and work
efficiency, help resolve values problems faced bynurseries such as lack of nursery school teacher.
Furthermore, by analyzing data related to nurseryschool children, advanced data usages such as
disease prevention, etc. will be possible.

Monitoring camera
Digitalization of
paper documents

Smartphone inclassesConstant
videoing

Movements ofchildren

Varioussensors/robots

Child
Monitoring AI






Communication
notebook
Temperature
Afternoon nap
Growth record
Individual
photo/video





Talk
Play
Automatic
photographyBreathingrate
Heartbeat

Digital thermometer Smart thermometer

Children

Smart bed

Detect warning signs in each child, and provide nursing advise
equivalent to that of professional nursery school teachers[Values for nursery school]*Data linkage with ?nursery schools aroundthe country Signs of cold
 Prevention of accidents such as SIDS Post-verifications after accident at thenursery school[Values for parents]Monitoring of child’s conditions
today
Child care according to growthBooking sitters based on cold signs

2SecondPrize

Phoenix Solution Co., Ltd.

- World’s-first RFID tag that is readable even through the metal to which it is attached -Outline of Project
Phoenix has developed special metal tags which can be read using normal readers, especially behind metals
and in laminated states (no batteries needed). These tags are expected to improve work efficiency and reducemanagement costs in industries using high volume of metallic materials such as manufacturing, construction, lease,
distribution, infrastructure and facilities, etc. (Examples of uses: metallic pallets, basket carriage, gas cylinder,
construction scaffold, etc.) The company aims to further expand use by application to supply chains and linkage
with sensors, drones, etc. This is the first technology of its kind in the world. By developing various types of tags,
the companies is aiming at extensive dissemination around the world, and realizing the IoT of metal products.

Outline of Required Support
・ Financial support（Public support for technologicaldevelopment, etc.）
・ Escort-type support such as guidance, advice by mentors.
860MHz-950MHz (UHF)Future Vision
The global IoT market is expected to be 400 trillion
yen in 2020, with 30~50 billion equipment andthings connected to networks. Thus efforts will bemade to expand this technology using open
platforms and sweep the global market in ashort period of time.

Cannot readMetal

Can read

Metal

3

Second
Prize

Zenrin Co., Ltd.

- Demonstration project concerning information on three-dimensional aerial maps toward the realization ofsafe drone flight over city areas -Outline of Project
The company is aiming to develop an automatic drone flying support system as an infrastructure forrealizing “contact flight in manned regions such as city areas, etc.” as the ultimate usage of drones.
(Level 4)
In this project, the company aims to realize “3D maps of the sky” including recommended flight routes
and obstacles, as well as develop technologies enabling safe drone flight in manned regions by he real-timetracking of drones deviated from their routes by gathering and analyzing drone probe information.

Outline of Required Support・Financial support (Public support for technologicaldevelopment, etc.）

Future Vision
・Establish de facto standards in the guidance/control/
management fields serving as infrastructure for industrial
use of drone.
・Radically expand the scope of use of drone and realize
innovative new services by realizing contact flight in city
areas, etc.

Automatic drone flying support system[Probe gathering/analysis]
Grasp route deviation state and determine
causes of accidents by probe cloud
analysis.

[Development ofcommunication technologies]
By mounting SIM to drones,
determine position at semirealtime and remote control[Creation of 3D map of the sky]Prepare map information fordrones such as recommended
flight routes and obstacles, etc.

4

exMedio Inc.

Special JuryPrize

- Technology for recognizing ophthalmic disorders using images and data from medical interviews -Outline of Project
For non-ophthalmic disorders, the company aims to develop AI enabling automatic identification anddiagnostic support of eye diseases using images and medical examination data, and mount tomobile apps “Memiru”.
Presently, non-ophthalmologists are forced to carry out eye diagnosis in some situations such as remote islandand places, hospitals with single departments, disaster areas, etc., and the high misdiagnosis rate* is a problem.
exMedio is currently developing skin disease automatic identification AI boasting high identification
accuracy, and aims to apply this technology to eye diseases in this project.

Outline of Required Support・Financial support（Public support for technological development, etc.)
・Escort-type support such as guidance, advice by mentors.

Future Vision
Through diagnostic support using AI, it will be possible to reduce
misdiagnosis rate by non-specialist doctors, and improve patient QOL.
In the future, the scope of application will be expanded to other medical
departments and the service will be provided to developing countries
and poor regions, etc. as a low cost diagnostic support technology.
*There are research reports indicating that 84% of diagnosis results of non-ophthalmologists andophthalmologists are different. BMJ 1988:1162-1167

5

OryLab Inc.
- Realize a community for conveying our existence using avatar robot OriHime -Outline of Project
OryLab has developed an avatar robot OriHime capable of “conveying existence”. It serves as anavatar for going to places where we cannot go due to physical reasons such as Lou Gehrig's disease or
distant places when posted far away from home, or meeting people we cannot meet. Even on the bed, we
can learn, work, participate in community through OriHime.
Presently, it is used for patients with difficult to cure diseases, disabled persons, and for those working at
home such as women taking of their children, etc.

Outline of Required Support・Financial support（Support for technologicaldevelopment for strengthening “sense of presence”.)
・Expand scope of support of national grant projects.

Future Vision
In the future, by allowing the robot to be placed anywhere infacilities or at home, it will be possible to construct a presence
infrastructure in which anybody can virtually go to the required
places anytime and carry out natural communication withpeople in far away places, learn, work, etc.

6

GNN Machinery Japan- Raw concrete quality continuous management system (Smart Agitator) -Outline of Project
The company has developed a continuous ready-mixed concrete quality management system (Smart Agitator)
capable of high quality control by sending the state of ready-mixed concrete being transported (hereafter readymixed concrete ) together with car information such as GPS position information, drum rotating speed, drum innerpressure, etc., to the cloud server at real-time.
Presently, ready-mixed concrete product inspection is manual sampling inspection by operators at the site with certain
level of skills. As a result, quality is inconsistent, and there are problems such as needing to secure such matured
workers.
The use of this system realizes automatic measures that does not need human assistance, and management ofready-mixed concrete quality for all products. It helps resolve the challenges faced in the ready-mixed concrete andconstruction industry such as reducing work time by 40% in addition as well as ensuring safety.

Outline of Required Support
Financial support（Public support, funds, etc. for service development)

Future Vision
With the problems faced in the ready-mixed concrete and constructionindustry being increasingly resolved by IoT (improved inspection efficiency ,securing of time-series management and traceability for all products,
securing of personnel, etc.), Japan is currently facing a construction rush
towards the 2020 Tokyo Olympics/Paralympics. This technology is expected
to contribute to the maintenance of high quality construction technologies.

7

DeNa Co., Ltd.
- Implementation of a shopping agent that strengthens the local consumption eco system -Outline of Project
By cooperating with the major distribution companies, the company aims to create a service that connects
local stores with consumers via the use of self driven vehicles.
Together with the research and development of self driving, they aim to create a system where various data such as
the store selling the goods, the delivery address, order time and local traffic information can be analyzed via
artificial intelligence to create the most effective delivery route possible.
It should be possible to solve the issue of disadvantaged shoppers, revitalize local shopping districts, increase
the efficiency of delivery truck routes and avoiding traffic congestion thereby decreasing CO2 emissions.
With a locally based EC network constructed to strengthen local consumption, it will become a new axis offormation within the EC world.

Outline of Required Support
・ Financial support
１．Development of a highly efficient delivery
planning algorithm
２．Development of technology that will detect themost efficient vehicle placement for goods pickup
・ Deregulation (Definite implementation of publicprivate talks (2015.11) towards self driving vehicles)

Future Vision
・ Stress free delivery becomes possible which takes into consideration people’s movements and daily lives,with pin point delivery of goods at designated times
and locations.
・ Elimination of disadvantaged shoppers andrevitalization of local shopping districts, contributing
to resolving local issues.

Service Flow

Obtain goods from Store goods fromlocal stores online shops in storage box

Confirm delivery
time and address
for the goods

Send notification
before delivery

Receive the
goods

8

smart-FOA- IoT age data flow information infrastructure “FOA system” for boosting the manufacturing industry in Japan -Outline of Project
It is predicted that with the advance of IoT, the information systems at manufacturing locations will get mixed
together, making it more complicated to connect data together. The ‘FOA System’ is able to resolve these
problems via it’s capability to consolidate information from various systems related to ‘Events’ (such as‘Defective product detected’). With this event driven flow type data system, it has become possible for people onsite to people in management to “enable to understand”* what is happening at manufacturing locations.
Furthermore it is possible to retrofit current systems, allowing small and medium sized companies to make a small
start. In the future the ‘Smart-FOA Platform’ system will be developed so that with standard API an open platform
can be achieved, which can be expandable without the need to stop the system of various services.

Outline of Required Support
・ Financial support (Public support for technologicaldevelopment, etc.)
・ Escort-type support such as guidance, advice bymentors.

Future Vision
To broadly permeate the domestic manufacturingindustries with IoT together with small and medium
sized companies that find it hard to incorporate large
scale systems, as well as creating a data platform forthe manufacturing industry in association with Ciscoand other large Japanese vendors, that can be
expanded globally.

Conventional System
Library-type System
Accumulating world

FOA System
Newspaper-type System
Throw away world

Flow

Stock

Scatteredphysical data

Appropriate
for data mining
データマイニング向き

Background,explanation data forevent on-site (small
data construction)
Appropriate for swift decisions,
迅速な判断・仮説検証向き
hypothesis verification

9

Konica Minolta, Inc- Home medical care support system by non-contact respiratory sensing -Outline of Project
The number of nursing homes and ‘home care patients’ staying at home is increasing yearly, with the current
540,000 patients estimated to increase to 1,900,000 by the year 2030. Also, it is assumed that with this thenumber of ‘nursing staff’ for these home care patients will drastically increase.
As a result of this, it is imperative that a system be constructed that will decrease the burden of home care
physicians and prepare ourselves for an aging society.
This project aims to create a home healthcare platform using a unique microwave sensor as its core technology,
that is capable of capturing detailed breathing and sleep information without direct contact, and together
with measured data for body temperature, blood pressure and such, it will be able to confirm the safety ofpatients as well as monitor the quality of their sleep that will lead to more effective home healthcare.

Outline of Required Support

Homecare support system via use of non-contact respiration sensing
Homecare support Cloud・Financial support (Public support fortechnological development, etc.)

Daily Patient
information

Patient

Future Vision
・With the increase in quality of home healthcare,bring to fruition an improved quality of life for
elderly people as well as terminal carepatients.
・Furthermore, secure the sustainability of ahome healthcare system that will lead to theimplementation of reduced medical costs aswell as a reducing the burden on home care
physicians.

Open platform where medical
data can be shared and utilized

Call center
Respiration detection
sensorHome examination request Sort the information

Acquisition of respiratory
data via non-contact
sensing, as well as bodytemperature, blood pressure
information from the patient

Based on the pre-designatedprocedure as set by aphysician, a homeexamination request will besorted and executed by thecall center

Confirm the condition
via telephone only

Emergency examination
by a home care physician Notification from thecall center will bereceived only when a
Hospitalization (ambulance)home care physician’s
attention is required

Reduction of burden on home care physicians can beachieved, promising increase in home care
physicians

10

Aerosense Inc.
- Realize safe, simple, and high precision 3D modeling operations -Outline of Project
The company has technology that utilize drones that take areal images to make high precision 3D models, optimizing
the work around civil engineering and topography surveys as well as construction designs. Specifically, it has become possible
to decrease the number of employees and man hours for civil engineering surveys to one third of the conventional
number (for a 90Ha survey, it will take around 2 weeks compared to the conventional duration of 6 weeks). By further
evolving this, it has become possible to automate the survey marker position timing and position measurements, aswell as any revision work on the marker from the filmed images, allowing for the most automated work schedule aspossible, and with the use of these drones for civil engineering surveys a further reduction in manpower and better work
efficiency (a 90Ha survey can be done in around one week) has become feasible.

Outline of Required Support
・ Financial support (Funding for technologicaldevelopment, etc.)
・ Establishment of rules (a sharing of views within similar
companies towards a standard for public surveys, reevaluation of export restrictions etc.)

Future Vision
・ To be the forerunner of IoT within public works,
being able to respond to the lack of workers causedby the decreasing birthrate and aging population.
・ To become the foundation of areal imagery 3Dmodeling with broad application possibilities such as
tourism and construction; feasible for overseas
development also.

RTK-GPS internallyequipped anti-aircraft
marker11

JVC KENWOOD Corporation- Build health management and remote diagnosis service by self recording breathing sounds -Outline of Project
The company aims to offer healthcare for the estimated 8 million domestic asthmatic patients with a service thatrecords their breathing sounds, allowing them to check their health via cloud information.
They are targeting the implementation of software being developed, that is capable of detecting abnormalities from therecorded breathing sounds.
Furthermore in the future, with the combination of AI (machine learning) the recorded breathing sounds together withrelated information (physical condition from recorded asthmatic diaries, seasons, time, associated symptoms, weather,treatment details, medication situation, contents of daily life etc.) that can be combined and made in to a model whereby theseasons, time and weather forecasts can be connected to undertake a more personalized symptom prediction for patients.

Outline of Required Support
・ Financial support（Funding, etc.)
・ Deregulation (Clarification of the legal
positioning of a breath recording devise)

Future Vision
To increase the service from healthcare forasthmatic patients, to a telemedicine andhomecare service via the use of breathing sounds.
Contribute in the reduction of medical costswith appropriate health care.
New big data business via the accumulation ofsounds.

Service image illustration
weather data

User
Breathing sound/ healthcare app+ exclusive
mask]

barometric data

Location data

breathing sound data
Daily life noise

Saved data /AI (machinelearning)

PhysicianPrevious data

Data accessand advice

12Space Market, Inc.
- Realize regional revitalization by space sharing business and create micro-entrepreneurs -Outline of Project••

Operation of a platform that matches hosts with unutilized spaces with guests looking for locations.
Together with meeting rooms etc., the company offers unique spaces such as shrines and temples, ruined
buildings, major’s offices and remote islands. By offering recommendations for unutilized spaces to owners andbringing them together with users, it has successively been able to monetize unutilized real estate.
By refining the recommendation function via the use of AI, they are aiming to design and implement asystem with a compensation scheme whereby hosts and guests can use it with peace of mind.

Outline of Required Support
・ Financial support (Public aid to upgrade the service)
・ Escort-type support such as guidance, advice bymentors.
・ Deregulation（Institutional handling of compensation
schemes)Borrower

I want to do a sales meeting

・Location search ・Support gatheringof returns
・Event planning ・Catering

Future Vision
・By progressing collaboration with municipalities, solve
various social issues such as empty houses and deficit
administration of local government facilities. At the sametime, contribute towards increased tourism originating fromthe unique locations. Build successful examples as rolemodels and expand nationwide.
・Contribute towards regional vitalization by offering apioneering example of a sharing economy involving
municipalities.

LenderI want to increase
the occupancy rateof the space
I want to monetize
the available space

I want toexercise

I want to throw a party

・Space management ・Producing spaces
・Reservation account ・Marketing support
management
・Product sampling・Accounting agent
・Management
・Photographing
consulting

13

ABEJA, Inc.
- Research and development of data system capable of comprehensively managing complicated data for IoT society -Outline of Project
The advancement of the already developed data base utilized in artificial intelligence data analysis platforms. With
the intention of maximizing sales at retail stores, problems arose as adjusting and formalizing the use of current data
was deemed insufficient. With various information on employees, the location of customers and their movement, productdisplacement, stock situations etc. being a factor in influencing sales, it is necessary to comprehensively manage theassorted pieces of data that is not adjusted or formalized, and use artificial intelligence technology to create a database and make simplified links possible. Starting with existing retail store customers, the project will develop an artificial
intelligence data analysis platform that can be used for a variety of industries that plan to advance the use of IoT.
[Sensing/ visual processing/machine learning][Data analysis platform][Forecast and visualization based on analysis results] [In-use effect]

Actual retail store data
People movement

Chronological
data analysis
Managecomprehensively
linkable database

Point of sale
sales

Assorted
data

Artificial
intelligence
technology

Elimination of waste inlogistics, production

Efficiency of management andoperation at retail stores

Advanced
usage of data

Creation of a high quality
customer experience

Esixting duties

Outline of Required
Support・Financial support
Database technologicaldevelopment
・Deregulation/Establishment of rules
1.Protection of personalized data
2.Data ownership
3.Portability of data

Future Vision
・To become a role model that increases productivity via the use of
artificial intelligence, used in a variety of industries (manufacturing,
healthcare etc.), and become a data platform creator* with the accumulationof this business data.
・Being adopted in many countries in Asia, it is used not only in one
location (such as an office or shop) but spreading over many locations andeventually covering regions with collected data, making it possible tocreate value with data analysis for cities and the region as a whole.

14

Implementation State of
IoT Lab Demonstration(IoT related demonstration budget)by Theme

- Contents １．Social System Promotion projects for promoting IoT
FY2015 Supplementary budget: 1.12 Billion yen
FY2016 Initial budget: 2.04 Billion yen/Supplementary budget: 1.1 Billion yen
FY2017 Requested budget: 2.24 Billion yen① [Manufacturing] Japanese-Style Smart Factory Model Case Demonstration Project・・・・・・・・・・・・・・・・・・・・ 3② [Infrastructure] New Industry Model Creation Project in Regional Social Infrastructure Field・・・・・・・・・・・ 4③ [Industrial safety] Independent Safety Measures Advancement Project (Oil Refinery)/
Chemical Plant, etc.・・・・・・・・・・・・・・・ 5④ [Government] New Index Development Project Using Big Data・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・ 6⑤ [Medical/Health] Health Information Infrastructure Establishment and Usage Promotion Project・・・・・・・ 7
Health Promotion Model Project Using Life Data Analysis・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・ 9⑥ [Distribution] Drone IoT Demonstration ・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・ 10⑦ [Service] IoT-Based Service Demonstration ・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・ 11[New Projects]⑧ [Smart home] Data Usage Environment Establishment Promotion Project for Smart Homes・・・・・・・・・・ 12⑨ [Aircraft] Aircraft System Advancement Project for Supporting Piloting・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・ 13

２．Smart Mobility System Research & Development and Demonstration Project
FY2016 Initial budget: 1.88 Billion yen
FY2017 Requested budget: 3 Billion yen ・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・・ 14

①[Manufacturing] Japanese-Style Smart Factory Model Case
Demonstration ProjectThis project aims to establish infrastructures which enables Japan’s manufacturing industry to make visible
the situation of production sites, and deal flexibly with market needs that change quickly.
Specifically, it will reflect information on the operations of the different types of production machines
and facilities in production management and quality management, etc., and create common formats fordata transmission for realizing optimum production, inventory, distribution, etc.

[Project background][Project image]【IT infrastructure/software】
ITinfrastructure/
softwareOS

Middleware

Database

AI【Solution】【Manufacturing site/Hardware】

Controller

Sensor【Implemented by】
Hitachi, Muratec, Mitsuiwa(Machine(Machine tool,
etc.）

etc.

Example of solutions using manufacturing site data
Production
Management

Monitoring offacility

Optimization of
distribution, etc.

Data can be centrally managed without sophisticatedintegration

Common format
Optimization of
production site

Common for large companies/small and medium size companies(Examples)
Predictive
Productionetc.
maintenanceoptimization

Quick changes inmarket needs

 For this reason, common data formats will be established as an
infrastructure for linking factories and companies and providing such
solutions quickly while making use of the strengths of the
manufacturing site which serves as Japan’s forte, and create example
of cutting edge efforts.

Optimization of wholebusiness When the manufacturing industry value chains are classified into
“manufacturing site/hardware”, “solutions”, “IT
infrastructure/software” layers, the solutions layer is expected to
become the source of profits in the future and the main battlefield ofcompetition.

Accumulate data from various machines at the
production site such as robots machine tools,
controllers, etc.

3② [Infrastructure] New Industry Model Creation Project in Regional
Social Infrastructure Field• The efficient and sustainable business operations in the field of regional social infrastructure is amajor social issue. Amidst the dwindling population, declining birthrate, and growing silver population,
regional infrastructure businesses are facing reduced effects of investments with the aging of facilities, excess
facilities, and reduced demands.
• In such social infrastructure fields, this projects aims to carry out standardizations for applying IoT to a seriesof business processes (facility management, operational management) to enhance operational efficiency
through the use of IoT. This will help enhance the efficiency of routine operations as well as realize
optimum asset maintenance management.
• In 2016, the specific effects of IoT for waterworks will be demonstrated, and the effectiveness of using
IoT in the social infrastructure field not limited to waterworks will be verified.
[Details of implementation]
１. Diagnosis of deterioration signs
Automatic
By standardizing data processing, integrate
and analyze difference data such as operations
data, asset data, etc., to enhance management
efficiency and resolve vendor lock in.
WarningSign
予兆診断
Diagnosis
アプリAppsAsset
Management
資産運用
Apps

アプリ

Request for gathering of

必要データの収集依頼
required data

集中監視制御Concentrated Monitoring
Control Apps
アプリ

水運用
Waterworks
アプリ
Apps

Use data accumulated from various facilities
and devices to automatically detect signs ofmachine deterioration

Water Quality
水質管理
Management Apps

アプリ

Standard
API
標準API
Demonstration
System: Effective evaluation tool
実証システム：効果評価用ツール

Commonparts
共通部品

Function
機能

変換

Agent

機能

Agent

Water intake facility

Notification of
状態変更の通知change in state

Broadcenter
広域センター

Addition of
変換
機能
意味付け情報の付加
meaning information

Agent

Change変換

Function
機能

Water purification
plant E

Agent

Change変換

Function
機能

Agent
Monitoring

Company
facility
B社製B設備Image of standardization

Moduleconforming to standard API
標準APIに則したモジュール
Standard API
標準API

Water supplied area W

Discontinuation of inefficientwater intake facility

Improvement of facility
usage rate by integration

Standard
API
標準API

Effective
evaluation tool
効果評価用ツール

Water distribution
lake GMid and long term
demand forecasting

Water intake facility
B(small scale)

状態監視of state
Company
facility
C社製C設備Z社
Company
Z

Use
利用

Demanders

Water supplied area V
Water intake facility
A (medium scale)

Renewalof agent
Agent更新

Data

Company
facility
A社製A 設備

Water distribution facility

Centralize information on operations ofmultiple facilities located over a wide area andwater supply information and realize efficient
operations of each facility through monitoringof operations and remote control.
運転監視
アプリ

Agent管理Agent
control

データの収集
gathering

System X
システムX

Water purification facility

3. Efficient operations

Operations Monitoring
Apps

Other platform linkage function
他プラットフォーム連携機能

Standard
interface
標準インターフェイス
Change変換

Using information such as change in population,
operations information, and maintenanceinformation, perform simulation ofreorganization of facilities and equipment tosupport efficiency facility renewal plans.
※LCC：Life cycle costs

detection ofoperation andequipment
malfunctions

Automatic learning ofrelation between data

KPIKPI測定モジュール
measurement module
AI, deep learning
AI、ディープラーニング

データレイクData lake
データクレンジング
Data cleansing

2. Efficient asset management taking
into account LCC

Input
countless data

Water distribution
lake H

Water supplied area X

Water purification

Module conforming
標準APIに則した
toモジュール
standard API

Company
X社 X

SCADA

Enhancement ofexisting facilities

Water intake facility
C (large scale)

b浄水場

a浄水場
facility aWater purification
facility b

Company Module conforming
標準APIに則した
Y
Y社
toモジュール
standard API

GW

Water supplied area Y

X社 標準APIに則した
to standard API
モジュール
PLC
Company
X

System Y
システムY

Water purification
plant F

Water intake facility
D (small scale)

PLC

Water distribution
lake Ito standard API
Y社 標準APIに則した
モジュール
PLC

Module conforming

CompanyY

PLC

Module conforming

Water supplied area Z

PLC

PLC

[Implemented by] Mitsubishi Research Institute, Hitachi, NTT[Water suppliers] Iwate Chubu Waterworks Organization, Osaka Waterworks Authority, Kagawa Waterworks, Takamatsu City Waterand Sewage Bureau, Kagawa Prefecture Waterworks Setup Preparatory Committee, Hachinohe Regional Water Supply Authority

4

③[Industrial safety] Independent Safety Measures Advancement
Project (Oil Refinery)/Chemical Plant, etc.）• analyzing realtime operational data (temperature, pressure, flow, etc.) constantly acquired using
sensors, etc. in the area of industrial safety measures (oil refinery, chemical plants, etc.)• The efficiency of such new mechanisms will be checked and the mechanisms will be incorporated in new
regulatory systems of the High Pressure Gas Safety Law (Super Certified Business System) ,implementation of IoT, etc. will be promoted.

[Example of demonstration]

1. Constant monitoring of operations (Early discovery
of abnormalities and warning signs)
・”Abnormal” alarm

old ・Long detection time
→ Large effects on
production

・Alarm indicating “different
Newfrom normal state”
・Short detection time
→ Small effects on production

Steady Signs
Upper limit alarmState management index
Early discovery
Lower limit alarmTime elapse

2. Construction of piping corrosion prediction[Regulatory system realizing advanced independent
safety measures]Super certified businesses

Certification requirements (Added) Regulatory incentives
according to safety
・Use of IoT, big data, etc.
・Implementation of advanced risk
assurance ability
assessment
・Evaluation of safety assurance
・Approval of new
ability by third parties, etc.
inspection methods
Organically linkdemonstration
Certified businesses
・Easing of inspection
and regulatory
frequency to enables
Certification requirements
systemlong continuous
・Installation of specialist
organization related to safety
operations
measures
・PDCA
・Increase ”notification”
・Thorough education and training, of minor changes inetc.

Accumulate/analyze data related to inner side piping corrosion at
oil refineries, etc. and data on outer side corrosion below heatinsulating material in chemical plants, and construct prediction
models for early discovery of abnormalities of facilities and equipment.

Officefacilities, etc.

[Participating companies]
1：Tottori University, Hitachi, Yokogawa Electric, NEC, etc.
2：JX, Idemitsu, Cosmo Energy Group, Showa Shell Sekiyu, Tonen General, Taiyo Oil, Fuji Oil Company, Asahi Kasei, Sumitomo
Chemical, Maruzen Petrochemical, Mitsui Chemical, JSR, Nippon Shokubai, ZEON, Mitsubishi Chemical, Showa Denko, Daicel, Denka,
Tosoh, Nippon Steel and Sumikin Chemical

5④ [Government] New Index Development Project Using Big Data
• This project aims to use big data such as POS data which private sector companies posses, SNS data,etc., accumulated in cyber space, to complement existing governmental statistics, and develop new
indices for accurately determining economical trends and reporting them promptly[Details of implementation]
In 2016, POS data will be procured from retailers, limited to the “home appliance” field, and demonstrations will be carriedout first for the following.
・Development of new indices which can substitute/complement existing government statistics (survey of dynamic statistics
of commerce).
・Development of new indices with high added value by linking big data such as POS and SNS, etc. and government statistics
data, etc.
In addition, hold the “Expert Committee on Use of Big Data”, and review details of the establishment of regulations/rules
required for the use of big data in government statistics.

[Implementation system](1)
Demonstration project
Government
statistics,
etc.

Data gathering/processing/supply・GfK Marketing
Service Japan

New index
development/
evaluation/verification

・Intage, Intage
Research,
Intage Techno Square(3)
Summary
anddisseminat
ion ofresults

Illustration of Survey slip Submission in Future
Present
Survey slip submission(Post or online)

・Hotlink
・NTT Data①Task setting/signing ofcontract
・NomuraSecurities

・NTT Data
・Distribution Economics Institute of Japan
New index
calculation/
Mounting and
Supply ofdisclosed services

Task setting/evaluation/
progress management,
etc.

(2)
Committee
WG
comprehensive survey②Running of
Evaluationcommittee③Guidance/
advice/progress
management①Managementof expert
committee/WG②
Comprehensive
survey①Summaryof results②
Disseminati
on ofresults

・IT system vendors, etc.
(Review based on progress of demonstration
projects, etc.)

Re-subcontracted party selected from public offering

Ministry of
Economy,Trade andIndustry
METI

Future 1

Processed
POS data submission

Surveysubjects① or ②can be selected

Future 2
Processed
POS data

POS data submission

Submission
service

Restoration ofanalysis results

PwC Arata Limited Liability Audit Corporations

6⑤ [Medical/Health①] Health Information Infrastructure Establishment
and Usage Promotion Project This demonstration project aims to specifically enhance symptoms through intervention for patients with mild diabetes
by companies, insurers, medical practitioners, etc. using health information etc. As part of these efforts, the required
data formats, health information collection methods using IoT terminals, and intervention methods for
subjects are verified.
 In particular, given that the format and definition of health information differ by equipment and manufacturer,
and the smooth accumulation and use of information is difficult, data formats will actually be devised and used.
This project will aim to promote services using health information, etc. Accumulated from IoT equipment.

[Image of Project] Monitoring based on health related[Subjects]

Diabetes

Healthy persons/borderline
persons
No. of subjects:
90 million

data/alert changes in symptoms

Outpatient phase
No. of subjects:
2 million
Annual medical costs:
400000 yen/person

Dialysis phase
No. of subjects:
100,000
Annual medical costs:
5800,000 yen/person

Medicalcheckup data

Receipt
data

Entrepreneur/
Insurer

医療機関等
Industrial
physician,public health[Mainly used health information, etc.]
Through demonstration projects and review meetings (alsoparticipated by Cabinet Secretariat, Ministry of Health, Ministry ofInternal Affairs and Communications) installed under the Next
Generation Medical ICT Infrastructure Council, establish rules suchas data exchange regulations (data format).
（Examples of data）① Information required for monitoring of daily life
…No. of steps/activity volume (Measure with wearable equipment such as
pedometer, etc., smartphone, etc.)② Information for alerting changes in symptoms (Measure at workplace, etc.)…Weight, blood pressure, HbA1c, blood sugar, etc.
Accumulate these health information, test information, etc., together with information on
date/time of measurement, measurement equipment, testing organization, testing method,etc. from the viewpoint of assuring data quality, and define the format of about 60
information items.

Share
information
as required

ClinicaldoctorIntervene
and support
behavioral
changeSubjects
Self-monitoringof daily actions

Health related
database
Accumulate health data such as
number of steps taken, activity
volume, weight, blood pressure, etc.

7

（Reference)

METI 2015 Supplementary Budget “New Industry Models Creation Infrastructure Establishment Project for Promoting IoT”

List of consortiums selected for project for promoting behavioral modification using individual health and medical care information possessed by companies, insurers, etc.

Type

Leadingcompany

Leadingcompany

Leadingcompany

Leadingcompany

RepresentativeOrganization

Ewel

Minacare

SMS

NomuraResearch
Institute

Small/mediu
Junpukaim company

Regional

NTT DATAINSTITUTE OFMANAGEMENTCONSULTING

Regional/Le Aichi Health
Promotion
ading
company Public Interest
Foundation
Leadingcompany/Regional

NagoyaUniversity

Consortium

Collabo Health

Health and medication
information collaborationby corporate insurers
using Genki Lab

Health improvement by
personal nutritionists

Marunouchi Healthy Town
Development Association

Creating healthy
companies

Participating
Organizations/Main Cosponsors

Analysts and industrial medical
universities

Daiichi-Life, Terumo HealthLife Insurance Society, Toppan
Group Health Life InsuranceSociety, LIXI Health Life
Insurance Society

105

860,000

(220)

－

29

110

(50)

(100)

－

123

Mitsubishi Estate, Nippon
Parking Development, Japan
Medical Checkup Association,
Life Science Institute, Carna
Health Support

Ryobi Holdings, Japan Health
Insurance, Association
Okayama branch, Toppan
Printing, Tanita
NTT Data, Japan Medical
Association, Saitama Prefecture
Medical Association, Saitama
Prefecture

Team Shichifukujin

Seirei Social Welfare
Community, Nagoya University,
Japan Oracle, ABeam
Consulting, Medical Data Vision
Omron Healthcare
Toyota, NAC, Nippon
Systemware, WOWOW
Communications, Toyota City

57

４

(60)

－

85

40

•

•
77,000(180)••
160,000－

Outline•115

Mizuho Information & ResearchInstitute, Mizuho Bank

Support for continuous
prevention of serious casesof diabetes in Saitama
Prefecture using IoTHealth navigator

No. of participants（Top: Results as of November, Bottom:
Scheduled no. of persons)Moderate
Borderline
Healthypatients※1
patients※2
persons※3••
98,000

(100)

－

54

－

(100)

－

168

－

(200)

－

152

－

(130)

－

650

392

(860)

(280)

•

8,400
(Japan Health
Insurance
Association
Okayamabranch：395000)(4 participating
citiesNational Health
Insurance:
Approx. 480000)

•
•

•
•

•
93,000•340,000

Ｔｏｔａｌ

Approx.
1,640,000※Japan Health
Insurance
Association, Japan
Health Insurance

Participated by Konica Minolta, Autobacs, PFU, Nippon Life
Insurance, Orix Group, Nissan, and 18 other organizations.
Collaborating with industrial medical universities and industrial
physicians of companies, productivity loss amount is compared inaddition to activity volume and analyzed.
Participated by Daiichi-Life, Terumo Health Life InsuranceSociety, Toppan Group Health Life Insurance Society, LIXI HealthLife Insurance Society.
Health and medical information possessed by corporate insurers
and subscribers is linked by systems to realize comprehensive
support.
Participated by Mizuho FG corporate health insurance association(Mizuho Health Insurance Society) and SMS.
Escort-type services are provided where the health conditions ofsubjects are generally tracked by the individuals, doctors,
nutritionists, etc., and nutritionists provide diet and exercise
support personally everyday using apps and PC.
Participated by companies located in the Marunouchi area
(Mitsubishi Chemical, Tokio Marine and Nichido Fire Insurance,
Nomura Securities, Asahi Newspaper, Mitsubishi Estate, Asahi
Life).
Programs for preventing serious cases are carried out regionallyusing wearable equipment and monitoring alert functions.
Participated by Ryobi Holdings including bus and taxi drivers. Tieup with Japan Health Insurance Association.
Provides guidance to subjects and create programs using lifestyledisease recovery plans, etc. , and provide monitoring functions
using corporate management functions.
Participated by Saitama Prefecture municipalities (Ageo-shi,
Tokorozawa-shi, Saitama-shi, Sayama-shi).
Prefectures, municipalities, cities, towns, and villages collaborate
with doctors and provide IoT programs.

The project will be carried out by tying up with 23 medicalorganizations and two health guidance organization and sharing
knowhow through workgroups.
Sends messages and calls for attention via the Shichifukujin Apps.
Analyzes and reviews machine learning using accumulated data.

Participated by employees of Toyota head office and their doctors.
Aims to realize visible data using the Health Navigator, andservices such as virtual staff (regular sending of advice),verification of medical conditions call center nurses, face-t-facehealth guidance by industrial doctors.
※1:Includes subjects whose diabetes diagnosis index (HbA1c) is
above 6.5 and require medication.
※2:Includes subjects whose diabetes diagnosis index (HbA1c) is
above 5.6 but below 6.5 and require medication.
※3: No. of employees per company (≒health insurance subscribers
excluding dependents）••

8

⑤[Medical/Health②] Health Promotion Model Business Using Life Data
Analysis Demonstration projects aimed to investigate systematic and technological tasks when applying thefollowing technologies in healthcare industry, etc. starting with genetic testing.
① Statistical analysis method for efficiently analyzing relations between multiple genetic risk
factors and diseases② Technology for analyzing DB with large data volume such as genome information, etc. inencrypted state By establishing these technologies, aim to ①enhance accuracy of onset risk forecast of lifestyle diseases,
etc., and ②establish environment where life data can be used safely.
① Demonstration of statistics analysis method for efficiently
determining multiple risk factors[Implementation system][Present situation](i) National Institute of Advanced
・Search relation of risk factors
and diseases, etc. 1 on 1.
Cannot evaluate effects ofoverlapped multiple factors.
→ Can only explain some of
the genetic causes of
diseases, etc.

・Using database containing
genetic analysis informationand clinical information,
comprehensively analyze
relations between
combination of multiple
factors and diseases, etc.
(Analysis method： (LimitlessArity Multiple testing Procedure（LAMP）
・Verify if analysis is possibleusing realistic calculation
resources (time, cost,
performance, etc.)→ Improves accuracy of risk
prediction of lifestyle diseases,
etc. based on genetic analysis

Industrial Science and Technology[Database used for demonstration]
Biobank Japan (Disease biobank by
Univ. of Tokyo, RIKEN, etc.) DB(Gene analysis information＋ clinicalinformation)② Demonstration of secure multiparty computing technology
which can be applied to DB with large data amount[Implementation system][Present situation]
SBX
・Secure multiparty computing
technology for large data
volume with high sensitivity
such as genome information,
etc.
has
not
been
established(ii) GeneQuest[Database used for demonstration]
DB accumulated and constructed inown company’s inspection operations(Gene analysis information＋
questionnaire information)
Existing method×
Search data of first item

New method (LAMP method）

×[Platform used for demonstration]
Life science information analysis
integration platform Garuda（canmountvariousinformation
analysistools,DB).
Spreadextensively to medical and healthinformation analysis)

Illustration of secure multiparty
computing technology
・Verify if secure multiparty
computing technology
applied to DB with small
data volume such ascompound structure DB canalso be applied to DB withlarge data volume such as
genome information, etc.
→ Reduces leakage risks of
information with highsensitivity such as genome
information, etc.

Analyze correlation with multiple gene mutations
by searching the data of multiple items

Life data
Searchsimilar data

Don’t wantothers to know
my information

Searchresults

Genes, physicalconditions,health information etc.

…
…
Don’t want toleak information

9

⑥ [Distribution] Drone IoT Demonstration Project• To realize safe distribution activities by unmanned flying to remote islands, etc. using drones with the
Quasi zenith satellite drones, this project aims to conduct flight demonstrations for accumulating various data
(Kamiamagusa-shi to Yushima, Kumamoto Prefecture) and survey research for commercialization.

■ Project details■ Implementation system

1. Development and demonstration of drones using Quasi zenithsatellite system
2. Survey and research for commercialization① Based on the results of flight demonstrations, investigate
systematic and technical issues of commercialization.
② Investigate safety measures including security measures③ Survey of commercialization needs

Led by: Hitachi Zosen
Drones: EnRoute, Yamaha Motor
Communication and operating system
Demonstration municipal: Kumamoto Prefecture,
Kamiamakusa-shi■ Demonstration area
(Kamiamakusa-shi, Kumamoto Prefecture)

High precision
measurement

Drones

Quasi zenithsatellite system

Communication and control
linked to quasi zenith satellite
system drones

・Implement demonstration experiments in Kamiamakusa-shi,
Kumamoto Prefecture on Nov 29, 201610

⑦ [Service] IoT-Based Service Demonstration Project• To realize “Omotenashi” service, this project aims to carry out demonstrations on sharing/using data related
to attributes (gender, age, nationality, etc..) and history of actions (accommodations, shopping,
movement, etc..) between service providers with consent from the visitors to Japan, and providing
advanced and diverse service /payment environment.
• In the demonstrations, efforts will be made to respond to systems in individual services, and rules will beestablished on dealing data formats for sharing and using data between various service providers
with different systems.
Demonstrations were started at actual sites from
October this year. Aim for use by foreigners visiting
Japan exceeding 10000 persons within the year.

A KantoInformation linkage

B(Hakone, Yugawara,
Kamakura)

Omotenashi
Platform

Kansai(Osaka)C

D
Kyushu(Fukuoka)

Construction of “Omotenashi Platform” D
テーマ: Information linkage between various service
platforms
Implementation system: Deloitte, Dai Nippon
Printing, etc..
Establish rules on data exchange regulations(data format) via demonstration projects(Example of data items)
userID,email,phone,firstname,middleName,lastName,sex,gender,blood,birthday,language,nationalities,country,state,city,wedlock,family,work,hobby,interest,smoke,allergyFood,arrivalDate,departureDate,tourType,purpose,headco
unt,member,paymentNumber,paymentType,shop,item,currency,quantity,price,amount ・・・

Kanto (Hakone, Yugawara, Kamakura) local
demonstrations
Theme：New services using biometrics
authentication, etc..
Implementation system：JTB Corporate Sales,
Liquid, Hakone Onsen, Yugawara Onsen, etc..

A Settlement by biometricauthentication
 Checkin/Checkout Delivery and receipt of goods
 Provision of regional informationin multiple languages

B

Kansai (Osaka) local demonstration
Theme：New settlement (Total Wallet, etc..)
Implementation system：Panasonic Group, Mitsui
Sumitomo Card, Dai Nippon Printing, Kaiyukan(Aquarium), etc..

Liquid Marketing, Inc.

1st IoT Lab Selection
Grand Prize Winner

Individual authentication
system by fingerprint
using Artificial Intelligence

Institutional issues

 Register multiple payment means
anywhere, anytime using asmartphone, and carry out
biometrics authentication
 Provide multiple-language
information linked to signboards,
signage, etc..

Can verification of actual
passport based on Hotel and
Ryokan Management Law be
substituted with fingerprint
authentication systemC

Use of gray zone
resolution system

Kyushu (Fukuoka) local demonstration
Theme ：Broad, horizontal information usage andpromotion of consumption
Implementation system：JTB, JTB Tourism
Research & Consulting , JCB, JSTO, NTT
Advertising, Kyushu Economic Federation, etc..
 Issue card type gift certificate linked
to mobile phone apps, and in addition
to attribute information, gather accesslogs/GPS information/settlement
history, etc.., and provide service

Enable passport verification offoreign tourists visiting Japan
when paying for shopping andchecking into hotels, using
fingerprint only .
→Use for demonstration
projects

11⑧ [Smate home] Data Usage Environment Establishment Promotion
Project for Smart Homes (New)• In the future, with the increase in equipment linked inside the household and improvement of volume/qualityof data which can be acquired, it is hoped that this project will help create innovative services enablingcustomization of living space and improvement in product lifecycle, in addition to the visualization of energy
consumption and On/Off operations of home appliances.
• Through demonstrations, the environment required for creating new services will be established, such asdevising common industrial cross-sectional guidelines in data collaborations taking into account privacy.

Image of Project○ Construct an environment which enables equipment to be connectedto the network in the home to be brought in to acquire/provide data
in an open manner through corporate consortiums made up of housemanufacturers, home appliance manufacturers, power and gas
providers, and service providers.
○ Demonstrations will also be carried out to create use cases such ascomprehensive services in the product life cycle and services meetingneeds of private companies using various data related to the home.

Service

Service provider, etc..

（

•
•
•
•
•

Creation of innovative services
Delivery of recall information, etc..
Easy discharge in recycling
Provision of energy-saving information such as
replacement period, etc..
Provision of advanced home care services
Proposal of food recipe for promoting health, ingredientdelivery, etc..

Data provision[Outline of innovative services born fromdata collaboration]
information related to home（e.g. Home appliance
operations information, etc..）

Home appliancerecycling/recall

EnergyManagement

Medicalcare/health/nursing

Service provider

♪

…etc

Entertainment
Childcaretelework

Security/insurance/
maintenanceHouse (home appliance, sensor, etc..)

Equipment (home appliance manufacturer, power/gas companies）

House (House manufacturer)

Creation/supply of innovative
services

Resolve social issues(E.g.) ・Support lifestyles for promoting the advancement of home care using life logs and advance of women into society.
・Promote recall measures and discharge of disposed home appliances through the proper route through theenhancement of serviceability of home appliances.

Satisfy corporate
and individual needs(E.g.) ・Develop products meeting consumer needs by analyzing consumer information, equipment operation state.
・Realize comfortable lives by grasping the state at home from outside and automatic control of home appliances.

12⑨ [Aircraft] Aircraft System Advancement Project for Supporting
Piloting (New)• Global air transportation demand will expand at an annual rate of 5% in the coming years. While the numberof pilots is expected to double by the year 2030, there will still be a deficit of approximately 8,000 pilots per
year, raising the concern of the need for more skilled pilots.
• Utilizing accumulated navigation data and AI technology, this project aims to carry out
demonstrations for realizing sophisticated and safe aircraft systems such as systems for supporting
pilots with assistance on navigational flight plan alterations during bad weather, which is currently
manually handled by the pilot.
[Demonstration details][Image of implementation system]① Flight plan data

③ Flight result data

Flight plan

Flight results

Airframe,
Avionics
makers・Integrate withaircraft applications② In-flight information etc.
Inside cockpit,
weather
information etc.

Pilot
discretion

AI・IoT
companies

By utilizing AI and IoT technology for information ①～③, carryout demonstrations providing that aircraft systems that are moreadvanced and safer than systems supporting pilot judgments.

[Example of pilot assistance fordecision making]・Analyze data etc.
provided by airlines
using AI technology

・Store and share
flight result data etc.

Reduced time
Bad weather

Indicate appropriate
flight path and support
during sudden airplanemalfunctions

Minimumuse of fuelEmargency landing

Forced landing

Airlines

Present anappropriate flightpath to avoid foul
weather (option)

In case of sudden illness,
indicate appropriate
airfield and flight pathfor emergency landing

When safe landing isdifficult, indicate landing
return (start over) andflight path

Landing return
Emergency landing13

⑩ [Mobility] Smart Mobility System Research & Development and Demonstration Project
Purpose and Details of ProjectThis project aims to demonstrate the use of a sophisticated autonomous driving system that will help contribute to the advancement ofenergy saving for the transportation sector, that takes in to consideration safety, social receptivity, economic efficiency as well as the global
outlook, as well as to investigate the necessary technology, business environment and such to implement it in to society.
⇒ Sophisticated autonomous driving system Convoy (columnar) driving, Automatic valet parking, Use of exclusive zones, etc. for Last
mile autonomous driving (Terminal traffic system)
Convoy (columnar)
driving

Select location for 2016 demonstration run
Implement demonstration experiment at test course
in 2017

Future Vision：Actualization of over 3 unmanned trucks
driving together on the highway at night in a truck convoy

MannedUnmanned
Unmanned

Required efforts○Development of electronic connection
technology (including brakes)○Arouse social receptivity (startdemonstrations with 2 following cars withpersons on board) etc.

Lifestyle autonomous driving

Automatic valet
parking

Implement demonstration experiment in 2018

Future Vision：Actualization of automatic valet parking at
exclusive parking lots (where there are no pedestrians)

Implementation structure coordination: Toyota Tsusho○Test vehicle production,
demonstration experiment
implementation:
Isuzu Motor Co., Hino Motor Co.,
Mitsubishi Fuso, UD Truck○Technology necessary for thecolumnar convoy:
Advanced Smart Mobility Co.,JTEKT, Nabtesco, Wabco Japan,
Nippon Signal Co.
○Evaluation of business model etc.:
Yamato Transport, Sagawa
Express, Nippon Express, Japan
Trucking Association

Implementation structure coordination: Japan Automobile
Research Institute(From Honda Motor Co. homepage)○Control center development: Fujitsu Ten○Parking control format development:
Aishin Seiki Co.
○Mapping, localizer* format development:
Pioneer

Required efforts○Consensus building amongst the related parties○Allocate responsibilities (standardization) for vehicles, parking, control center etc.

① Users (elderly people and such) callup and board unmanned vehicle② Unmannedautonomous driving③ Users disembark attheir final destination(homes etc.)

Select demonstration location via public
offering in 2016
Aim to implement demonstration
experiment by 2018

Future Vision：A new transport
service via the use of an exclusive
zone is realized, connecting the‘Last one mile’ between thenearest station etc. and finaldestination location

Neareststation etc.
最寄駅等

Required efforts※ Exclusive zone for autonomous driving
vehicles that is void of pedestrians④ Unmanned autonomous vehicles
with return automatically○Select exclusive area for introduction○Establishment of system to minimize
maintenance and operation
burdens etc.

最終目的地
Final destination(homesetc.)(自宅等)

Implementation structure – coordination:
National Institute of Advanced Science and Technology○ Development of small electric karts and systems:
Yamaha Motor Co., Hitachi, Toyota Tsusho○ Establishment of small buses utilizing autonomous driving technology:
SB Drive, The Japan Research Institute14