Gather a variety of data sets using monitoring technologies

Apply optimization, simulation and deep learning techniques to the real world data

Collaborative research

CPS(Cyber Physical System) and Creating New Industrial Applications on ABCI

Information: https://unit.aist.go.jp/rwbc-oil/index-en.htmlContact: info-rwbc-ml@aist.go.jp

CPS(Cyber Physical System) and Mobility Optimization Engine

歩道

倉庫

ＥＶ

オフィスビル

高速道路

監視カメラ

入退館ゲートＥＳＣ

商業複合ビル

空港

産地

農業

橋堤防

航空管制

住宅マンション

ＳＡ/ＰＡ

ゴミ処理場コンビニ 商店街

駅

農業用水路

病院

車道

市街地道路

河川

浄水場

トンネル

医療

Energy Consumption

FCV/EV

Traffic Movement

People Movement

GPS, GIS, Facility Information

Administrative Information,

Social InformationMedical & Finance

Wearable DevicePersonal Device

Digital Signage

Smart Phone, Navigation

Social System, ITS, EMS

Real World Real World

Modeling Real World Feedback/Control Real World

Cyber Space

Optimization / Simulation

Cyber-physical System and Industrial Applications of Mobility Optimization Engine

サブ 分け

サブ1

回路A

回路B

回路C

回路Aと 回路Bの関係性

回路Bと 回路Cの関係性

絶対条件（ 共圧着） に該当する 枝 (赤) にはより 高い重みを 与える

グラ フ分割の結果は点の色で表現

(3) サブ分けの評価

(1) 枝生成ルールの決定

(2) グラフ 分割

Next Generation AI Optimizing the materials flow in the distribution center

Virtual Factory on CyberspaceOptimizing production planning and schedule &decreasing manufacturing costs

Mobility of Human, Object, Money and InformationAnalyzing web access data & estimating effectiveness of web advertisementGeneral Simulator of HV or PHV

Given a driving pattern, minimize the fuel consumption of HV or PHV system

Automatic Driving & Traffic Route PlanAnalyzing CAN data & constructing map matching system based on GPS data

Cyber Physical System(CPS) & Mobility Optimization Engine

Real World Cyber World Real World• Data acquisition

• Censoring, Sensing, …

• Optimization• Simulation• Analyzing

• Feedback• Realization• Display

…

…

Human and objectsdetectionfrom cameras

Obtaining the most likely passage using optimization and graph analysis

Detection and visualization of congestions and its origins

High Dimensional Data

Low Dimensional Representation

Based on Manifold Theory

Extract nice low dimensional representation from high dimensional original data

多様体理論

With extremely large scale of access data gathered by[1]Clustering users under considering users’ interest each website by 3 optimization problem[2]Fitting user’s time on website to single weibull distribution every cluster and website

Proposing New Website Performance Metricby Obtaining How to Change User’s Interest

Fitting

Fitting

Clustering

Weibull distribution

①Nonnegative Matrix Factorization

②LP (Constrained Network flow Problem)

Pick up feature vector of

each webpage and user

Calculate the proportion ofclusters in each website

under given feature vector

Decide which cluster the user belongs

when the user visits certain website

③LP (Constrained Network flow Problem)

Analyzing Web access data & Estimating effectiveness of Web advertisement

Basic Requirements for AI Cloud System

PFSLu stre・

GPFS

Ba tch Job Sch ed u l er s

Loca l Fla sh + 3 D

Xp o in t Stor a g e

DFSHDFS

BD/AI U ser Ap p l ica tion s

RDBPostg reSQL

Py th on , Ju p yte r N o tebook , R etc. + I DL

SQLH ive/Pi g

Clo u d DB/N oSQLHbase/Mond oDB/Red is

Re so u rce Br oke rs

Mach in e Lea rn ing Lib rar ies

Nu m er ica l Lib ra r iesBLAS/Ma tla b

Fo rtra n ・ C・ C+ +Na tive Cod es

BD Alg o r ithm K e rn e ls ( so r t e tc. )

Pa ra l le l Deb u g g e rs a n d Pro f i le rs

W ork f low System s

Graph Com pu tin g Libra ries

Deep Lea rn in g

Fram ew orks

W eb Services

Lin u x Con ta in er s ・ Clou d Ser v ice s

M PI ・ Open M P/ACC・ CUDA/Op en CL

Lin u x OS

I B・ OPAH ig h Ca pa city

Lo w La ten cy N W

X8 6 ( Xeon , Ph i )＋Acce l era to r s e . g . GPU,

FPGA, La ke Cr est

Ap p l ica tio n

ü Easy use of various ML/DL/Graph frameworks from Python, Jupyter Notebook, R, etc.

ü Web-based applications and services provision

System So f tw a re

ü HPC-oriented techniques for numerical libraries, BD Algorithm kernels, etc.

ü Supporting long running jobs / workflow for DL ü Accelerated I/O and secure data access to large data

setsü User-customized environment based on Linux

containers for easy deployment and reproducibility

OS

H a rd w a re

ü Modern supercomputing facilities based on commodity components

CPS Mobility Optimization Engine on ABCI•AI(Deep Learning), Graph Analysis, Mathematical Optimization (LP, MILP, SDP, etc.)⇒ Chainer(Chainermn), Caffe, Tensorflow, Keras, SDPARA etc.

4D Geospatial Information System + CPS Mobility Optimization Engine

Current System : Smartphone + Google Maps ⇒New Generation Personal Navigation System⇒ 4D Display + CPS Mobility (life, amusement, security) + Wearable Devices (AR + VR)

サイ バー空間

リ アルタ イ ム計算

オンデマンド 計算

ディ ープ計算

マク ロ解析層

中位解析層

ミ ク ロ解析層

動線データとグラフデータ化 建物や動線の設計

グラフデータと静的データ活用

最適化計算機械学習

ネットワークフロー計算

混雑度予測リアルタイム避難誘導

実世界 実世界実世界のデータ 化 最適化計算、 シミ ュ レーショ ン 実世界へ反映、 制御

⾧期

中期

短期

棚や商品の配置商品や場所等の価値判定

センシングなどの動的データ活用データセンシング

ボトルネック解析最適化計算

CPS Mobility Optimization Engine

4D (Position + time)Geospatial Information

+Wearable Devices

VR + ARData

(Imagery + Point)

Knowledge4D map =

position(3D) + time

Physical CyberData collection + Map renewal

Positioning +Optimized action based on

simulation and big data analysis

Real objects an events Dynamic 3D map

OPEN AI Infrastructure

+

…