cockpit for big systems and big iot systems leveraging ibm bluemix and watson

Local Touch - Global Reach.

Intelligent System for Precision FarmingA partnership project between Drotek & SogetiLeveraging IBM Bluemix and Watson Technologies

World of Watson – Octrober 24-27 – Las Vegas

SOGETI France - 2016

IBM World of Watson 2016 Conference

Session ID: IOT-2052

http://www.ibm.com/events/global/wow/sessions/

Partnership Project – IBM World of Watson 2016 Conference

2 The Speakers

Patrick started programming on a Casio FX-602P and after on HP-41C, a long time ago! After more than a quarter century working on machines for people and large organizations, as a developer, as an architect, as a project manager or consultant he is still fascinated by the beauty and by the monstrous and elusive nature of complex systems, and in particular socio-technical systems. In 2012, as an innovation leader at Sogeti and members of the SogetiLabs, he launched five R&D programs using big data, software system testing, multi-agent systems, cloud computing, and project management as fields of experiments. His conviction is that instead of undergoing complex systems we must try to understand them, better control them, innovate, and do business with that.

Kevin is Drotek’s CTO & Associate. Technology aficionado, late night explorer, language learning addict, he is a real Swiss army knife for the start up. He loves it when someone comes up with a new « out of the blue » idea (if he doesn’t himself) and he has to design a prototype for it from scratch. Fast. Innovate. Iterate. That’s his motto. Skydiver, pilot, there seems to be no limit for him. He strongly believes that without risk there can be no success. Most important thing about his personality is that he is relentlessly eager to learn. He has proved his ability to solve complex problems in record time, as an intern he designed, developed and started to sell a disruptive product in less than 6 months.


3 Once upon a time …

At different scale …

But still complex systems !

With unpredictable behavior and

evolution!

Complexity !


4

ConstituentEcosystem

Why Complexity? Which issues?

System(of interest) Constituent

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

applies toapplies to


aggregation of

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

Sy stem Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

Sy stem Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

Behavior

Evolution

Plurality

Variety

Hierarchy

Feedback

Speed of changes

Emergence of Behavior

FACTS

Representation& Modelization

Calculability:Optimization& Prediction

ISSUES


5


System(of interest)

Constituent

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution



aggregation of

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

Behavior

Evolution

The Agent and Multi-Agent Based System Paradigm

Associate System-Agent with Software-Agent

Wherever and Whenever possible Models based Agents


6 Control and Command of Complex Systems


System(of interest)

Constituent

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution



aggregation of

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

System Constituant

Behavior

Evolution

Behavior

Evolution

Control

from

Sensors

Command

to

Actuators

Intelligence


7

Historically, CBS started with the need to control-command and manage Very Large Systems of Systems (~100K machines) in the IT area, with a much larger number of assets (~20 managed assets per machine) and Ultra Large Scale System as final target (more than 1 million machines ~20 million assets) . Our concerns were:

• Efficient functioning with the same quality at different scales• Inherent heterogeneity of management of assets and diversity of modes to communicate with each others• Adjustment to the fine granularity of information in order to follow in real time the business needs• Orchestration control of the systems of systems

We built a generic infrastructure system, adaptable to business needs, and to use cases. CBS is OK with VLSS, but we are still running at the ULSS.

We need more scalability, elasticity and fast application development for experiments. We needed something like Bluemix!

Cockpit for Big System (CBS): The First Step


8

• Currently , each instance of CBS can manage ~ 30 000 machines (more than half million assets managed)

• Monitoring information are retrieved each 15 minutes, then consolidated in a daily inventory 3Go of data consolidated daily 4To of data on a 18 months window

• + 250 000 assets inventoried in less than 5 minutes on a common LAN/WAN

• ~ 200 unique inventory keys, allowing to repertory, e.g., more than 700 applications, several OS, CPU, GPU, network interface controller, … Based on a generic inventory keys system, new sensors or actuators in the new version of CBS called CBIoTS can be added in some minutes.

• + 100K SLOC of Javascript, Perl, C, sh

• + 10 years of maturity of the agent software, which memory footprint is ~ 500Ko on Linux and ~ 1Mo on Windows

• + 20 environments / OS handled (Unix, Linux, Windows, Android, Raspberry PI, Yocto) . Soon on IOS and OSX

• All communications (agent-agent, agent-platform) use key authentication (AES) and communications encrypted (RSA)

Cockpit for Big System: Some Metrics


9 Cockpit for Big Systems: Architecture Overview

CBS: Web Server Portal• Apache• Js/HTML• Widgets• Perl

CBS: Databases Cluster

• SQL• NoSQL• Graph

CBS: Consolidation Servers

• Consolidation• Operations automation

CBS: Data Collection Servers

• Data Collection• Data Integration• Listener

External Repositories

• LDAP• CMDB• …

CBS: Secure Gateway

• End-to-end connection• Encrypted tunnel• Encrypted communication

CBS real time compatible Agent• UNIX (Oracle, HP , IRIX, …)• LINUX (Red Hat, Cent OS,

Debian, Raspbian, …)• MS WINDOWS (all)• Yocto (Intel Edison)• Andoid• Soon on IoS and OSX

IBM Bluemix

• Docker containers• DB Server• Services


10

The IoT Experiments: reach the ULSSand take other kind of socio-technical SoS up

Cockpit for Big IoT Systems: The New Stage of CBS

• Instantiation of the CBS platform for very big IoT systems

• Processing of Big Data• Retrieve of data and function determination given

the sensors• Action on the environment using actuators• A sensor (or actuator) = a function

Functional composition and triggered actions

CBIoTS Engine

CBS

Agen

t

Sens

ors/

Actu

ator

s up

to 2

0/un

it

Devi

ce w

ith U

nix,

Li

nux,

Win

dow

s or

An

droi

d O

S

CBS Agent

Sensors/Actuators up to 20/unit

Device with U

nix, Linux, W

indows or

Android OS

CBS Agent

Sensors/Actuators up to 20/unit

Device with Unix, Linux, Windows or

Android OS

CBS Agent

Sensors/Actuators

up to 20/unitDevice with Unix,

Linux, Windows or

Android OS

CBS AgentSensors/Actuators

up to 20/unit

Device with Unix,

Linux, Windows or

Android OS

CBS Agent

Senso

rs/Actu

ators

up to 20/unit Dev

ice w

ith U

nix,

Linux,

Windows o

r

Android OS

CBS Age

ntSe

nsors/

Actuato

rs

up to

20/unit

Device w

ith U

nix,

Linux,

Windows o

r

Android OS

EnvironmentEnvironment

Environment

Environment

Envir

onmen

t

Envi

ronm

ent

Envir

onmen

t


11

Business ApplicationBusiness

Application

Cockpit for Big IoT Systems: Architecture Overview

Up to 30 000 units

encrypted

encrypted encrypted

encrypted

CBIoTS Platform

Sensors or Actuators(up to 20/unit)

Device OS

CBS Agent

IBM Watson

Business Application

Data (cloudified (IBM Bluemix) or on-premise)

High Data Streaming on IBM Bluemix

CBIoTS Engine on IBM Bluemix

Feedback Loop Feedback Loop

Feedback Loop

Up to half million sensors/ actuators under control/ command per CBioTS Engine instance

Device OS

CBS Agent

The IoT Experiments: reach the ULSS and take other kind of socio-technical SoS up

Use of Watson as a Global Feedback Loop

Use CBIoTS on Bluemix & Watson as an Infrastructure to quickly develop intelligent IoT business applications


12

• Very Large IT Systems monitoring (done and running on-premise)• DevOps (done and running on Bluemix , see NADO project)• Smart Farming (in progress, see partnership with Drotek)• Smart Cities (ongoing prospection)• Smart Villages (in progress, some services are in partnership with Droteck)• Home automation• Transport (ongoing prospection)• Better understanding of System of Systems and Complex Systems (Current links with

research laboratories in Toulouse)• …

CBS/CBIoTS: Use Cases


13 CBS/CBIoTS: Partnership with IBM

Special thanks to the IBM Architect Team in India• Vishal A CHAREGAONKAR• Naveen K PRATHAPANENI• Prashant S NAIK• Shiva KUMAR H R

Which are helping us in the porting of the CBS/CBIoTS platform on Bluemix

Many thanks to all the people involved in our partnership with IBM• Christian CHATEAUVIEUX (IBM France)• Claude BRUSSOLO (IBM France)• Olivier LISE (SOGETI)• Philippe DURANTE (SOGETI)• Jacques MEZHRAHID (SOGETI)• Mark RIGGS (Capgemini)• And all the others not mentioned here


14

The information contained n this presentation s proprietary.© 2015 Sogeti. All rights reserved.

www.fr.sogeti.com

About SogetiSogeti is a leading provider of technology and software testing, specializing in Application, Infrastructure and Engineering Services. Sogeti offers cutting-edge solutions around Testing, Business Intelligence & Analytics, Mobile, Cloud and Cyber Security, combining world class methodologies and its global delivery model, Rightshore®. Sogeti brings together more than 20,000 professionals in 15 countries and has a strong local presence in over 100 locations in Europe, USA and India. Sogeti is a wholly-owned subsidiary of Cap Gemini S.A., listed on the Paris Stock Exchange.

TMap®, TMap NEXT®, TPI® and TPI NEXT® are registered trademarks of Sogeti, part of the Capgemini Group.

Thank you for your attention!

Now, lets talk about Precision Farming with Kevin from Drotek…

http://www.facebook.com/Capgemini

http://www.linkedin.com/company/capgemini

http://www.twitter.com/capgemini

http://www.youtube.com/capgemini

http://www.slideshare.net/capgemini


15 Planet Earth in 2050

+30%

+70%

+5%

+0.7%

People

Food need

Arable land

YieldOUR WORLD

IN2050


16 Main Goals

COMPETITIVENESSECONOMICS

YIELD

ECOLOGY

SOCIAL


17 Farmers overwhelmed by data


18 ISPF: The Ecosystem


19

IBM BluemixMobile Devices, Sensors & Actuators

Fixed SensorsISPF

Portal Clou

d or

On-

prem

ise D

ata

Drotek embedded system &

CBIoTS smart agents

A fully distributed Architecture based on Embedded Systems, Multi-

Agent and Cloud Technologies

TCP, LoRa, Sigfox

ISPF: Architecture overview


20 ISPF in Real Life


21 ISPF Measurable Metrics

10%15%

99%

5%

Fuel economySavings on seeds, fertilizerand chemicalsDecrease on fertilizer cost

Yield increase


22 ISPF: Main script

From Sensors (S) to Actuators (A)

+

+

CBIoTSWATSON Network

CBIoTS Network

S

A

A

Network CBIoTS WATSON+1

2

3

1Data collection 2Automation with: • Context awareness• Smart behavior

3Analytics & Forecasting for • Context awareness• Smart content


23 ISPF: Functional Overview

Animation


24 Intelligent System for Precision Farming


25 Thank you

Thank youFor more details contact:

Patrick MarquetPractice Leader Enterprise Solutions Consulting - Sogeti France

[email protected]

mailto:[email protected]


26

The information contained n this presentation s proprietary.© 2015 Sogeti. All rights reserved.

Thank you for your attention !

drotek.com

About DROTEKDrotek is a French tech start-up made of technology aficionados and late-night explorers. We think, design and produce as if we still were in our garage. Fast. Innovate. Iterate. This is our motto. We love it when someone comes up with a new "out of the blue" idea and we have to design a fully-working prototype completely from scratch. We strongly believe that people should pay for the atoms, not for the bits and this is why we offer free learning through our open-source and open-hardware products... Our eagerness to learn is relentless. And we want to share it. Our own production line lets us work fast for customers who put the emphasis on quality and smart designs. Made in France stamped stuff !.

https://www.facebook.com/drotek

http://twitter.com/drotek

https://www.youtube.com/c/DrotekFr