INF5120 Modelbased System development · 6-18/2: ArchiMate 3.0 Modeling, TOGAF 9.0 7-25/2: Node-RED Cognitive Services/AI –Watson services example (for Oblig 2) (IBM Cloud) 8-4/3:

Telecom and Informatics 1

INF5120

”Modelbased System development”

Lecture 13: 08.04.2019Arne-Jørgen Berre

[email protected] and [email protected]

mailto:[email protected]

mailto:[email protected]

Course parts – 2019 (tentative plan)

2

Part I-a -(Introduction to Modeling): 14/1 - Start 1-14/1: Introduction to INF5120 Part I-b -(Introduction to Modeling and Metamodeling and) 2-21/1: Modeling structure and behaviour (UML and UML 2.0 and metamodeling) 3-28/1: MDE with Eclipse EMF, Xtext and SIRIUS 4-4/2: Business Modeling – BMC, LSC, VDML/VDMBee, (w/meta model) - (Business Model Canvas, Value Proposition,

Lean Canvas - VDMBee, VDML Part II - (Business Architecture/Business Modeling Modeling + Server side – Node-RED + THingML + Sensors/IoT/Cloud -

and the Smart Home project): ) 5-11/2: BPMN 6-18/2: ArchiMate 3.0 Modeling, TOGAF 9.0 7-25/2: Node-RED Cognitive Services/AI – Watson services example (for Oblig 2) (IBM Cloud) 8-4/3: Smart Home - Design Thinking + Chatbots 9-11/3: Service Modeling with UML 2.X Collaboration Models and Composite Models and SoaML + CJML 10- 18/3: UML 2.x Sequence Diagrams, UML 2.x State Machines. ArchiMate ArchIsurance, ArhiMetal examples, 11- 25/3 CJML – Customer Journey Modeling Language (Guest lecture, Dr. Ragnhild Halvorsrud and UML OCL) Group presentations – Oblig 1 ideas .. Part IIi - (Modeling –Apps + EA/ArchiMate) 1/4 - Oblig 1: Specification Models Smart Home – Business Architecture – Business Canvases, ++, ArchiMate + IBM

Cloud basis 11- 1/4 DSLs: SysML (Graphical) and ThingML (Lexical), - Oblig 2, 3 - discussion/ Oblig 1 Group presentation (2nd

group)Part IV - (MDE – Creating Your own Domain Specific Language – Eclipse, Xtext/SIRIUS): 12-8/4: Model driven engineering – DSLs - IBM SPSS Graphic Modeler and IoT Analytics EASTER – 15/4 and 22/4 13-29/4: Lecture - DSLs and Transformations 14-6/5 Lecture – Model Driven Engineering 6/5 - Oblig 2 – delivery: Individual / Pairs - Metamodeling (Editor) 15-13/5 Lecture - Model Driven Engineering 13/5 – Oblig 3- : Smart Home – Design/Realisation with Node-RED, IBM Watson/IoT services + ArchiMate/UML++

Application, Technology, Physical models – Smart Home demonstrations - 10% 16-20/5: Summary of the course - Oblig 4 final discussions - Conclusions, Previous exams – group collaborations for the Exam by old exams 3/6: Exam (4 hours), Mandag June 3rd, (0900-1300) - 70%

IBM SPSS Graphic Modeler (Graphic DSL example)

https://www.ibm.com/no-en/marketplace/spss-modeler

EXAMPLE:

Tutorial text

predictionconfidence

https://www.ibm.com/cloud/garage/architectures/dataAnalyticsArchitecture

https://www.ibm.com/cloud/garage/architectures/dataAnalyticsArchitecture/alldataanalyticssolutions

BDV – Big Data and Analytics/Machine LearningReference Model

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OperationRetail and

Services

Da

ta

Acq

uis

itio

n

Cu

rati

on

Sto

ra

ge

an

d p

roce

ssin

gA

naly

sis

Valu

e

Bes

lutn

ings

støtt

ever

ktø

y

ProductionDesign

BIO

Data

Array

dbLinked

data

INDUSTRIAL DATA SPACE – with Data Security

Industrial Analytics / Hybrid Modeling and Analytics Descriptive, Diagnostic, Predictive, Prescriptive, Preventive Analytic services

Storage Variety, Variability

Volume

Batch

Velocity

Real-

time

Infrastructure

Data Driven Analytics, Data Science, and Machine Learning

BIO

Data

Interactive

In

Memory

ClassificationVisual

AnalyticsBasic Statistics

ClusteringRegression,

Neural Network

Machine

Learning

Dat

a M

anag

emen

t

Component

models

Weather

data

Maintenance

dataSCADA

Sensor

data

Hydro

modelsMeta

data

IoT

Sensors

actuators

HPC

cluster

EDGE/Machine Connections

and Edge Analytics

First Principles Cybernetic ModelingP

roce

ssin

g

Data Platform with Hybrid Analytics

Model Simluation and Optimisation

MATLAB – HPC

Simulation OptimisationMPC

Model

Data

Sim

DataOptimis

Data

...

Sensors

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Descriptive analyticsDiagnostic analyticsPredictive analyticsPrescriptive analyticsPreventive analytics

SENSORS- Temperature– ambient- Temperature – surface- Moisture- Light - Lux- Open/Close- Movement- Pressure- Button (push)- Digitalisator (strøm/spenning) – for analogue connection- Vibration- Camera- Voice in/out– Chatbots, Alexa, Google Home,..- Clock - time- Position – outside/inside- Identification (RFID)- …- andre …

Sensor Data

Other Data

Even Other Data

Message Broker

Database

Stream Analytics

Interactive(Dev)

Batch (Backtesting)

Experiment with Analytics for EL-Watch Neuron sensors (See later Node-RED integration)

45

https://www.el-watch.com/en/

46

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11/04/2019 ICT-15 proposal preparation meeting - Brussels

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Documents

INF5120 Modelbased System development · 6-18/2: ArchiMate 3.0 Modeling, TOGAF 9.0 7-25/2: Node-RED Cognitive Services/AI –Watson services example (for Oblig 2) (IBM Cloud) 8-4/3: