ICT Smartcities 2013 FP7-SMARTCITIES-2013 Kick Off Meeting Athens October 23,24 2013 OPTIMising the energy USe in cities with smart decision support system.

Slides:



Advertisements
Similar presentations
Ch:8 Design Concepts S.W Design should have following quality attribute: Functionality Usability Reliability Performance Supportability (extensibility,
Advertisements

New market instruments for RES-E to meet the 20/20/20 targets Sophie Dourlens-Quaranta, Technofi (Market4RES WP4 leader) Market4RES public kick-off Brussels,
1 st Review Meeting, Brussels 5/12/12 – Technical progress (P. Paganelli, Bluegreen) iCargo 1st Review Meeting Brussels 5/12/12 Technical.
PERFORMER WP2 INTRODUCTION 13th of September 2013 CSTB Sophia Antipolis, France.
Project Management 6e..
Lecture # 2 : Process Models
Information Systems Analysis and Design
OPTIRAIL WORKSHOP · OCTOBER 23, 2014 · BRUSSELS WP5: “Integration and Usability validation of models”
© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 6-1 Chapter 6 Decision Support System Development.
Irwin/McGraw-Hill Copyright © 2004 The McGraw-Hill Companies. All Rights reserved Whitten Bentley DittmanSYSTEMS ANALYSIS AND DESIGN METHODS6th Edition.
Copyright 2004 Prentice-Hall, Inc. Essentials of Systems Analysis and Design Second Edition Joseph S. Valacich Joey F. George Jeffrey A. Hoffer Chapter.
DECISION SUPPORT SYSTEM DEVELOPMENT
The Software Product Life Cycle. Views of the Software Product Life Cycle  Management  Software engineering  Engineering design  Architectural design.
WP 8: Networks for Lifelong Competence Development Alicia Cheak INSEAD CALT (Centre for Advanced Learning Technologies) TEN Competence Kickoff Meeting.
© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 6-1 Chapter 6 Decision Support System Development.
Welcome to CMPE003 Personal Computer Concepts: Hardware and Software Winter 2003 UC Santa Cruz Instructor: Guy Cox.
The URBACT II Programme General Presentation Vilnius, 20 January 2011.
What is Business Analysis Planning & Monitoring?
Process: A Generic View
Bina Nusantara 2 C H A P T E R INFORMATION SYSTEM BUILDING BLOCKS.
S/W Project Management
FP OntoGrid: Paving the way for Knowledgeable Grid Services and Systems WP8: Use case 1: Quality Analysis for Satellite Missions.
Copyright 2002 Prentice-Hall, Inc. Chapter 1 The Systems Development Environment 1.1 Modern Systems Analysis and Design.
Mantychore Oct 2010 WP 7 Andrew Mackarel. Agenda 1. Scope of the WP 2. Mm distribution 3. The WP plan 4. Objectives 5. Deliverables 6. Deadlines 7. Partners.
Microgeneration and new end-use technologies in ADDRESS, INCA and SEESGEN-ICT Jussi Ikäheimo (VTT) (& Regine Belhomme, Giovanni Valtorta) IEA DSM 17 workshop.
CS 360 Lecture 3.  The software process is a structured set of activities required to develop a software system.  Fundamental Assumption:  Good software.
A NEW MARKET PLAYER: THE AGGREGATOR AND ITS INTERACTION WITH THE CONSUMER interaction Ramón Cerero, Iberdrola Distribución Paris, June 9th 2010 ADDRESS.
Copyright © 2004 The McGraw-Hill Companies. All Rights reserved Whitten Bentley DittmanSYSTEMS ANALYSIS AND DESIGN METHODS6th Edition Irwin/McGraw-Hill.
2131 Structured System Analysis and Design By Germaine Cheung Hong Kong Computer Institute Lecture 2 (Chapter 2) Information System Building Blocks.
OPERATIONAL GUIDELINES Ensuring Ownership of PARSEL by Partners.
Green Partnerships Local Partnerships for Greener Cities and Region Stavroula Tournaki, Chemical Engineer MSc, ΕU Projects Manager Konstantinos Voumvourakis,
1-1 System Development Process System development process – a set of activities, methods, best practices, deliverables, and automated tools that stakeholders.
Software Engineering Principles Principles form the basis of methods, techniques, methodologies and tools Principles form the basis of methods, techniques,
Decision Support System Development By Dr.S.Sridhar,Ph.D., RACI(Paris),RZFM(Germany),RMR(USA),RIEEEProc. web-site :
Copyright © 2004 The McGraw-Hill Companies. All Rights reserved Whitten Bentley DittmanSYSTEMS ANALYSIS AND DESIGN METHODS6th Edition Irwin/McGraw-Hill.
SYSTEM TESTING AND DEPLOYMENT CHAPTER 8. Chapter 8: System Testing and Deployment 2 KNOWLEDGE CAPTURE (Creation) KNOWLEDGE TRANSFER KNOWLEDGE SHARING.
GBIF Mid Term Meetings 2011 Biodiversity Data Portals for GBIF Participants: The NPT Global Biodiversity Information Facility (GBIF) 3 rd May 2011.
© 2006 Cisco Systems, Inc. All rights reserved.Cisco Public 1 Version 4.0 Gathering Network Requirements Designing and Supporting Computer Networks – Chapter.
WP 9: 1 st Planning meeting summary Clarification between WP members of common objectives: Workshop planning and logistics with time- line Planning for.
Consultant Advance Research Team. Outline UNDERSTANDING M&E DATA NEEDS PEOPLE, PARTNERSHIP AND PLANNING 1.Organizational structures with HIV M&E functions.
Process Asad Ur Rehman Chief Technology Officer Feditec Enterprise.
Rafael Rodríguez Clemente. Coordinator* *Estación Biológica de Doñana, CSIC. Sevilla (Spain) MoCo Meeting, Casablanca (Morocco)
© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 6-1 Chapter 6 Decision Support System Development.
2 ASSIST for Schools/Districts An Overview of the Framework Dr. W. Darrell Barringer.
Managing Agriculture KnowledgeThrough Localized CommunityExpert System Managing Agriculture Knowledge Through Localized Community Expert System A Research.
ANALYSIS PHASE OF BUSINESS SYSTEM DEVELOPMENT METHODOLOGY.
Search Engine Optimization © HiTech Institute. All rights reserved. Slide 1 Click to edit Master title style What is Business Analysis Body of Knowledge?
Software Development Process CS 360 Lecture 3. Software Process The software process is a structured set of activities required to develop a software.
1 Chapter 11 Planning. 2 Project Planning “establishing a predetermined course of action within a forecasted environment” “establishing a predetermined.
Virtual Collaborative Social Living Community for Elderly Kick Off Event WP2 Overview Instituto Pedro Nunes Co-Living 12/3/ Paulo Freitas - Instituto.
Session 2: Developing a Comprehensive M&E Work Plan.
© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 6-1 Chapter 6 Decision Support System Development.
ICT Smartcities 2013 FP7-SMARTCITIES-2013 Kick Off Meeting Athens October 23, OPTIMising the energy USe in cities with smart decision support system.
This project is co-funded by the European Union Brussels, 16 December 2014 Overview of the Project Status & Management Issues (WP6)
This project is co-funded by the European Union 1 st Review Meeting - Brussels, December 16 th, 2014 WP 1: Smart City Energy Assessment Framework & User.
Savona, T1.3 User Requirements. Outline Task 1.3 in OPTIMUS DOW Deliverable 1.3 Content User Requirements’ definition methodology Collected.
Savona, WP3 Optimus DSS. TECNALIA LA SALLE POLITO April 2014 MS4 August 2014.
Information systems based on semantic technologies to improve energy efficiency in architecture and urban planning Leandro Madrazo, Álvaro Sicilia Research.
ICT Smartcities 2013 FP7-SMARTCITIES-2013 Kick Off Meeting Athens October 23, OPTIMising the energy USe in cities with smart decision support system.
ICT Smartcities 2013 FP7-SMARTCITIES-2013 OPTIMUS Concept, Objectives and Work Plan OPTIMising the energy USe in cities with smart decision support system.
Savona, 10th April 2014 OPTIMUS Linking Smart Cities with Energy Optimisation.
ICT Smartcities 2013 FP7-SMARTCITIES-2013 WP6 – Project Management OPTIMising the energy USe in cities with smart decision support system (OPTIMUS) Objective.
First Ideas on the Methodological Approach OPTIMising the energy USe in cities with smart decision support system (OPTIMUS) Presentation by Stella Androulaki.
FIRST REVIEW MEETING, Brusells, T2.6 - Renewable energy production data capturing module.
The Components of Information Systems
WP1 – Smart City Energy Assessment and User Requirements
The Components of Information Systems
Where We Are Now. Where We Are Now Defining the Project (100) Step 1: Defining the Project Scope Step 2: Establishing Project Priorities Step 3: Creating.
Information System Building Blocks
Presentation transcript:

ICT Smartcities 2013 FP7-SMARTCITIES-2013 Kick Off Meeting Athens October 23, OPTIMising the energy USe in cities with smart decision support system (OPTIMUS) Objective ICT Optimising Energy Systems in Smart Cities Small or medium scale focused research project (STREP) “FUNITEC- Engineering and Architecture La Salle Ramon Llull University, Barcelona, Spain” Dr. Leandro Madrazo, Álvaro Sicilia, Gonçal Costa

Index -Scope -Objectives -Tasks -Deliverables -TimeLine -Milestones -Actions -Requirements capture -Risks

Scope The semantic framework will gather and integrate the data coming from the various data sources. Then, data mining process will be carried out to add metadata to data (patterns, clusters, etc). The inference engine will receive as input the data and metadata, and based on the rules included in it, it will suggest the best alternatives for the short-term energy planning. The front-end environment will show the data, criteria and suggested alternatives in the right form to the end user (city authorities).

Objectives These different types of data will be treated by the corresponding DSS modules. They will also inform the OPTIMUS DSS requirements and objectives. The data which will be modelled using semantic technologies and provided to different stakeholders to develop and apply advanced analysis procedures. The semantic data integration will be implemented with the participation of domain experts and data owners so as to integrate the data sources into a global data space for a city. This integration processes encompass data cleaning, data linking, data enrichment, data publishing and testing, as depicted in the following figure. Semantic integration process

Objectives This work package will focus on the construction of the OPTIMUS DSS architecture according to the requirements and objectives set in the WP1. The main objectives are: 1.To make use of the data captured in WP2 which will be transformed into meaningful information for different stakeholders applying advanced analysis procedures.  Tasks: T3.1, T3.2 and T The information and recommendations provided by the DSS will be facilitated to stakeholders through open environments which will foster the interaction between data and users with the purpose of achieving the energy optimization objectives. 3. To meet all the necessary requirements and expectations of the end-users and will act as decision support tool for energy optimization in a rapid and sustainable way for different stakeholders involved. The DSS front-end will be user-friendly and it will be generic and adaptable enough to be applied in different cities.

Tasks Task 3.1: Semantic Framework For Data Integration (FUNITEC)  Implementation of methods and tools to provide an integrated access to the data captured and modelled in WP2 using semantic technologies. Task 3.2 Data Mining Analysis (FUNITEC)  Receives the semantic data from the semantic framework (T3.1) and applies data mining analysis generating a metadata layer which enhances the source data. Task 3.3 Inference Rules (POLITO)  Develop/Implement all the knowledge and intelligent rules for the energy optimization, based on the data that the DSS will receive as input (Inference Engine) Task 3.4: Front-End Environments (FUNITEC)  Create web-based environments which will provide access to different types of stakeholders in diverse forms suited to their requirements and knowledge. Task 3.5: Integration and Development of OPTIMUS DSS (FUNITEC)  Integration of the semantic data, analysis tools, inference engine and web environments (developed in T3.1, T3.2, T3.3 and T3.4) in a common architecture.

Deliverables D3.1. Published data in an open data portal M15  The data semantically integrated will be published in a data portal providing both HTML and RDF interface D3.2. Analysis tools to process data and inference rules M17  Tools identified and implemented as part of the DSS, including the customization of the data mining methods selected. D3.3. Inference engine integrated in the management environment M19  To create an inference from the semantic data D3.4. Functional end-user environment M17  The end-user environment implemented as part of the DSS validated and tested by the final user. D3.5 Integrated DSS system M21  Semantic framework, data portal, analysis tools, inference engine, management and end-user environments completely integrated D3.6 Integrated DSS system, fine-tuned version M34  Semantic framework, data portal, analysis tools, inference engine, management and end-user environments completely integrated

TimeLine Requirements (e.g. use cases, indicators, users, tools) are required to model the data based on the outputs provided by T2.1. Creation of links between data elements of different sources is required (e.g. the energy consumption data monitored in T2.3 to link them to the energy prices data captured in T2.5.) Development of the environments will be based on the user requirements gathered in T1.3. Pilot phase requires the implementation of the DSS to test it in different environments

Timeline WP3 -Data integration -Data mining -Inference rules -Front-end WP4 -DSS customization -Feedback from SCEAF implementation WP1 -SCEAF -User requirements WP2 -DSS Architecture -Data capture modules Requirements (e.g. use cases, indicators, users, tools, data, needs) are required to implement the DSS based on the outputs provided by -T1.3 User requirements -T2.1 DSS architecture -T4.1 Application of SCEAF in cities The feedback gathered in the Pilot implementation will retrofit the DSS implementation Requirements (e.g. use cases, indicators, users, tools, data, needs) are required to implement the DSS based on the outputs provided by -T1.3 User requirements -T2.1 DSS architecture -T4.1 Application of SCEAF in cities The feedback gathered in the Pilot implementation will retrofit the DSS implementation DSS to test it in different environments.. DSS to test it in different environments.. WP3 receives from other WPS WP3 provides to other WPS

Milestones Milestone 3 (month 34) - Design, Architecture and development of OPTIMUS DSS (WP2, WP3) - Fine-tuned version of OPTIMUS DSS fully operational.

Requirements capture process A first contact has been established with P-11 Sant Cugat to know the data, users and services which would be needed. A survey has been sent to Sant Cugat. This can be a starting point of the requirement capture process to carried out in the three pilot cities (SCEAF, Task 1.2, Task 4.1).

Requirements capture process: survey 1. ABOUT DATA SOURCES - Energy consumption data (monitoring) - List buildings you have energy consumption data of (monitoring, bills,…). - Describe each of them: Building dimensions, Building materials, Building destination, Occupancy, Appliances, consuming electricity, or other energy sources, Instrumentations (HVAC…)… - Energy prices - Which kind of energy prices do you have (tariffs, contractual options, special offers)? - How are you managing the energy prices? - Do you have real time access to energy prices from the energy providers? (PDF, Excel, web page…) - Energy production -Which energy production facilities do you have in your buildings/districts? - Describe each of them: Energy source (solar, wind, waterpower, renewed biomass…), energy produced, operation schedule, monitoring sensors and counters… - Which energy production management solutions are you deploying? This survey could be a starting point for Task 1.2

Requirements capture process: survey 1.ABOUT DATA SOURCES 2.ABOUT END-USERS 3.ABOUT NEW SERVICES This survey could be a starting point for Task 1.2

Requirements capture process: survey 1. ABOUT DATA SOURCES - Weather conditions Do you have/use any weather forecast system? - Upcoming events Do you have any system to capture data about citizens’ activities/events carried out in your buildings? Describe them: channels (web page, forums, social networks…),. This survey could be a starting point for Task 1.2

Requirements capture process: survey 2. ABOUT END-USERS - Who are the decision-makers who will use the data facilitated by the Decision Support System (DSS)? - Describe each of them: role, activities carried out by them, external company/administration… - Who are the users who will implement the actions to optimize existing conditions (facility managers, energy prices manager…)? - Describe each of them: role, tasks carried out by them, external company/administration… 3. ABOUT NEW SERVICES - Regarding energy prices which actions can you carry out/improve (changing a tariff, contractual options, special offers…)? - Regarding facilities management, which actions can you carry out/improve (operating procedures…)? This survey could be a starting point for Task 1.2

Risks. Risk DescriptionProbabilityImpactMitigation Plan OPTIMUS DSS requirements not adequate for development. LowHighThe OPTIMUS DSS architecture will be designed by the WP2. However, these will not be created in a vacuum. Initial design activities will be already underway giving the opportunity to technical personnel to articulate their need for specific and useful requirements during the implementation of the particular WP. OPTIMUS DSS is off-spec relative to the initial design of the prototype or fails performance and functionality testing MediumHighDevelopment will have constant oversight and quality controls. A rigorous testing and software/hardware quality control framework will be designed as a separate task and used for continuous testing and adaptations of the prototype platform. OPTIMUS DSS Pilot application is hampered due to technical problems with the prototype platform MediumHighThe testing and quality procedures will ensure software/hardware quality before the OPTIMUS DSS application. Continuous upgrades of the System mean that resources will be on hand to ensure quick responses to bugs and technical problems The reduction of energy consumption and CO2 emissions in the pilot cities is lower than anticipated due to insufficient consideration of OPTIMUS DSS suggestions from pilot cities’ decision makers. MediumHighThe pilot cities’ decision makers will be strongly involved in the project since its first phases. This reassures that their needs and expectations from the system and its envisaged functionalities will be taken into consideration in its design and development, thus increasing the OPTIMUS DSS level of acceptance. In addition during the pilot operation period, there will be strong collaboration among all consortium partners and city authorities so as to reassure that decision makers will remain highly committed to project objectives.