inLab FIB & Industry 4.0
1 like513 views
InLab FIB at UPC is a research and innovation lab focused on ICT, data science, and simulation, with over 35 years of experience collaborating with public and private institutions. Their mission is to transfer knowledge through multidisciplinary projects, providing technical assessments, innovative solutions, and learning support across various domains. The lab offers expertise in areas like smart mobility, cybersecurity, data science, and service engineering to enhance industry 4.0 applications and societal benefits.
inLab FIB & Industry 4.0
- 1. inLab FIB & Industry 4.0 www.cit.upc.edu http://inlab.fib.upc.edu @inLabFIB Director Professor Josep Casanovas [email protected] Ernest Teniente [email protected]
- 2. inLab FIB UPC is a research & innovation lab of the Barcelona School of Informatics (FIB) at UPC It has over 35 years of experience with providing applications & services for public and private institutions Integrates experts with broad experience (technical and academic staff) with young talent (students) MISSION To transfer knowledge to society through developing human talent and R&D&i multidisciplinary projects based on breakthrough ICT technologies, simulation and data science. 2
- 3. Collaboration with companies Collaborations (some examples): • Visualization, analysis & optimisation of current and future scenarios -> Risk reduction • Development of innovative ICT solutions and applications • Technical assessment, training and specialized services in our expertise areas Research & Development collaboration models: Open Innovation & Joint Labs, Industrial doctorates, Joint collaboration international (H2020) and national projects, Subcontracting Sponsorship Programmes (Talent Program) 4
- 4. Recent partners See full list at http://inlab.fib.upc.edu/en/col-laboradors Members of:
- 5. R + D Areas of expertise Combining ICT, data science and simulation
- 6. Modeling, simulation & optimization • Feasibility studies and/or improvements to systems and processes • Applied to industry 4.0, transport, logistics, and emergency systems. • Social simulation applied to demography, population dynamics, epidemiology… • Energy efficiency in buildings and transport Microscopic simulation of passengers movements in the new terminal of the airport of Barcelona. AENA-INDRA More information: http://inlab.fib.upc.edu/en/experteses/mod elitzacio-simulacio-i-optimitzacio 7
- 7. Smart Mobility Public transport systems, traffic management, dynamic Routing applications, traffic and mobility data processing • New generation forecasting models for high quality traffic and travel information, short-term real-time predictions. • Traffic data analytics: data filtering, completion and fusion, big data, interoperability, floating passenger data. • New mobility concepts: ridesharing, demand- responsive transportation modes, connected cars. • Multimodal journey planners, dynamic vehicle routing for fleets. • Macro, meso and micro traffic simulation. More information: http://inlab.fib.upc.edu/en/experteses/smar t-cities 8
- 8. Mobile Solutions • Integration with wearables technology and IoT • Mobile applications for geoservices based on OpenStreetMap • Mobile Apps Learning Lab • iOS, Android Apps development • Leading OpenStreetMap in Catalonia. More information: https://inlab.fib.upc.edu/en/experteses/aplicacions-mobils-i- gis ParkFinder - SEAT 9
- 9. Cybersecurity • Training and cyber security awareness • Security audits • Forensic analysis • Incident Response • Monitoring of networks • Development of systems for detecting malware and electronic fraud • Security of applicationsFirst Spanish Response Team More information: http://inlab.fib.upc.edu/en/experteses/segu retat-i-infraestructures-tic 10
- 10. ICT environments and services to support learning • Learning Analytics • Smart learning environments • Information systems for university management, computer labs • Systems for measuring and analysing academic results. More information: http://inlab.fib.upc.edu/en/experteses/entorns-i-serveis-tic-de-suport- laprenentatge-i-la-gestio-universitaria 11
- 11. Data Science and Big Data Smart data, methods and statistical techniques for analysing and processing data and their interoperability • Data mining • Advanced statistical analysis • Measurement of intangibles (satisfaction, quality, etc.) • Open data • Integration, fusion and processing of large volumes of data • Big data architectures • Dashboards , data warehouse, BI More information: http://inlab.fib.upc.edu/en/experteses/anali sis-i-tractament-de-dades Queries and large data matrix analysis for the Centre for Opinion Studies (CEO) of the Government of Catalonia 12
- 12. Software (service?) engineering • (Semantic) ontologies • Service and business process engineering • Semantic integration • Interoperability and integration of systems • Software as a Service and interoperability technologies More information: http://inlab.fib.upc.edu/en/experteses/inter net-collaborativa 13
- 13. System Several visions of a system
- 14. ? ? Industry 4.0 world • Technology is not a problem • Raw data (in itself) does not have a (huge) value • How do we transform data into knowledge? • How do we achieve a common understanding of the service being provided?
- 15. All engineering disciplines are founded on models that are analyzable and can predict the properties of the artifact being engineered Key problem: have to give an unambiguous, easy to understand account of our understanding of an organization and how it works, also how the new system will fit in that organization We can do so with English (textual) descriptions; but such descriptions are often cumbersome, incomplete, ambiguous and can lead to misunderstandings Then, we use ontologies for this purpose, i.e. to describe proposed requirements and designs for the new system Ontologies capture people’s understanding (conceptualization) of what is being handled (Semantic) Ontologies
- 16. “Quality is never an accident. It is always the result of intelligent effort”. William A. Foster “The hardest single part of building a software system is deciding what to build, maintain / check / evolve “ Fred Brooks Sistematization Organization Communication Analysis Empathy Negotiation Conflict resolution ... Why is this also important?
- 17. The idea is not ... ...neither... RE goals Features of ontology definition Criteria Methodology Tools People Specification strategy Context Artifacts How should we do it?
- 18. An example in the BIG IoT project
- 19. Languages such as UML are based in first order logic Only symbols? Models “speak” in an unambigous way and they can provide a “response” with analysis tools Automation capability (analysis, verification, generation...) Traffic management service: city map
- 20. Test-driven Software Development Ontology-based Data Access Automated Code Generation Automated Reasoning Ontology-based Data Exchange Visualization of Large Conceptual Schemas, like HL7 Learning Analytics … Other advantages of using ontologies
- 21. Business Process Modeling • Key activity in organizations Artifact-centric process modeling • Focus on data • Contrast to traditional process modeling focused on activities/processes • Business artifacts updated by services (service engineering) • BALSA framework: 4 dimensions for artifact-centric models • Characteristics • Focus on data • Intuitive • Formal • Flexible Particularly important for providing SaaS Business analysis can be performed from the models (Artifact-centric) Business Process Modeling
- 22. http://inlab.fib.upc.edu [email protected] +34 93 401 69 41 c/ Jordi Girona 1-3 Campus Nord. Edifici B6 08034 Barcelona Twitter: @inLabFIB Contact us