DISIT Lab overview

    

Work at DISIT PhD grant, for 3 years at DISIT lab UNIFI on national PhD AI training course, 2024-2028

ITA: Sistemi modellistici per l’analisi della mobilità in organizzazioni complesse

ENG: Modeling systems for the analysis of mobility in complex organizations

ITA: Il dottorando svilupperà modelli per l’analisi della mobilità a partire da dati eterogenei a livello nazionale. Questi dati potranno essere elaborati con tecniche di AI/XAI per derivare informazioni di origine destinazione, ma anche per la valutazione dei servizi e la loro pianificazione. La principale tematica è relativa alla valutazione della soddisfazione della domanda di mobilità (data dai dati di movimento delle persone) rispetto all’offerta (formalizzata tramite il trasporto pubblico di varia natura). I modelli di ottimizzazione saranno sviluppati tramite tecniche di generative AI. Il candidato potrà utilizzare le infrastrutture di calcolo del DISIT Lab Https://www.disit.org come https://www.Snap4City.org Le tematiche proposte sono volte ad apportare un significativo sviluppo della conoscenza matematica e informatica, negli ambiti di interesse del PNRR, in particolare in merito a grafi che modellano reti di trasporto. Lo studio degli aspetti teorici e pratici di questo tipo di strutture dati rientra nelle finalità del percorso di dottorato. Il dottorando avrà l’opportunità di lavorare con dati in possesso di FS e di sviluppare algoritmi e metodologie data driven nell’ambito della mobilità.  Il progetto è pertinente con i criteri di ammissibilità e in particolare favorisce l’interdisciplinarità, l'adesione a reti internazionali e l’intersettorialità promosse dal PNRR. 6 mesi di lavoro presso Ferrovie dello Stato

ENG: The PhD student will develop models for the analysis of mobility starting from heterogeneous data at a national level. This data can be processed with AI/XAI techniques to derive source-destination information, but also for the evaluation of services and their planning. The main topic is related to the evaluation of the satisfaction of the demand for mobility (given by the movement data of people) compared to the supply (formalized through public transport of various kinds). The optimization models will be developed using generative AI techniques. The candidate will be able to use the computing infrastructures of the DISIT Lab Https://www.disit.org as well as https://www.Snap4City.org  The proposed topics are aimed at bringing a significant development of mathematical and IT knowledge, in the areas of interest of the PNRR, in particular regarding graphs that model transport networks. The study of the theoretical and practical aspects of this type of data structures is part of the aims of the doctoral programme. The doctoral student will have the opportunity to work with data held by FS and to develop data driven algorithms and methodologies in the field of mobility.   The project is relevant to the eligibility criteria and in particular favors interdisciplinarity, membership of international networks and inter-sectorality promoted by the PNRR. 6 months of work at Ferrovie dello Stato

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kind: DN 630

referente: Paolo Nesi, paolo.nesi@unifi.it

tel: +39-3355668674

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DISIT LAB competences: https://www.disit.org/node/7190

Visit the Smart City Platform of DISIT Lab: Snap4City https://www.snap4city.org solution which is 100% open source, support cloud and scalability for processing and IOT/IOE, respect user needs and privacy according GDPR and to the different user kinds, provide tools and community for co-creation; mixt data driven, stream and batch processing; it is fully based on microservices and using easily replaceable tools. Snap4City solution has been designed to be Click to access Snap4City tools main entry Click the image to access Snap4City scalable, flexible, safe and respectful of privacy, endowed of a powerful semantic reasoner based on Km4City multi-domain semantic model and tools (https://www.km4city.org ). A special attention is provided to enable the development of applications in multiple domains and not only on mobility and transport, tourism, health, welfare, social, etc.  

DISIT Lab of UNIFI is the most active Big Data / AI lab of the University of Florence, metropolitan Tuscany area, and it is an official Regional Lab in Tuscany, Certified Experts of FIWARE, member of GAIA-X, EDIH Tuscany X.0, UNINFO ISO, CBD-AI of Tuscany Region, national CINI, national CNIT, national PhD on AI,  involved into IFAB, etc., and in several international boards as those of BBC.

DISIT successfully developed a relevant number of International and National research, development and innovation projects and direct contract with industries and public administrations.

DISIT Lab is strongly active on artificial intelligence (ML, generative AI, deep learning, Bert, continuous learning, etc.), Explainable AI, neuro-symbolic AI, big data, knowledge engineering, security and privacy, GDPR, Digital Twins, What-if analysis, decision support, expert systems, digital twins, NLP, LLM, big data architectures, etc. https://www.snap4city.org/944

Domains of: mobility and transport, energy, environmental, Smart City, environmental, HPC, industry 4.0, NLP for justice, computer vision, ethics AI and data, etc.

Noticeable DISIT solutions are for predictions, traffic flow reconstruction and predictions, parking/bike predictions, landslide predictions, user behavior analysis, pollutant flow predictions, recommendation, matchmaking, decision support, 15Min Indexing for cities, community of energy, 3D local and global city reconstruction, people flow, engagement, decision making systems, expert systems, predictive maintenance, early warning, anomaly detections, etc.

DISIT Lab is/has working/worked for relevant public administrations in Italy, France, Belgium, Finland, Spain, Sweden, Croatia, Bosnia, Greece, etc. and for: ISPRA JRC of the European Commission, ANCI, Tuscany Region, Cipro ministry, etc. And for/with noticeable companies as: BBC, Eutelsat, Thales, Leonardo, TIM, ENEL, Philips, Motorola, Lutech, UNISYSTEM, ECM, Tiscali, IBM, Esseco, Italmatic, etc.

DISIT cloud infrastructure is on High availability, HA, DRS, FT.  

 
DISIT research areas: 
  • Technologies and techniques in data analytics, artificial intelligence, Explainable AI, semantic computing, big data, knowledge mining and representation, security and privacy, GDPR, Digital Twins, production control, What-if analysis, decision support tool, experts systems, linked open data, formal models, etc. 
  • Are noticeable DISIT solutions for: predictions, predictive maintenance, early warning, anomaly detections, traffic flow reconstruction and predictions, smart parking, smart biking, bike sharing, user behaviour analysis, pollutant flow predictions, recommendation, user profiling, indoor/outdoor navigation, matchmaking, decision support, sentient and autonomous agents and tools, 15Min Indexing for cities, etc. 
  • In the recent years, a special attention has been given to big data analysis for people flows, pedestrian, and vehicles by means of data analysis coming from mobile, sensors, cell phones, etc., such as evident from the publications and projects.
  •  
  • DS4SSCC Blueprint and Snap4City
  • CityVerse and Snap4City
  • Snap4City vs MIMs Plus Living-in.EU Technical Specifications

The DISIT research group consists of about 20 people working on smart city, industry 4.0, artificial intelligence, data analytics, big data analysis with a special care to on domains of mobility and transport, environment, energy, health, justice, retail, quality of life. DISIT lab has a dedicated datacenter for bigdata solutions on which https://www.snap4city.org and Twitter Vigilance are operated, providing services for a large number of cities and regions

  • Smart City integrated solutions: https://www.snap4city.org
  • Data Mining and understanding: OD ingestion, quality improvement, data fusion, reconciliation
  • Open Data: OD, LOD, RDF stores visual tools, link discovering, enrichment, such as: https://log.disit.org
  • Data analytics: statistics, clustering, logistic and holistic regression, machine learning, artificial intelligence, deep learning, XAI, indexing and search, similarity distance,  
  • Semantic computing: ontology / knowledge modeling, reasoning, deduction, recognition, disambiguation, prediction, inference, such as: https://www.disit.org/6568
  • high performance distributed systems, Grid and parallel computing: https://www.disit.org/6566, https://www.disit.org/5551
  • RDF store: indexing, high performance, parallel querying
  • Content and data protection: IPR modeling, conditional access, digital rights management, MPEG-21 (http://www.axmedis.org), https://www.disit.org/5509,  protected content players, etc.

 

DISIT Lab is/has working/worked for many relevant public administrations in Italy, France, Belgium, Finland, Spain, Sweden, Croatia, Bosnia, Greece, etc. and also for: ISPRA JRC of the European Commission, ANCI, Tuscany Region, etc.

DISIT solutions for: user behaviour analysis, multilingual and cross media indexing, user and collective profiling, indoor/outdoor navigation, media synchronisation, matchmaking, audio transcoding, sentient and autonomous agents and tools, open data, linked open data.

 

(see more on Publications and Current Projects page, see on the left bar of this page for the Conferences in which DISIT is directly involved). See web page of DISIT coordinator Prof. Paolo Nesi

DISIT lab may develop original solutions in RIA project as well as solutions grounded on available DISIT tools for specified TRL for IA, inovation action projects:

Skill and competences 
•    3D reconstruction, mounted display, virtual environments, global digital twin, local digital twin
•    AI algorithms and solutions  
•    AI/XAI algorithms and solutions: environment, mobility, terrain sliding
•    Big data management and analytics
•    Big Data provider 
•    BIM GIS interoperability
•    Copernicus Satellite data processing for smart city and industry  
•    Data discovery and data surrogates/replacements 
•    Data driven increase resilience of buildings and infrastructures 
•    Data flow vs work flow interoperability 
•    Data interoperability, data aggregation and semantic processing
•    Data sharing and data space federation 
•    Decision making processes
•    Digital Twin solutions: building scale and city scale 
•    GDPR platform testing and verification 
•    Green Deal objectives 
•    Industrial-Urban Symbiosis (I-US) 
•    Interoperating with haptic devices, data collection and control data driven   
•    IoT interoperability, edge, fog and cloud 
•    KPI modelling and computing
•    No-code online collaborative distributed developing environment 
•    Ontology development for cognitive reasoning 
•    Prediction and control of pollutants/aerosol, CO2, NO2, GHG; taking into account 3D flows
•    Predictive maintenance, early warning, anomaly detection 
•    Sensor networks, data aggregation, semantic models 
•    Simplified data gathering platform for satellite data 
•    symbolic and hybrid approaches 
•    Testing AI algorithms on different contexts: smart city, industry, human behaviour, mobility,  
•    Trustworthy AI, explainable AI, resilient AI 
•    Trustworthy AI, explainable AI, transparent AI 
•    What-if analysis 
 

Some Flyers as PDF (for links to the projects web pages see on the left):

 References of DISIT activities in the areas of:

  • TOURISMO: recently approved EC project on multisite innovative, AI, data management for tourism
  • AMMIRARE: recently approved EC project on data analytics, AI and infrastructure for climate impact on costal erosion and changes
  • CN MOST: national center on sustainable mobility: https://www.centronazionalemost.it/
  • EDIH Tuscany X, European Digital Innovation Hub https://www.tuscanyx.eu/
  • Herit-Data, https://herit-data.interreg-med.eu/ Interreg project for the implementation of innovative solution to better manage tourism flows impact on cultural and natural heritage sites through technologies and big data. We are the official platform for the big data collection and analysis for the areas of Florence, Mostar, Pont Du Gard, Valencia, and Greece. 
  • MOBIMART, http://interreg-maritime.eu/web/mobimart/home for the implementation of the integration of transport system, with high attention to tourism. Snap4City has been selected as a reference platform for Tuscany area.
  • Snap4City PCP of Select4Cities, which has generated the Snap4City platform presently on EOSC

(European Open Science Cloud) Https://www.snap4city.org (Coordinated by DISIT Lab, Paolo Nesi). A platform for smart city IOT as a service, what-if analysis, also implementing IOT Applications, IOT data analytic, dashboard, end-2-end secure IOT platform, etc. Which passed two PENTESTs performed by two major companies in Europe (Thales, Setek), and it has been qualified the Winner of PCP of Select4Cities.  Digital Twin: https://digitaltwin.snap4city.org/

  • REPLICATE EC H2020 SCC1 Lighthouse project https://replicate-project.eu/  development of Smart City Control Room in Florence metro Area. Today operative the solution has been totally based on Snap4City and Km4City solutions of DISIT Lab. The project as a wall has also produced solutions and pilots for energy management of building, e-taxi, etc. Control Room: https://www.snap4city.org/drupal/node/531  
  • RESOLUTE EC H2020 DR7 project http://www.resolute-eu.org/  Resilience of Urban transport System (Coordinated by DISIT Lab, Paolo Nesi). Big data Driven critical infrastructure resilience for the development of the European Guidelines of Critical Infrastructure Resilience of cities and in particular on transport systems. The solution has been based on the exploitation of data in the city area and produce hints by using a large number of data analytics for people flow prediction and analysis, evacuation paths, early warning, Twitter data sentiment analysis, social media alerting, etc.
  • TRAFAIR CEF, https://trafair.eu/ for the implementation of predictive models for environmental data such as NOX with particular attention to the pollution produced by: traffic, heating, etc.
  • MOSAIC smart mobility solutions, models and tools for: (i) the analysis and matching between the offer of transportation and demand of mobility based on census data, tourism, city facilities, etc.; (ii) connected drive solutions; (iii) prediction on parking and multimodal hubs;
  • Snap4Ispra contract with ISPRA JRC of European Commission for study and implementation of Snap4City solution on ISPRA plant and village of the EC.
  • Cyprus Smart City Strategy plan.
  • Other former EC projects: AXMEDIS, WEDELMUSIC, WEEE Life, Life project on RAE, etc. 
  • Sii-Mobility SCN smart city national project http://www.sii-mobility.org/  of MIUR (Italian ministry of research) (Coordinated by DISIT Lab, Paolo Nesi), for developing a unified mobility and transport infrastructure and solution for sustainable mobility, smart parking, dynamic traffic shape, matching demand and offer, etc. This platform produced the Km4City ontology, today well known (https://www.km4city.org  )
  • Other former national projects: Collabora, TesysRail, etc. 
  • Other Regional projects: AMPERE, Feedback, Enterprise, Soda, … GreenField, 5G, LAID (on Smart BEDs), Trace-IT, RAISS, ALTARI Soda, Almafluida Italmatic, etc.

Awards

DISIT has received a number of awards, for projects such as Snap4City, WEDELMUSIC, AXMEDIS. And Awards for best paper conferences and for innovation.
 

  • Best paper Award, on ICCSA 2023.
  • Best paper Award, on DMSVIVA 2022, for Global Digital Twin, 3D representation of cities
  • ISO MPEG award to Paolo Nesi and Pierfrancesco Bellini for the service provided as MPEG AHG chair of MPEG SMR, and editing of the Part 23 of the MPEG4 standard.
  • Best paper awards: IEEE ICECCS su TILCO, AXMEDIS, DMS2011 su OSIM, DMS2014 con Mobile emergency, DMS2015 con NLP on Hadoop.
  • 4 different Innovations of DISIT Lab have been selected by the Italian Ministery Agency for the diffusion of Innovation Technologies in the national competition Italy of Innovators.
  • winner of MIREX 2009 competition: DISIT partecipated to MIREX competition for the 2009, about the polyphonic music transcoding algorithms and tools. Multiple Fundamental Frequency Estimation & Tracking Results. DISIT resulted to be the winner for the Tukey-Kramer HSD Multi-Comparison for Task2B (Piano). Conference 2009.
  • AXMEDIS FP6 IST research and development project: considered as one of the most succesfull IP projects of the FP6 in the area of content and tools. Social Network and content demonstration: XMF
  • WEDELMUSIC project has been selected as one of the best top 20 projects in the area of “Cross media content and publishing” for the FP 5 of the European Commission. On such grounds it has been granted with the support of the ADOPT-IT project, even after the WEDELMUSIC project reached its end.
  • Discovery technology award: DISIT reached the final in the area of Information Technology, among several submitted papers, with his research work for the MOODS project, where Prof. P. Nesi was coordinator. The project itself has been proposed for candidacy by the Disney Company in 2001.
  • Pirelli Internet Technology Award 2002, DISIT reached the final in the area of Information Technology among more than 1200 submitted papers, with his research work for the project WEDELMUSIC IST FP 5.     
 

DISIT Spin off

has generated Snap4 srl, and DAI spinoffs

 

DISIT Managed networks and communities

DISIT is managing Snap4City.org: https://www.snap4city.org

 

DISIT Master Studies, Ph.D. Courses and work with

If you are interested in performing a stage, thesis or a doctoral study at DISIT please contact his director Prof Paolo Nesi and visit the related web pages for thesis, projects and didaptical activities 

 

Contacts

Paolo Nesi paolo.nesi@unifi.it