PORTALE DELLA DIDATTICA

PORTALE DELLA DIDATTICA

PORTALE DELLA DIDATTICA

Elenco notifiche



IoT platforms for spatial analytics in smart energy systems

01UJVRS

A.A. 2019/20

Course Language

Inglese

Degree programme(s)

Doctorate Research in Urban And Regional Development - Torino

Course structure
Teaching Hours
Lezioni 25
Lecturers
Teacher Status SSD h.Les h.Ex h.Lab h.Tut Years teaching
Patti Edoardo   Professore Associato IINF-05/A 15 0 0 0 1
Co-lectures
Espandi

Context
SSD CFU Activities Area context
*** N/A ***    
2019/20
PERIOD: APRILE - MAGGIO Finalità del corso in inglese: The continuous evolution of Internet of Things (IoT) technologies is evolving the concept of smart cities as well as the surrounding environments. From pervasive sensors, through computational nodes at the edge of the network to the cloud and final user applications, the data flow chain makes available to the user a very large and heterogeneous amount of data. IoT platforms are at the core of this chain, providing seamless access to data independently from the hardware devices and making possible the interoperability with other data sources (e.g. Geographic Information System and System Information Models). Despite the availability of IoT platform solutions either commercial and open-source, research is still very active to design and implement flexible, easy to use and efficient web-service oriented software infrastructures (i.e. middleware). After providing the main basic concepts of the Internet-of-Things (main communication paradigms, main development frameworks), this course will present the current IoT platform infrastructures starting from consolidated literature solutions up to the latest platforms envisioned by recent research projects. The main challenges and directions about future platform will be outlined, putting them in the context of real case studies. The course will be focused also on presenting innovative IoT platforms for energy distribution systems for spatial planning. Furthermore, the course will outline possible use of open-data and Volunteered Geographic Information (VGI) for spatial analytics in energy systems
PERIOD:APRIL - MAY Finalità del corso in inglese: The continuous evolution of Internet of Things (IoT) technologies is evolving the concept of smart cities as well as the surrounding environments. From pervasive sensors, through computational nodes at the edge of the network to the cloud and final user applications, the data flow chain makes available to the user a very large and heterogeneous amount of data. IoT platforms are at the core of this chain, providing seamless access to data independently from the hardware devices and making possible the interoperability with other data sources (e.g. Geographic Information System and System Information Models). Despite the availability of IoT platform solutions either commercial and open-source, research is still very active to design and implement flexible, easy to use and efficient web-service oriented software infrastructures (i.e. middleware). After providing the main basic concepts of the Internet-of-Things (main communication paradigms, main development frameworks), this course will present the current IoT platform infrastructures starting from consolidated literature solutions up to the latest platforms envisioned by recent research projects. The main challenges and directions about future platform will be outlined, putting them in the context of real case studies. The course will be focused also on presenting innovative IoT platforms for energy distribution systems for spatial planning. Furthermore, the course will outline possible use of open-data and Volunteered Geographic Information (VGI) for spatial analytics in energy systems
Part 1: Software solutions for Internet-of-Things platforms 1. Introduction to the Internet of things 2. Introduction to communication paradigms a. request/response through HTTP REST Web Services b. publish/subscribe through MQTT 3. Software requirements to develop scalable IoT platforms 4. Design patterns to develop distributed software platforms (SOAP, Microservice) 5. Deployment paradigms in cloud systems (IaaS, PaaS, SaaS) 6. Example of software IoT platforms (LinkSmart, Seempubs, Dimmer, Flexmeter) 7. Services Life Cycle Part 2: Spatial Analytics in Smart Energy Systems 1. Introduction to spatial data and available web standards 2. Open-data and Volunteered Geographic Information (VGI) 3. IoT systems for environmental monitoring 4. State of the art solutions for PV planning 5. Innovation in photovoltaic planning tools 6. PV-in-grid: a co-simulation framework for renewable energy assessments 7. Agent Based Models for photovoltaic diffusion in cities 8. Load-Sim: using open-data to mimic energy consumption in cities based on citizens’ behaviours 9. State of the art solutions for Thermal Energy consumption in Buildings 10. Thermal energy signature for buildings 11. Mapping smart-metering-infrastructure data 12. Future challenges
Part 1: Software solutions for Internet-of-Things platforms 1. Introduction to the Internet of things 2. Introduction to communication paradigms a. request/response through HTTP REST Web Services b. publish/subscribe through MQTT 3. Software requirements to develop scalable IoT platforms 4. Design patterns to develop distributed software platforms (SOAP, Microservice) 5. Deployment paradigms in cloud systems (IaaS, PaaS, SaaS) 6. Example of software IoT platforms (LinkSmart, Seempubs, Dimmer, Flexmeter) 7. Services Life Cycle Part 2: Spatial Analytics in Smart Energy Systems 1. Introduction to spatial data and available web standards 2. Open-data and Volunteered Geographic Information (VGI) 3. IoT systems for environmental monitoring 4. State of the art solutions for PV planning 5. Innovation in photovoltaic planning tools 6. PV-in-grid: a co-simulation framework for renewable energy assessments 7. Agent Based Models for photovoltaic diffusion in cities 8. Load-Sim: using open-data to mimic energy consumption in cities based on citizens’ behaviours 9. State of the art solutions for Thermal Energy consumption in Buildings 10. Thermal energy signature for buildings 11. Mapping smart-metering-infrastructure data 12. Future challenges
• Tuesday 28 April 14:00-16:00 -> Tuesday 5 May 14:00-16:00 • Wednesday 29 April 14:00-16:00 -> Wednesday 6 May 14:00-16:00 • Thursday 30 April 14:00-17:00 -> Thursday 7 May 14:00-17:00 • Wednesday 6 May 14:00-15:30 -> Wednesday 13 May 14:00-15:30 • Tuesday 12 May 14:00-15:30 -> Tuesday 19 May 14:00-15:30
• Tuesday 28 April 14:00-16:00 -> Tuesday 5 May 14:00-16:00 • Wednesday 29 April 14:00-16:00 -> Wednesday 6 May 14:00-16:00 • Thursday 30 April 14:00-17:00 -> Thursday 7 May 14:00-17:00 • Wednesday 6 May 14:00-15:30 -> Wednesday 13 May 14:00-15:30 • Tuesday 12 May 14:00-15:30 -> Tuesday 19 May 14:00-15:30
Modalità di esame:
Exam:
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Gli studenti e le studentesse con disabilità o con Disturbi Specifici di Apprendimento (DSA), oltre alla segnalazione tramite procedura informatizzata, sono invitati a comunicare anche direttamente al/la docente titolare dell'insegnamento, con un preavviso non inferiore ad una settimana dall'avvio della sessione d'esame, gli strumenti compensativi concordati con l'Unità Special Needs, al fine di permettere al/la docente la declinazione più idonea in riferimento alla specifica tipologia di esame.
Exam:
In addition to the message sent by the online system, students with disabilities or Specific Learning Disorders (SLD) are invited to directly inform the professor in charge of the course about the special arrangements for the exam that have been agreed with the Special Needs Unit. The professor has to be informed at least one week before the beginning of the examination session in order to provide students with the most suitable arrangements for each specific type of exam.
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