Budapest University of Technology and Economics, Faculty of Electrical Engineering and Informatics

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    Smart City Infocommunication Technologies

    A tantárgy neve magyarul / Name of the subject in Hungarian: Okos városok infokommunikációs technológiái

    Last updated: 2024. február 15.

    Budapest University of Technology and Economics
    Faculty of Electrical Engineering and Informatics
    Course ID Semester Assessment Credit Tantárgyfélév
    VITMMA15   2/1/0/v 5  
    3. Course coordinator and department Dr. Vidács Attila,
    4. Instructors
    Dr. Vidács Attila, docens, TMIT
    Dr. Fehér Gábor, docens, TMIT
    Dr. Vida Rolland, docens, TMIT
    5. Required knowledge -
    6. Pre-requisites
    Kötelező:
    NEM
    (TárgyEredmény( "BMEVITMMA09", "jegy" , _ ) >= 2
    VAGY
    TárgyEredmény("BMEVITMMA09", "FELVETEL", AktualisFelev()) > 0)

    A fenti forma a Neptun sajátja, ezen technikai okokból nem változtattunk.

    A kötelező előtanulmányi rend az adott szak honlapján és képzési programjában található.

    7. Objectives, learning outcomes and obtained knowledge
    One of the basic requirements of smart cities is to be able to observe the city's operations, the movement of people and vehicles, the evolution of environmental parameters, the processes in the city, and then, after processing the raw data collected, to be able to use the information extracted from it to intervene in these processes, making the city's operation more efficient through various adaptive services. This requires an appropriate infocommunication infrastructure, of which the sensing infrastructure and the communication infrastructure are key elements. The objective of this course is therefore to present the hardware and software architectures, communication protocols, specific challenges and dedicated solutions for the networking of sensors in smart cities. In addition, special attention will be paid to the communication issues of intelligent transport systems in smart cities, networked vehicles and different solutions for vehicle communication.
    8. Synopsis
    Lectures:

    1. Introduction to the world of smart cities. What is meant by sensing and communication infrastructure. What are the hardware and software architectures of smart sensors? Hardware components of sensor "motes". 

    2. Sensor operating systems (e.g. Contiki, FreeRTOS, TinyOS).

    3. Sensor communication protocols: physical layer, sleep-wake scheduling, time synchronisation. Sensor radios (LoRa, NB-IoT, 5G mMTC). Wired solutions (MODBUS, Ethernet/IP, Profinet).

    4. Data link layer, medium access control (sensor MAC). 

    5. Network layer, energy and location-aware routing; attribute-based addressing, clustering; data-centric operation. 

    6. Transport layer (TCP-like protocols without global addressing, low storage requirements).  

    7. Sensor network architectures. Sensor network design issues. Topology construction and management, single and multi-hop communication, energy saving, topology control.

    8. Advanced sensors for intelligent vehicles: odometer, tachometer, radar, lidar, ultrasonic sensors, cameras

    9. In-vehicle communication technologies: CAN bus, Flexray, LIN, MOST

    10. WiFi-based vehicle communication. DSRC, WAVE, IEEE 802.11p, IEEE 1609, ITS-G5 

    11. Cellular vehicle communication technologies (C-V2x). 5G NR V2X, 6G V2X. Vehicle-to-vehicle communication technologies and protocols.
     
    12. VANET (Vehicular Ad hoc Networks) networks. Advanced mobility models, routing and clustering protocols. Geographic based routing, advantages, disadvantages and applicability. Hybrid communication solutions.

    13. Technology solutions for self-driving vehicles.
     
    Detailed topics for the exercises:

    1. Detailed description and discussion of homework assignments, assignment of tasks and tools. Presentation of assignment, assignment and student safety briefing. Detailed presentation of optional tools and platforms

    2. Building sensors from microcontroller and radio module. Introduction to simple sensors and interferers. Introduction to the development environment.

    3. Sensor communication exercises. Building an Internet connection. Remote data acquisition, data display and data analysis. Deployment and use of containerised services.

    4. Homework intermediate checkpoint: presentation of system designs, details of technological solutions, joint discussion

    5. Use of IoT platforms. Demonstration of the use of some platforms, programming, extension options.

    6. Demonstration and programming of cloud-based IoT data processing. Building services.

    7. Presentation, joint discussion and evaluation of home tasks. 
    9. Method of instruction
    - Lectures 

    - Classroom computer exercises

    - Independent work (homework)
    10. Assessment
    During the semester: 1 summative type mid-term examination and 1 homework assignment.
    Successful completion of the mid-term exam and the homework is a prerequisite for signature and passing the exam.
     
    During the examination period: written examination.
    11. Recaps
    The mid-term exam can be retaken up once.
    The deadline for the submission of homework is during the semester. Homework may be handed in by the deadline set for one week after the semester end.
    12. Consultations On request, by prior arrangement with the lecturer.
    14. Required learning hours and assignment
    Kontakt óra42
    Félévközi készülés órákra
    Felkészülés zárthelyire20
    Házi feladat elkészítése40
    Kijelölt írásos tananyag elsajátítása8
    Vizsgafelkészülés40
    Összesen150
    15. Syllabus prepared by
    Dr. Attila Vidács, Associate Professor, TMIT
    Dr. Vida Rolland, Associate Professor, TMIT
    Dr. Gábor Fehér, Associate Professor, TMIT