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IoT - Internet of Things

IoT - Tárgyak internete
A tantárgyleírás hatályossága
Hatályosság kezdete:
2026. March 21.
Hatályosság vége:
Subject name (Hungarian, English)
IoT - Tárgyak internete
IoT - Internet of Things
Subject code BMEVITMMB13
Subject type
Training Level
Course types and hours (weekly/semester)
Course type lecture tutorial laboratory
hours (weekly) 2 1 0
type (linked/independent) derived course
Assessment type vizsga
Credits 5
Subject coordinator
DR. Vidács Attila
position: egyetemi docens
Responsible department
Távközlési és Mesterséges Intelligencia Tanszék
Faculty Villamosmérnöki és Informatikai Kar
Subject website https://www.tmit.bme.hu/vitmmb13
Primary curriculum type
Direct prerequisites – Strong prerequisite none
Direct prerequisites – Weak prerequisite none
Direct prerequisites – Parallel prerequisite none
Direct prerequisites – Milestone prerequisite none
Direct prerequisites – Exclusion none

Objectives

Programme
LECTURES:
1. Introduction: the world of IoT, trends in the IoT world. The emergence of IoT in smart cities, smart homes and industry. IoT devices requirements and capabilities.
2. IoT technologies: Low-power wireless solutions. Resource-efficient solutions. Low-power, low-voltage, low-power solutions.
3. IoT communication: low-power, short-range radio communication solutions. Low-power, long-range radio communication solutions.
4. IoT network architectures. Low-power, low-power IoT networks. Measurement data delivery over the Internet. Server/client and advertisement/subscription models in IoT communications. IoT data visualization.
5. IoT in the cloud: different IoT cloud platforms and their connection to physical sensors. IoT platforms: IBM Watson IoT, Google Cloud, MS Azure, AWS IoT, ThingSpeak, OpenRemote. Communication between different platforms and components.
6. IoT reliability and security. Authentication of IoT devices.
7. IoT and Artificial Intelligence. Data processing. Edge AI. Cloud solutions: TorchServe and TensorFlow Serving.
8. Industrial IoT (IIoT) solutions. IoT and Robotics. IIoT platforms. Case study: EU 5G-SMART, Arrowhead.
Smart City solutions. Case study: Smart Santander. Massive IoT.
9. Smart city solutions. Case study: smart Santander. Massive IoT.
10. Supporting infrastructures for intelligent transport systems. Smart parking solutions.
11. Smart home. Open source home automation solutions. Home Assistant, OpenHAB.
12. Environmental monitoring. Case studies: rainforest monitoring, water/air/environmental pollution. Global solutions (e.g. tsunami, earthquake monitoring and forecasting).
13. eHealth. Wearable devices. WPAN and in-body wireless IoT solutions.
 
PRACTICES:
 
1. Detailed presentation, discussion and assignment of the mid-term homework. Transfer of knowledge on safety of devices and students. Presentation of optional tools and platforms.
2. Sensor communication exercise. Building sensors, connecting to the Internet.
3. Remote data collection, data visualisation and data analysis. Deployment and use of containerised services.
4. Homework intermediate checkpoint: presentation of system designs, details of technological solution, joint discussion.
5. Use and extension of smart home IoT platform.
6. Use and programming of cloud-based IoT platform.
7. Presentation, joint discussion and evaluation of homework tasks.
The objective of the course is for students to learn the basics of IoT systems and applications by solving practical problems using real IoT devices.

Learning outcomes

Ez a tantárgy a KKK rendeletben meghatározott, következő kompetenciák fejlesztését szolgálja:

Knowledge

No learning outcomes recorded.

Skills

No learning outcomes recorded.

Attitudes

No learning outcomes recorded.

Autonomy and responsibility

No learning outcomes recorded.

Oktatási módszertan

- Lectures. - Classroom computer exercises. - Independent work (homework).

Tanulástámogató anyagok

Online források
Online reading material for presentations (book chapters, articles)

Recommended preliminary knowledge for completing the subject

Knowledge type competencies
(azon előzetes ismeretek összessége, amelyek megléte nem kötelező, de a tantárgy eredményes teljesítését nagyban elősegíti)
Skill type competencies
(azon előzetes képességek és készségek összessége, amelyek megléte nem kötelező, de a tantárgy eredményes teljesítését nagyban elősegíti)
nincs
Recommended (non-compulsory) preliminary competencies
(azon ajánlott (nem kötelező) előzetesen megszerzendő kompetenciák összessége, amelyek jelentősen hozzájárulnak a tantárgy eredményes teljesítéséhez)
General rules
Requirements: During the semester: Writing of 1 summative type midterm exam (ZH) and 1 homework assignment. Successful completion of the ZH and the homework is a prerequisite for signing and passing the exam. During the examination period: Written examination, the mark obtained is determined by the result of the examination paper, the threshold level for a satisfactory mark is 40%. Additional possibilities: The ZH can re-taken up once. The deadline for the submission of homework is during the semester. The homework may be handed in by the deadline set for the make-up period.
Assessment methods
In-term assessments

No detailed assessments provided.

Weight of in-term assessments

No weights provided.

Exam-period assessments

No detailed assessments provided.

Weight of exam elements

No weights provided.

Grade calculation

No grade thresholds provided.

Attendance requirements

No attendance requirements provided.

Rules for retake and resubmission

Not provided.

Short description

Not provided.

Detailed description

Not provided.

Recommended courses
-
Workload to complete the subject

No workload breakdown provided.

Validity of subject requirements
Requirements valid from:
Requirements valid until:
Curriculum placement

No curriculum placements recorded for this subject version.