Smart City Services and Applications
A tantárgyleírás hatályossága
| Subject name (Hungarian, English) |
Okosváros szolgáltatások és alkalmazások
Smart City Services and Applications
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| Subject code | BMEVITMMA16 | ||||||||||||
| Subject type | — | ||||||||||||
| Training Level | — | ||||||||||||
| Course types and hours (weekly/semester) |
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| Assessment type | vizsga | ||||||||||||
| Credits | 5 | ||||||||||||
| Subject coordinator |
DR. Vida Rolland
position: egyetemi docens
contact:
vida.rolland@vik.bme.hu
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| Responsible department |
Távközlési és Mesterséges Intelligencia Tanszék
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| Faculty | Villamosmérnöki és Informatikai Kar | ||||||||||||
| Subject website | https://www.tmit.bme.hu/vitmma16 | ||||||||||||
| 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
Detailed topics of the lectures:,
1. Smart city goals, strategies, master plans. Island-like systems v. smart city services and applications that build on each other and are in synergy with each other.
2. Operational models of urban sensor networks. Event, time and query based control. Data aggregation within a network. Mobility in sensor networks, base station vs. sensor mobility, virtual mobility,
3. Localization and tracking in urban sensor networks, location-aware operation. Modeling of sensor networks, simulation tools (tossim). Test networks (IoT-LAB). Standardization issues.,
4. Intelligent transport systems in smart cities. Efficient public transport. Ride sharing solutions, incentive mechanisms, HOV lanes. Matchmaking optimization between drivers and passengers.,
5. Car sharing services. Station-based vs. free floating, centralized vs. peer-to-peer car sharing. Fleet sizing issues.,
6. Smart parking systems, indoors and outdoors. Adaptive pricing solutions. International case studies.
7. Electric vehicles in smart cities. Construction and optimization of a charging network. Vehicle-to-Grid.
8. Smart grid, smart metering. Two-way electricity supply, integration of renewable energy sources, service models.
9. Smart buildings, smart homes. Water management and waste management in smart cities.
10. Environmental protection in smart cities. Reducing the carbon footprint of cities. Monitoring the formation of heat islands, air pollution issues.
11. Smart city management. Encourage community participation. Crowdsourcing and crowdsensing applications. Crowdfunding.
12. Security of smart cities. Security of sensor networks and IoT systems. Secure data transfer. Vehicle communication security, car hacking. Protection of critical infrastructure, cyber attacks. Data publicity issues, Open Data. Protection of the private sphere, anonymity, privacy.
13. Case studies, smart cities around the world. Singapore, Vienna/Aspern, Songdo, London, Barcelona, Santander, Toyota Woven City, Masdar, Dubai Expo City, Neom/The Line.
The detailed topics of the practical works:
1. Detailed description, discussion and assignment of semester homework. Detailed description of selectable devices and platforms
2. Map and map data management in services. Using maps in applications. Presentation of some available services, access to services: route planning, timetables.
3. Investigating parking space occupancy in a smart city. Sensor and camera solutions. Low-power, long-distance radio connections.
4. Homework intermediate control point: presentation and joint discussion of system plans, technological solution details
5. Analysis of smart city street traffic camera images using deep learning methods. Training a classification neural network for cars and pedestrians.
6. Object detection with deep learning methods. Use of object detection in smart city traffic.
7. Presentation, joint discussion and evaluation of homework.
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
Tanulástámogató anyagok
Online források
Recommended preliminary knowledge for completing the subject
General rules
Assessment methods
In-term assessments
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Weight of in-term assessments
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Exam-period assessments
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Grade calculation
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Attendance requirements
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Rules for retake and resubmission
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Short description
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Detailed description
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Recommended courses
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Workload to complete the subject
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