Monitorowanie ruchu ulicznego z wykorzystaniem chmury obliczeniowej i techniki RFID

pol Article in Polish DOI: 10.14313/PAR_239/19

Bartosz Pawłowicz , send Mateusz Salach , Bartosz Trybus , Konrad Żak Politechnika Rzeszowska, Wydział Elektrotechniki i Informatyki

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Streszczenie

W artykule przedstawiono architekturę i implementację systemu monitorowania ruchu ulicznego. Zastosowano w nim identyfikatory RFID do rozpoznawania pojazdów, w tym specjalnego znaczenia, jak karetki pogotowia, autobusy miejskie, pojazdy z obniżoną emisją spalin. Dane o ruchu są przesyłane do usługi IoT Hub w chmurze obliczeniowej Azure. Na ich podstawie dokonywana jest analiza sytuacji drogowych i podejmowane decyzje dotyczące sterowania ruchem ulicznym. Informacje sterujące są zwrotnie kierowane do urządzeń sterujących ruchem za pomocą świateł ulicznych, barier, tablic informacyjnych. W artykule opisano sposób komunikacji z chmurą obliczeniową oraz możliwości realizacji algorytmów monitorowania i sterowania ruchem za pomocą IoT Hub.

Słowa kluczowe

chmura obliczeniowa, identyfikacja pojazdów, rfid, smart city

Traffic Monitoring Using Cloud Computing and RFID Technology

Abstract

The article presents the architecture and implementation of a street traffic monitoring system. It uses RFID identifiers to recognize vehicles, including special meaning, such as ambulances, city buses, vehicles with reduced exhaust gas emissions. Traffic data is sent to the IoT Hub service in the Azure cloud. On their basis, road situations are analyzed and decisions are made regarding traffic control. Control information is fed back to traffic control devices by means of street lights, barriers, information boards. The article describes the method of communication with the computing cloud and the possibilities of implementing traffic monitoring and control algorithms using IoT Hub.

Keywords

cloud computing, rfid, smart city, vehicle identification

Bibliography

  1. Goudar R.H., Megha H.N., Next generation intelligent traffic management system and analysis for smart cities, 2017 International Conference on Smart Technologies for Smart Nation (SmartTechCon), Bangalore, 2017, 999–1003, DOI: 10.1109/SmartTechCon.2017.8358521.
  2. Ksiksi A., Al Shehhi S., Ramzan R., Intelligent Traffic Alert System for Smart Cities, 2015 IEEE International Conference on Smart City/SocialCom/SustainCom (SmartCity), Chengdu, 2015, 165–169, DOI: 10.1109/SmartCity.2015.65.
  3. Sundar R., Hebbar S., Golla V., Implementing Intelligent Traffic Control System for Congestion Control, Ambulance Clearance, and Stolen Vehicle Detection, “IEEE Sensors Journal”, Vol. 15, No. 2, 2015, 1109–1113, DOI: 10.1109/JSEN.2014.2360288.
  4. Ukkonen L., Sydanheimo L., Kivikoski M., Read Range Performance Comparison of Compact Reader Antennas for a Handheld UHF RFID Reader, “IEEE Communications Magazine”, Vol. 45, No. 4, 2007, 24–31, DOI: 10.1109/MCOM.2007.348674.
  5. Jankowski-Mihułowicz P., Węglarski M., Definition, Characteristics and Determining Parameters of Antennas in Terms of Synthesizing the Interrogation Zone in RFID Systems, Radio Frequency Identification, Crepaldi P.C., Pimenta T.C. (Ed.), Chapter 5, 65–119, INTECH, 29 November 2017, DOI: 10.5772/intechopen.71378.
  6. Jankowski-Mihułowicz P., Węglarski M., Factors affecting the synthesis of autonomous sensors with RFID interface, “Sensors”, Vol. 19, No. 20, 4392, 2019, DOI: 10.3390/s19204392.
  7. ISO/IEC 14443-3:2016, Identification cards – Contactless integrated circuit cards – Proximity cards.
  8. ISO/IEC 15693, Identification cards – Contactless integrated circuit cards – Vicinity cards.
  9. ISO/IEC 18000-6:2013 Information technology – Radio frequency identification for item management – Part 6: Parameters for air interface communications at 860 MHz to 960 MHz General.
  10. Pawłowicz B., Trybus B., Salach M., Jankowski-Mihułowicz P., Dynamic RFID Identification in Urban Traffic Management Systems. “Sensors”, Vol. 20, No. 15, 2020, DOI: 10.3390/s20154225.
  11. Prinsloo J., Malekian R., Accurate Vehicle Location System Using RFID, an Internet of Things Approach. “Sensors”, Vol. 16, No. 6, 2016, DOI: 10.3390/s16060825.
  12. Wang J., Ni D., Li K., RFID-Based Vehicle Positioning and Its Applications in Connected Vehicles. “Sensors”. Vol. 14, No. 3, 2014, 4225–4238, DOI: 10.3390/s140304225.
  13. Mandal V., Mussah A.R., Jin P., Adu-Gyamfi Y., Artificial Intelligence-Enabled Traffic Monitoring System. “Sustainability”, Vol. 12, No. 21, 2020; DOI: 10.3390/su12219177.
  14. Zhao S., Wang C., Wei P., Zhao Q., Research on the Deep Recognition of Urban Road Vehicle Flow Based on Deep Learning. “Sustainability”, Vol. 12, No. 7.
  15. Pillai U.K.K., Valles D., Vehicle Type and Color Classification and Detection for Amber and Silver Alert Emergencies Using Machine Learning, 2020 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS), 1–5, Vancouver, BC, Canada, 2020, DOI: 10.1109/IEMTRONICS51293.2020.9216368.
  16. Razavi M., Hamidkhani M., Sadeghi R., Smart Traffic Light Scheduling in Smart City Using Image and Video Processing, 2019 3rd International Conference on Internet of Things and Applications (IoT), Isfahan, Iran, 2019, 1–4, DOI: 10.1109/IICITA.2019.8808836.
  17. Bagula A., Castelli L., Zennaro M., On the Design of Smart Parking Networks in the Smart Cities: An Optimal Sensor Placement Model. “Sensors”, Vol. 15, No. 7, 2015, 15443–15467, DOI: 10.3390/s150715443.
  18. Elmrini A., Amrani A.G., Wireless Sensors Network for Traffic Surveillance and Management in Smart Cities, 2018 IEEE 5th International Congress on Information Science and Technology (CiSt), Marrakech, 2018, 562–566, DOI: 10.1109/CIST.2018.8596636.
  19. Naik D.R., Das L.B., Bindiya T.S., Wireless Sensor networks with Zigbee and WiFi for Environment Monitoring, Traffic Management and Vehicle Monitoring in Smart Cities, 2018 IEEE 3rd International Conference on Computing, Communication and Security (ICCCS), Kathmandu, 2018, 46–50, DOI: 10.1109/CCCS.2018.8586819.
  20. Kazi S., Nuzhat S., Nashrah A., Rameeza Q., Smart Parking System to Reduce Traffic Congestion, 2018 International Conference on Smart City and Emerging Technology (ICSCET), Mumbai, 2018, 1–4, DOI: 10.1109/ICSCET.2018.8537367.
  21. Melnyk P., Djahel S., Nait-Abdesselam F., Towards a Smart Parking Management System for Smart Cities, 2019 IEEE International Smart Cities Conference (ISC2), Casablanca, Morocco, 2019, 542–546, DOI: 10.1109/ISC246665.2019.9071740.
  22. García Oya J.R., Martín Clemente R., Hidalgo Fort E., González Carvajal R., Muñoz Chavero F., Passive RFID Based Inventory of Traffic Signs on Roads and Urban Environments. “Sensors”, Vol. 18, No. 7, 2018, DOI: 10.3390/s18072385.