SavedAdd your journal

Journals / Uludağ Üniversitesi Mühendislik Fakültesi Dergisi / 2026 / Cilt: 28 Sayı: 2

AN IOT BASED APPLICATION ON THE DETECTION OF CAR PARKING AREA BY AN ARTIFICIAL INTELLIGENCE APPROACH

Bir Yapay Zeka Yaklaşımı ile Araba Otopark Alanı Tespiti Üzerine Bir IoT Uygulaması

Oguzhan Karakaya(DOKUZ EYLUL UNIVERSITY)0000-0001-5227-8221
Fikret Mert Gültekin(DOKUZ EYLUL UNIVERSITY)0000-0003-1273-0353
Mert Başkaya(DOKUZ EYLUL UNIVERSITY)0000-0001-6003-6310
Yunus Doğan(DOKUZ EYLÜL ÜNİVERSİTESİ)0000-0002-0353-5014
Pages
465–482
Publication Date
2023-08-31
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Thanks to this system, vehicle owners who want to park their vehicles on the side of the street will be able to learn whether the parking places in a street are available in advance and they will be able to save their time by preferring more available streets.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Nowadays, smart cities solutions have been becoming popular day by day.
📊
Key Findings & Data:As a result, a parking IoT determination system has been implemented in this study with 92% accuracy value.
💡
Conclusion & Impact:Thanks to this system, vehicle owners who want to park their vehicles on the side of the street will be able to learn whether the parking places in a street are available in advance and they will be able to save their time by preferring more available streets.
🔬Design:Araştırma Makalesi
📍Scope:Comprehensive Sample
⚙️Variables:akıllı şehirler · karar destek sistemleri · görüntü işleme

Abstract

Nowadays, smart cities solutions have been becoming popular day by day. The problem of finding a parking place is one of these implementations. Our study appeals to users who want to park their vehicle quickly and who want to find out whether the parking place is available to park before searching for a parking place. This application aims to find a solution to the problem of searching for a place to park. We have found a novel solution to this problem by using image processing methods and utilizing photographs of streetside parking places in the most effective way. In addition, an Android software has been developed through which we can deliver the results obtained with the image processing module to users via a mobile application. As a result, a parking IoT determination system has been implemented in this study with 92% accuracy value. Thanks to this system, vehicle owners who want to park their vehicles on the side of the street will be able to learn whether the parking places in a street are available in advance and they will be able to save their time by preferring more available streets.

Özet

Günümüzde akıllı şehir çözümleri her geçen gün popüler hale gelmektedir. Park yeri bulma sorunu da bu uygulamalardan biridir. Çalışmamız hızlı bir şekilde aracını park etmek isteyen ve park yeri aramadan önce park yerinin müsait olup olmadığını öğrenmek isteyen kullanıcılara hitap etmektedir. Bu uygulama park edecek yer arama sorununa çözüm bulmayı amaçlamaktadır. Görüntü işleme yöntemlerini kullanarak, yol kenarındaki park yerlerinin fotoğraflarından en etkin şekilde yararlanarak bu soruna yeni bir çözüm bulunmuştur. Ayrıca görüntü işleme modülü ile elde edilen sonuçları bir mobil uygulama üzerinden kullanıcılara ulaştırabileceğimiz bir Andorid yazılımı gerçekleştirilmiştir. Sonuç olarak bu çalışmada %92 doğruluk değerine sahip bir otopark IoT belirleme sistemi gerçekleştirilmiştir. Bu sistem sayesinde araçlarını cadde kenarına park etmek isteyen araç sahipleri, bir caddede park yerlerinin müsait olup olmadığını önceden öğrenebilecek ve daha müsait caddeleri tercih ederek zamandan tasarruf edebilecektir.

🔖

Cite This Article

Karakaya, O., Gültekin, F. M., Başkaya, M., Doğan, Y. (2023). AN IOT BASED APPLICATION ON THE DETECTION OF CAR PARKING AREA BY AN ARTIFICIAL INTELLIGENCE APPROACH. Uludağ Üniversitesi Mühendislik Fakültesi Dergisi, Cilt: 28 Sayı: 2, 465–482. https://doi.org/10.17482/uumfd.1247989

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (20)

  1. Aqeel, A. (2018). Introduction to NodeMCU V3, accessed October, 11, 2022. Retrieved from https://www.theengineeringprojects.com/2018/10/introduction-to-nodemcuv3.html.
  2. Balmiki, D., Singhal, M., Singh, A., & Tyagi, D. (2020) A Research on Smart Vehicle Parking System, International Journal of Scientific Research and Management Studies (IJSRMS), 4(7), 124-127. doi:10.55248/gengpi.2022.3.7.15
  3. Boyko, N., Basystiuk, O., & Shakhovska, N. (2018). Performance evaluation and comparison of software for face recognition, based on dlib and opencv library, International Conference on Data Stream Mining & Processing (DSMP), Lviv, 478-482. doi:10.1109/DSMP.2018.8478556
  4. Ch'ng, S. F. (2019). Web-based car parking slot monitoring system (Doctoral dissertation, UTAR), Faculty of Engineering and Green Technology, Universiti Tunku Abdul Rahman, Malaysia.
  5. Crisostomo, C. I. C., Malalis, R. V. C., Saysay, R. S., & Baldovino, R. G. (2019). A Multi-storey Garage Smart Parking System based on Image Processing, International Conference on Robot Intelligence Technology and Applications (RiTA), Daejeon, 52-55. doi:10.1109/RITAPP.2019.8932899
  6. Ghorpade, S. N., Zennaro, M., & Chaudhari, B. S. (2020). GWO model for optimal localization of IoT-enabled sensor nodes in smart parking systems. IEEE Transactions on Intelligent Transportation Systems, 22(2), 1217-1224. doi:10.1109/TITS.2020.2964604
  7. Hanis, H. I. A., & Ramli, S. N. (2021). Attendance Monitoring Application for Students using RFID. Applied Information Technology and Computer Science, 2(2), 73-84. doi:10.30880/aitcs.2021.02.02.005
  8. https://frightanic.com/iot/comparison-of-esp8266- nodemcu-development-boards/, accessed, september 30, 2022
  9. https://github.com/AlexeyAB/darknet/, accessed, september 30, 2022.
  10. https://kotlinlang.org/docs/comparison-to-java.html, accessed, october 30, 2022.
  11. Jo, Y., Choi, J., & Jung, I. (2014). Traffic information acquisition system with ultrasonic sensors in wireless sensor networks. International Journal of Distributed Sensor Networks, 10(5), 961073. doi:10.1155/2014/961073
  12. Kemp, S. (2021, September 24). Digital 2021: the latest insights into the 'state of digital.' WeAreSocialUSA.
  13. Morais, G. A. D., Fujiwara, E., Soares, M. C. P., & Lucimara, G. (2018). Development of an image processing MATLAB algorithm for cell growth analysis. Revista dos Trabalhos de Iniciação Científica da UNICAMP, (26). doi:10.20396/revpibic262018557
  14. Nandyal, S., Sultana, S., & Anjum, S. (2017). Smart car parking system using arduino uno. International Journal of Computer Applications, 169(1), 13-18. doi:10.5120/ijca2017914425
  15. Nisha, S. R., Shyamala, C., Pooja, S., Abarnia, A. P., & Shajeetha, M. S. (2020). RFID based smart car parking system using IoT and cloud. Studia Rosenthaliana (Journal for the Study of Research), 12(5), 60-66.
  16. Rahman, S., & Bhoumik, P. (2019). IoT based smart parking system. International Journal of Advances in Computer and Electronics Engineering, 4(1), 11-16.
  17. Selvaraj, K., & Chakrapani, A. (2017). Smart dustbin monitoring system using LAN Server and Arduino. International Journal of Advances in Computer and Electronics Engineering, 2(4), 20-23.
  18. Siswanto, S., Anif, M., Hayati, D. N., & Yuhefizar, Y. (2019). Pengamanan pintu ruangan menggunakan arduino mega 2560, mq-2, dht-11 berbasis android. Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), 3(1), 66-72. doi:10.29207/resti.v3i1.797
  19. Umesh, P. (2012). Image processing in python. CSI Communications, 23, 2.
  20. Yusnita, R., Norbaya, F., & Basharuddin, N. (2012). Intelligent parking space detection system based on image processing. International Journal of Innovation, Management and Technology, 3(3), 232-235. doi:10.4236/wjet.2014.22006