Real-Time Traffic Study Using Smart Technology
Keywords:
real time, traffic study, smart technology, Agnosticity Framework, Australian cityAbstract
The concomitant spike in traffic creates substantial obstacles to effective traffic management as metropolitan areas experience rapid development. This article details an innovative project in the Australian city of Liverpool that uses smart visual sensors to conduct a real-time traffic study. To monitor various forms of transportation in real-time while protecting the privacy of individuals, these sensors were created as a pilot project and use computer vision and deep neural networks. The study used a complete town center dataset to evaluate the edge-computing device's performance. We present the Agnosticity Framework, an open-standards system that can read and write data from various sensors. Two experimental results show that the framework improves our general understanding and control of urban traffic dynamics. This research provides important insights for future smart city projects and helps create intelligent and privacy-conscious solutions for urban traffic studies.
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References
Tuvikene, Tauri. "Between traffic and walking discourse: Pedestrians in the traffic machine, hints from the Estonian case." The Journal of Transport History (2023): 00225266231179557.
Yannis, George, and Antonis Chaziris. "Transport system and infrastructure." Transportation research procedia 60 (2022): 6-11.
Ouallane, Asma Ait, Assia Bakali, Ayoub Bahnasse, Said Broumi, and Mohamed Talea. "Fusion of engineering insights and emerging trends: Intelligent urban traffic management system." Information Fusion (2022).
Napolitano, Enea Vincenzo. "Intelligent technologies for urban progress: exploring the role of ai and advanced telecommunications in smart city evolution." In European Conference on Advances in Databases and Information Systems, pp. 676-683. Cham: Springer Nature Switzerland, 2023.
Pompigna, Andrea, and Raffaele Mauro. "Smart roads: A state of the art of highways innovations in the Smart Age." Engineering Science and Technology, an International Journal 25 (2022): 100986.
Hanif, Arissa Nalia Binti, Safaa Najah Saud Al-Humairi, and R. Junaidi Daud. "IoT-based: Design an autonomous bus with QR code communication system." In 2021 IEEE International Conference on Automatic Control & Intelligent Systems (I2CACIS), pp. 225-230. IEEE, 2021.
Yue, Wenwei, Changle Li, Guoqiang Mao, Nan Cheng, and Di Zhou. "Evolution of road traffic congestion control: A survey from perspective of sensing, communication, and computation." China Communications 18, no. 12 (2021): 151-177.
Singh, Gurjeet. "Leveraging ChatGPT for Real-Time Decision-Making in Autonomous Systems." Eduzone: International Peer Reviewed/Refereed Multidisciplinary Journal 12, no. 2 (2023): 101-106.
Ali, Akbar, Nasir Ayub, Muhammad Shiraz, Niamat Ullah, Abdullah Gani, and Muhammad Ahsan Qureshi. "Traffic efficiency models for urban traffic management using mobile crowd sensing: A survey." Sustainability 13, no. 23 (2021): 13068.
Tomar, Ishu, Indu Sreedevi, and Neeta Pandey. "State-of-Art review of traffic light synchronization for intelligent vehicles: current status, challenges, and emerging trends." Electronics 11, no. 3 (2022): 465.
Wan, Xiangpeng, Michael C. Lucic, Hakim Ghazzai, and Yehia Massoud. "Empowering real-time traffic reporting systems with nlp-processed social media data." IEEE Open Journal of Intelligent Transportation Systems 1 (2020): 159-175.
WOLNIAK, Radosław, and Wies GREBSKI. "THE USAGE OF SMARTPHONE APPLICATIONS IN SMART CITY DEVELOPMENT–URBAN MOBILITY AND TRAFFIC MANAGEMENT." Scientific Papers of Silesian University of Technology. Organization & Management/Zeszyty Naukowe Politechniki Slaskiej. Seria Organizacji i Zarzadzanie 179 (2023).
Porru, Simone, Francesco Edoardo Misso, Filippo Eros Pani, and Cino Repetto. "Smart mobility and public transport: Opportunities and challenges in rural and urban areas." Journal of traffic and transportation engineering (English edition) 7, no. 1 (2020): 88-97.
Paiva, Sara, Mohd Abdul Ahad, Gautami Tripathi, Noushaba Feroz, and Gabriella Casalino. "Enabling technologies for urban smart mobility: Recent trends, opportunities and challenges." Sensors 21, no. 6 (2021): 2143.
Martins, Sofia, António Costa, Zafeiris Kokkinogenis, and Rosaldo JF Rossetti. "Enabling citizen-centric ITS services through blockchain and human incentives." In International Conference on Intelligent Transport Systems, pp. 85-94. Cham: Springer International Publishing, 2021.
Mohmmad, Sallauddin, Mohammed Ali Shaik, K. Mahender, Ranganath Kanakam, and Bonthala Prabhanjan Yadav. "Average Response Time (ART): Real-Time Traffic Management in VFC Enabled Smart Cities." In IOP Conference Series: Materials Science and Engineering, vol. 981, no. 2, p. 022054. IOP Publishing, 2020.
Atta, Ayesha, Sagheer Abbas, M. Adnan Khan, Gulzar Ahmed, and Umer Farooq. "An adaptive approach: Smart traffic congestion control system." Journal of King Saud University-Computer and Information Sciences 32, no. 9 (2020): 1012-1019.
Ma, Jing, Yinhua Tao, Mei-Po Kwan, and Yanwei Chai. "Assessing mobility-based real-time air pollution exposure in space and time using smart sensors and GPS trajectories in Beijing." In Smart Spaces and Places, pp. 102-116. Routledge, 2021.
Shengdong, Mu, Xiong Zhengxian, and Tian Yixiang. "Intelligent traffic control system based on cloud computing and big data mining." IEEE Transactions on Industrial Informatics 15, no. 12 (2019): 6583-6592.
Babar, Muhammad, and Fahim Arif. "Real-time data processing scheme using big data analytics in internet of things based smart transportation environment." Journal of Ambient Intelligence and Humanized Computing 10 (2019): 4167-4177.
Yang, Jiachen, Yurong Han, Yafang Wang, Bin Jiang, Zhihan Lv, and Houbing Song. "Optimization of real-time traffic network assignment based on IoT data using DBN and clustering model in smart city." Future Generation Computer Systems 108 (2020): 976-986.
Yu, James Jian Qiao, and Jiatao Gu. "Real-time traffic speed estimation with graph convolutional generative autoencoder." IEEE Transactions on Intelligent Transportation Systems 20, no. 10 (2019): 3940-3951.
Yu, Keping, Long Lin, Mamoun Alazab, Liang Tan, and Bo Gu. "Deep learning-based traffic safety solution for a mixture of autonomous and manual vehicles in a 5G-enabled intelligent transportation system." IEEE transactions on intelligent transportation systems 22, no. 7 (2020): 4337-4347.
Chen, Yi-Ting, Edward W. Sun, Ming-Feng Chang, and Yi-Bing Lin. "Pragmatic real-time logistics management with traffic IoT infrastructure: Big data predictive analytics of freight travel time for Logistics 4.0." International Journal of Production Economics 238 (2021): 108157.
Sarrab, Mohammed, Supriya Pulparambil, Naoufel Kraiem, and Mohammed Al-Badawi. "Real-time traffic monitoring systems based on magnetic sensor integration." In Smart City and Informatization: 7th International Conference, iSCI 2019, Guangzhou, China, November 12–15, 2019, Proceedings 7, pp. 447-460. Springer Singapore, 2019.
Ruz-Nieto, Andres, Esteban Egea-Lopez, Jose-Marıa Molina-Garcıa-Pardo, and Jose Santa. "A 3D simulation framework with ray-tracing propagation for LoRaWAN communication." Internet of Things 24 (2023): 100964.
Kim, J. L. "Smart Mountain: A Solution Based on a Low-Cost Embedded System to Detect Urban Traffic in Natural Parks." (2023): 132.
Wang, Li, Xinyu Zhang, Wenyuan Qin, Xiaoyu Li, Jinghan Gao, Lei Yang, Zhiwei Li et al. "Camo-mot: Combined appearance-motion optimization for 3d multi-object tracking with camera-lidar fusion." IEEE Transactions on Intelligent Transportation Systems (2023).
Meimetis, Dimitrios, Ioannis Daramouskas, Isidoros Perikos, and Ioannis Hatzilygeroudis. "Real-time multiple object tracking using deep learning methods." Neural Computing and Applications 35, no. 1 (2023): 89-118.
Qin, Zheng, Sanping Zhou, Le Wang, Jinghai Duan, Gang Hua, and Wei Tang. "MotionTrack: Learning Robust Short-term and Long-term Motions for Multi-Object Tracking." In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 17939-17948. 2023.
Tsampoulatidis, Ioannis, Nicos Komninos, Evangelos Syrmos, and Dimitrios Bechtsis. "Universality and Interoperability across Smart City Ecosystems." In International Conference on Human-Computer Interaction, pp. 218-230. Cham: Springer International Publishing, 2022.
Mishra, Ayaskanta, Anita Swain, Arun Kumar Ray, and Raed M. Shubair. "HetNet/M2M/D2D communication in 5G technologies." In 5G IoT and Edge Computing for Smart Healthcare, pp. 45-87. Academic Press, 2022.
Antonios, Pliatsios, Kotis Konstantinos, and Goumopoulos Christos. "A systematic review on semantic interoperability in the IoE-enabled smart cities." Internet of Things (2023): 100754.
https://www.kaggle.com/datasets/almightyj/oxford-town-centre
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