Smart Traffic Light Scheduling in Smart City Using Image and Video Processing

Razavi, Meisam; Hamidkhani, Mehdi; Sadeghi, Rasool

doi:10.1109/iicita.2019.8808836

Cited by 21 publications

(5 citation statements)

References 8 publications

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“…As a result, IoT technology has been used in process-related studies in many sectors, with fewer resources and the need to make processes more efficient. Examples of these sectors can be given as aviation [22][23][24][25][26][27], agriculture [28][29][30], public [31][32][33][34], waste management [35], transport [36], health [37][38][39][40][41][42], education [43], military [44], energy [45], financial [46], examples of intelligent systems [47][48][49][50][51][52].…”

Section: Related Workmentioning

confidence: 99%

Internet of Things Supported Airport Boarding System and Evaluation with Fuzzy

Memika¹,

Polat²

2023

Intelligent Automation &Amp; Soft Computing

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The existing systems sustained with the investments made require more automation and digital transformation with the continuous advancement of technology. The aviation industry is a sector that is open to more automation and digital transformation, mainly because of the intense competition and the analysis of a large variety of data. The long duration of operations in current airline processes and some process flows cause customer dissatisfaction and cost increase. In this study, the boarding process, which is one of the operational processes of airline transportation and is open to improvement, was discussed. The classical boarding process has been redesigned using Internet of Things technology a model called Boarding 4.0 was created. With Boarding 4.0, it is aimed to design a process where passengers can take their time before boarding more efficiently. In the study, the sub-processes of the Boarding 4.0 model, other processes that the sub-processes interact with, their activities, and data exchange passenger movements during the activities are explained in detail. Compared to the classical boarding process and Boarding 4.0 with the fuzzy ahp technique, it has been shown that boarding 4.0 is more advantageous and passenger movement times can be reduced during boarding. As a result of the evaluation made with the fuzzy ahp, it was determined that boarding 4.0 is more advantageous than the classical boarding process. In addition, when the total time of the sub-activities in the boarding process is calculated, boarding activities for a passenger take 50 min with the classic boarding process and 20 min with Boarding 4.0. Thus, when Boarding 4.0 is used, the passenger gains 30 min. Furthermore, when the calculation is made concerning the airport's current capacity, two passengers are hosted with the classical boarding process, while five passengers are hosted with Boarding 4.0. This acquisition is significant for airports in terms of efficient use of resources.

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Section: Related Workmentioning

confidence: 99%

Internet of Things Supported Airport Boarding System and Evaluation with Fuzzy

Memika¹,

Polat²

2023

Intelligent Automation &Amp; Soft Computing

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“…Users can access the services using the proposed mobile application connected to the Internet, as these services are integrated with the public map service. Related to this is the proposal of Razavi et al [50] where a new method for the management of traffic lights using a combination of IoT and image and video processing techniques is presented. In the proposed models, the scheduling of traffic lights is determined by the intensity and the number of vehicles going by.…”

Section: Air Pollution and Traffic Flow Monitoring Systems In The Sma...mentioning

confidence: 99%

IoT based monitoring of air quality and traffic using regression analysis

Martín-Baos

Rodríguez-Benítez

García-Ródenas

et al. 2022

Applied Soft Computing

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“…The developing populace and expanded [10] vehicles lead to the fundamental difficulties in metropolitan life. In this way, the job of traffic the executives will save time and fuel utilization and lessen ecological contamination.…”

Section: Literature Surveymentioning

confidence: 99%

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2022

International Journal of Innovative Research in Electrical, Ele

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Traffic the executives' framework is considered as one of the significant components of a shrewd city. With the fast development of populace and metropolitan portability in metropolitan urban areas, gridlock is frequently seen on streets. To handle different issues for overseeing traffic on streets and to help experts in legitimate preparation, a shrewd traffic the board framework utilizing the Internet of Things (IoT) is proposed in this paper. A crossover approach (blend of incorporated and decentralized) is utilized to improve traffic stream on streets and a calculation is conceived to oversee different traffic circumstances productively. For this reason, the framework accepts traffic thickness as contribution from a) cameras b) and sensors, then, at that point, oversees traffic lights. One more calculation in light of Artificial Intelligence is utilized to anticipate the traffic thickness for future to limit the gridlock. Other than this, Radio Frequency Identifications (RFID) are likewise used to focus on the crisis vehicles, for example, ambulances and fire detachment vehicles during a gridlock. If there should be an occurrence of fire out and about, Smoke sensors are likewise essential for this framework to recognize the present circumstance. To exhibit the viability of the proposed traffic the board framework, a model is created which streamlines the progression of traffic as well as associates close by salvage divisions with an incorporated server. In addition, it additionally extricates valuable data introduced in graphical organizations that might help the experts in future street arranging.

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Smart Traffic Light Scheduling in Smart City Using Image and Video Processing

Cited by 21 publications

References 8 publications

Internet of Things Supported Airport Boarding System and Evaluation with Fuzzy

Internet of Things Supported Airport Boarding System and Evaluation with Fuzzy

IoT based monitoring of air quality and traffic using regression analysis

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