IoT Enabled Clustering of Traffic Data - A Review
D. Kaladevi, Neha Samreen, Adarsh K.V, K. V. Praveen, J Nagaraja
Abstract
D. Kaladevi, Neha Samreen, Adarsh K.V, K. V. Praveen, J Nagaraja
Abstract
The administration of the traffic control system is a great concern in the metropolitan cities. The traffic control system has become much busier in recent years, traffic congestion is one of the reasons for these key challenges in smart cities. Traditional traffic management systems are not suitable for solving the problem, the mechanism of the congestion control mechanism is needed. This is how there is an intelligent control system. This research document proposes an intelligent system of traffic control based on IOT. This improves the high degree of scalability, replacing the previous traffic signage system with traffic signal control data in real time. To solve these safety protocol concerns, we implement IOT systems based on privacy with intelligence, which analyze the traffic data in real time for the control of traffic signals. We approach the man's data security attack in the center (MITM). And here, the algorithm of the support vector machine (SVM) will be used here for the classification of data on the edge and will be implemented by RASPBERRY PI3 and Scikit to implement the collection of raw traffic data. The sensors are used to distinguish positive or bad data from. The traffic data pattern of the terminal devices based on IOT. The edge router and the fog router will also be used to store traffic information in the cloud and to decide the level of traffic.
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The administration of the traffic control system is a great concern in the metropolitan cities. The traffic control system has become much busier in recent years, traffic congestion is one of the reasons for these key challenges in smart cities. Traditional traffic management systems are not suitable for solving the problem, the mechanism of the congestion control mechanism is needed. This is how there is an intelligent control system. This research document proposes an intelligent system of traffic control based on IOT. This improves the high degree of scalability, replacing the previous traffic signage system with traffic signal control data in real time. To solve these safety protocol concerns, we implement IOT systems based on privacy with intelligence, which analyze the traffic data in real time for the control of traffic signals. We approach the man's data security attack in the center (MITM). And here, the algorithm of the support vector machine (SVM) will be used here for the classification of data on the edge and will be implemented by RASPBERRY PI3 and Scikit to implement the collection of raw traffic data. The sensors are used to distinguish positive or bad data from. The traffic data pattern of the terminal devices based on IOT. The edge router and the fog router will also be used to store traffic information in the cloud and to decide the level of traffic.
Key concepts: Computer science, Computer network, Floating car data, Enhanced Data Rates for GSM Evolution, Cluster analysis, Network traffic control, Scalability, Traffic generation model