A Review Paper on Traffic Sign Detection and Manage Speed Limit
Author(s):
Manish Kumar Bharti, Dr. Amit Chandak
Keywords:
Deep learning, IOT, TSR (traffic sign recognition), machine learning, and artificial intelligence for traffic sign identification
Abstract
Nowadays, road accident problems are growing, which can reduce road traffic problems by solving proper vehicle speed monitoring systems. Deep learning and machine learning work propagate and complex calculation use in traffic signs detection are essential part of the road system and are used to convey information, regulate traffic, and provide guidance to drivers, pedestrians, and other road users. Accidents are associated without any sign and breakers and navigation. These signs use standardized symbols, colors, and shapes to ensure that their meaning is easily understood regardless of the language spoken; however, the TSR systems in vehicles can identify speed limits, stops, and signs. Artificial intelligent and machine learning already works on it. For each region where the rules must be observed, different sections are mentioned. Prepare the collected data by applying preprocessing techniques such as resizing, normalization, and augmentation. Preprocessing helps to enhance the quality and consistency of the data and improves the performance of the machine learning models. Choose a suitable camera to capture real-time video or images of the road. Many modern vehicles come equipped with built-in cameras for driver assistance systems, but if you are building a custom setup, you can use a USB camera or a camera module compatible with your platform. The IOT platform is used to attach a Wi-Fi and Bluetooth connection to the system to recognize the traffic speed control of the system .the objective of some improvement features is to detect the traffic sign speed limit change on board to regulate the pace
Article Details
Unique Paper ID: 161239

Publication Volume & Issue: Volume 10, Issue 3

Page(s): 43 - 48
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