Analyzing the Impact of Over Speeding of the Vehicles in the Society

Abstract

Over-speeding is a leading cause of business accidents, performing in significant losses and severe injuries worldwide. According to WHO, speed is a contributing factor in roughly 30 of road deaths in high- income countries and nearly 50 in low- and middle- income countries. Controlling vehicle speed is pivotal to precluding crashes and minimizing the inflexibility of injuries. Traditional styles of speed control and business law enforcement are frequently shy in effectively managing and reducing over-speeding incidents. To address this issue, recent studies have explored colorful technological results, similar as the Automatic E-Challan System, IOT- grounded business violation systems, and RF- grounded vehicle discovery. These systems use advanced technologies like detector networks, image processing, and radio frequence to cover business, descry violations, and issue penalties automatically. These approaches aim to enhance enforcement effectiveness, ameliorate business operation, and reduce road accidents. Our exploration focuses on integrating an automated speed discovery system that not only cautions motorists when they exceed speed limits but also contributes to reducing road accidents by administering compliance with business regulations. This result is anticipated to ameliorate road safety by precluding over-speeding and icing timely interventions.

Introduction

I. INTRODUCTION

In contemporary society, road safety remains a pressing concern globally, with over-speeding emerging as a significant contributor to road accidents, injuries, and fatalities.

Despite stringent speed limit regulations, enforcement of these limits poses substantial challenges for law enforcement agencies worldwide. Manual methods of speed monitoring and enforcement are often labor-intensive, resource-intensive, and prone to errors, limiting their effectiveness in curbing over- speeding violations.

To address these challenges, there is a growing imperative to develop innovative and automated systems capable of efficiently monitoring vehicle speeds, detecting instances of over-speeding in real-time, and issuing electronic challans (E-Challans) automatically to violators. Such systems leverage cutting-edge technologies, particularly the Internet of Things (IoT), to integrate sensor networks, data analytics algorithms, and communication infrastructures for seamless speed limit surveillance and enforcement.

The proposed system, " Sensor-Based Vehicle Speed Limit Surveillance and Smart E-Challan System for Over-Speeding Using IoT," represents a pioneering endeavor to revolutionize speed limit enforcement by harnessing the power of IoT technologies. By deploying sensors along roadways, collecting real-time speed data, and processing it intelligently, the system aims to enhance road safety, improve compliance with speed regulations, and reduce the incidence of accidents caused by over-speeding.

II. LITERATURE REVIEW

1. R. Mishra, et al, "Analysing traffic violations through E-challan system in metropolitan cities (workshop paper)," 2020 IEEE Sixth International Conference on Multimedia Big Data (BigMM). This paper presents an analysis of traffic violations using the e-challan system in metropolitan areas. The e-challan system is a digital platform to issue electronic challans (tickets) for traffic violations. The study focuses on how this system helps in managing traffic rules and enhancing enforcement efficiency. The paper discusses the system's integration with other technologies and its impact on reducing traffic violations.
2. S. Asoba, et al., "Advanced traffic violation control and penalty system using IoT and image processing techniques," 2020 2nd International Conference on Innovative Mechanisms for Industry Applications (ICIMIA). This paper introduces an advanced system for controlling traffic violations using the Internet of Things (IoT) and image processing technologies. The system leverages IoT devices to monitor traffic and image processing algorithms to detect violations, such as speeding or running red lights. The integration of these technologies aims to improve the accuracy of violation detection and automate the penalty process.
3. N. Kassem, A. E. Kosba, and M. Youssef, "RF-based vehicle detection and speed estimation," 2012 IEEE 75th Vehicular Technology Conference (VTC Spring). The paper explores a method for vehicle detection and speed estimation using radio frequency (RF) technology. The approach involves deploying RF sensors to detect vehicles and estimate their speed based on the signals reflected by moving vehicles. This method provides a non-intrusive way to monitor traffic flow and can be used to enhance traffic management systems.
4. S. M. Malik, et al., "Automated over speeding detection and reporting system," 2014 16th International Power Electronics and Motion Control Conference and Exposition. This research presents an automated system designed to detect and report instances of speeding. The system uses sensors and data processing algorithms to identify vehicles that exceed speed limits and automatically generate reports. The paper discusses the system's architecture, the technologies used, and its potential impact on improving road safety.
5. M. Z. Hussain, et al., "E-Challan System Implemented in Lahore Using Digital Image Processing," 2021 International Conference on Innovative Computing (ICIC). This paper details the implementation of an e-challan system in Lahore, utilizing digital image processing techniques. The system captures images of traffic violations and processes them to issue electronic tickets. The paper evaluates the effectiveness of this system in enhancing traffic law enforcement and discusses challenges and benefits observed during implementation
6. D. Vinay, et al., "Automatic E-Challan Generation if Vehicle is Not Insured," 2023 6th International Conference on Contemporary Computing and Informatics (IC3I). The paper proposes a system for automatically generating e-challans for vehicles that lack insurance. This system integrates vehicle registration data with insurance records to identify uninsured vehicles and issue penalties. The approach aims to ensure compliance with insurance regulations and improve overall road safety.
7. S. Rohan, S. Siddharth, and B. Bairwa, "Smart Traffic Fines Management System Using GSM Module," 2023 IEEE Renewable Energy and Sustainable E-Mobility Conference (RESEM). This paper introduces a smart traffic fines management system that uses GSM (Global System for Mobile Communications) technology. The system sends notifications and updates related to traffic fines via SMS. It aims to streamline the fine management process and enhance communication between traffic authorities and vehicle owners
8. A. Kavitha, et al., "Smart Traffic Violation Detection System Using Artificial Intelligence," 2023 3rd International Conference on Pervasive Computing and Social Networking (ICPCSN). The paper presents a traffic violation detection system that leverages artificial intelligence (AI). AI algorithms analyze traffic data and images to detect violations such as speeding or running red lights. The system aims to improve detection accuracy and reduce human intervention in traffic monitoring and enforcement

III. RESEARCH GAP

1. Inconsistent Speed Monitoring: Manual speed checks by traffic police were often inconsistent due to the limitations of human observation, leading to missed violations or inaccurate speed assessments.
2. High Human Resource Requirement: A significant amount of manpower was required to monitor traffic, stop vehicles, check for overspeeding, and issue fines. This was labor-intensive and inefficient.
3. Subjectivity and Human Error: Human involvement in detecting violations often leads to subjective decisions and errors, such as incorrect identification of violating vehicles or wrong speed estimations.
4. Delayed Response to Violations: In a manual system, there was often a delay between the detection of a violation and the issuance of a fine, reducing the effectiveness of enforcement and allowing violators to escape penalties.
5. Limited Coverage and Scalability: Manual enforcement was limited by the physical presence of traffic police, making it difficult to monitor large areas or multiple locations simultaneously.
6. Challenges in Record-Keeping and Data Management: Maintaining accurate records of violations, vehicle details, and issued fines was challenging in a manual system, often leading to errors and difficulties in enforcement.
7. Corruption and Bribery Risks: Manual traffic enforcement was susceptible to corruption and bribery, where violators could sometimes negotiate or bribe their way out of receiving a fine.

IV. PROBLEM STATEMENT

Over-speeding has been linked as a major cause of business accidents. Accidents due to speeding result in crashes, hazardous injuries, and death. WHO statistics showed that in high- profit nations, celerity contributes to around 30% of deaths on the road, while in some low- profit and middle ground- profit nations, celerity is estimated to be the main contributory procurator in around half of all road crashes.

Controlling instruments' celerity can support crash circumstance and reduce the jolt when they do, lessening the harshness of injuries sustained by the fatalities. Multitudinous accidents also occur due to the lack of control of the celerity of instruments without any alert when the agent gets over celerity. As The celerity of an overspeeding agent ca n't be maintained and ca n't be advised for the automobilist this work can be done by an spontaneous celerity detection engine which can advise the automobilist whenever they overspeed.

V. OBJECTIVES

1. Identification over speed via no. Plate: Accurately identifying and verifying the details of a specific vehicle, typically including its make, model, registration number, and owner information.
2. Automation & reduction of human intervention: The project's foremost objective is to contribute to automatically detecting instances of vehicle over-speeding and alerting drivers in real-time. By doing so, it aims to reduce human intervention and reduce workload
3. Promoting Responsible Driving: The project seeks to promote responsible driving behavior by making drivers aware of their vehicle's speed relative to posted speed limits. This awareness is intended to encourage drivers to adhere to speed regulations and exercise caution.
4. Real-Time Monitoring & Data Collection: The project aims to provide real-time monitoring & collecting data on vehicle speeds, enabling immediate detection and response to over-speeding incidents. This real-time aspect is crucial for swift interventions and accident prevention.
5. Speed Reduction & Automated e-challan generation: This could streamline the enforcement process, saving time and resources for authority.

VI. METHODOLOGY

1. Speed dimension The system measures the current speed of the vehicle using detectors.
2. Speed Limit via GPS & Sensor The speed limit and position information are handed via GPS and detectors.
3. Check for Overspeeding The system compares the measured speed with the speed limit.However, it moves to the coming step, If the vehicle exceeds the speed limit.
4. Detects Violation The system detects if a speed violation has passed grounded on the overspeeding check.
5. Warning System A warning is issued to the motorist, potentially in the form of a 30-alternate beep, indicating the violation.
6. Prize License Plate The system identifies the vehicle by rooting the license plate information.
7. Check Database for Details The system checks the police database for details about the vehicle.
8. Violation Record Creation A record of the violation is created, including details similar as the date, time, position, vehicle information, and type of violation.
9. E-Challan Generation Ane-challan( electronic ticket) is generated for the violation.
10. Announcement to Violator The registered proprietor of the vehicle is notified of the violation via dispatch or SMS, with details of thee-challan
11. Warning System A warning is issued to the motorist, potentially in the form of a 30-alternate beep, indicating the violation.
12. Prize License Plate The system identifies the vehicle by rooting the license plate information.
13. Check Database for Details The system checks the police database for details about the vehicle and its proprietor.
14. Violation Record Creation A record of the violation is created, including details similar as the date, time, position, vehicle information, and type of violation.
15. E-Challan Generation Ane-challan( electronic ticket) is generated for the violation.
16. Announcement to Violator The registered proprietor of the vehicle is notified of the violation via dispatch or SMS, with details of thee-challan.

Fig1. Flow diagram of overspeed detection & challan generation

Fig1. Architecture diagram of challan portal

VII. FUTURE SCOPE

1. No mortal Intervention Helps in landing the speed of vehicles without any mortal involvement.
2. Business jack. This design can also be used as a business jack; it's a device that records detailed information about business conditions over some time. Traffic lumberjacks generally collect data similar to vehicle counts, vehicle pets, vehicle groups( e.g., buses , exchanges, motorcycles), and business inflow patterns.)
3. It's a device specifically designed to count the number of vehicles passing a certain point on a road or road and many other business- related operations.
4. Smart Traffic Management Systems ameliorate the performance of road services through the use of detectors and GPS.

Conclusion

To decrease over-speeding on roads, leading to a significant reduction in traffic violations and related accidents. Automation through the integration of sensor-based technology, GPS modules, and communication systems ensures smooth and effective operation. The accuracy and reliability of the data collected are critical for successful over-speeding detection. As fewer vehicles exceed speed limits, overall road safety will improve, resulting in fewer accidents. This will also contribute to a reduction in traffic congestion caused by accidents and emergency response activities, further enhancing the efficiency and safety of road networks.

References

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Copyright

Copyright © 2025 Dr. S. S. Sawwashere, Mr. Farzan Khan, Mr. Gaurav Ramteke, Mr. Ritesh Mendhekar, Mr. Ritesh Bhoyar. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.