Accident Prevention System Research Articles

A Driver Health Monitoring-based Accident Prevention System for Commercial Vehicles in India

In the growing nation, road transportation is crucial. Accident rates will rise in tandem with an increase in road traffic. There are several categories in which accidents might arise. Among these reasons, one significant cause—the accident resulting from a heart attack—is chosen here. The majority of the time, it is seen that drivers who experience heart attacks abruptly lose control of their vehicles, which leads to accidents. The suggested system aims to address this problem by identifying heart attack symptoms early and automatically slowing down the vehicle. It also applies a gentle hand brake to bring the car to a stop, and it uses GSM services to send a GPS-coordinated message to the relevant department, such as the health department. The goal of the suggested approach is to raise the survival rate.

IoT Based Vehicle Accident Detection, Prevention and Parking System

IoT Based Vehicle Accident Detection, Prevention and Parking System

Comprehensive Systems Review for Accident Detection, Prevention, and Real-Time Alerting Mechanisms

The growth of technology and infrastructure at a rapid pace has made our lives easier. The increased frequency of road accidents and possible traffic dangers brought about by newer technologies has resulted in a significant loss of life and property due to inadequate emergency facilities and preventive measures. The greatest hazard to human life is traffic accidents. High speeds combined with intoxication are the main causes of many accidents. Vehicle safety and accident prevention and detection systems are important because they reduce the number of accidents and the time it takes for an accident to be recognized, allowing rescue personnel to attend to injured victims more quickly. This article presents the MCU-designed Vehicle Tracking and Accident Detection system along with several accident avoidance strategies.A prototype of an accident prevention & detection system using a vibration sensor as the detector and an ultrasonic sensor, or IR sensor, is to detect a signal in case of a near collision or a distance between two vehicles to prevent an accident. Even after this, if an accident occurs, they send a signal to the connected microcontroller via the vibration sensor. When the signal is received, the controller activates the relay, causing the airbag to deploy and the brakes to automatically lock. Meanwhile, a message is sent to the nearest help center, so ambulance service and other aid can come in the quickest time feasible.A black box gathers driving information before, during, and after a crash about the vehicle in which it is installed. The data collected by the black box includes speed, braking, acceleration, steering, and airbag deployment. The help can be provided in areas like vehicle safety, collision victim care, insurance corporations, vehicle crash investigations, and improving road conditions through the automotive black box system, which can reduce death rates to a significant level. The main aim of this paper is to include the overview and basics of certain techniques utilized to prevent, detect accidents, and alert the nearby help centers for the fastest aid in case of an accident.

Accident Prevention System for Cars, Buses, Trucks

Driver drowsiness is a significant factor in road accidents, contributing to a large number of crashes annually. To enhance road safety, the development of a Drivers Drowsiness Detection System is essential. This system builds to detect early signs of lazyness in drivers and provide timely alerts to prevent accidents. The proposed system uses to track key indicators of drowsiness, such as eye closure, head position, yawning, and blink rate. By utilizing a camera-based real-time monitoring system, it continuously analyzes the driver’s facial expressions. The system employs cadcade algorithms to distinguish a featurebased object detection algorithm to detect objects from images between alert and drowsy states based on collected data. When drowsiness is detected, the system triggers alerts like audio warnings, seat vibrations, or even vehicle slowing mechanisms, depending on the integration. This technology has the potential to significantly reduce the number of road accidents related to driver fatigue and could be applied in both personal vehicles and commercial fleets. The implementation of such systems represents a critical step toward improving road safety and decreasing driver-related incidents. Nowadays it is very challenging to stay active all the time due to busy schedules. Falling asleep while driving can lead to serious consequences, accidents, and even death. This situation is much more common and therefore it is very important to solve this problem. So, to solve this problem, we developed a sleep alarm system for drivers. This system alerts the user when he falls asleep at the wheel, thus the main concern is preventing accidents and saving lives. This system is useful for long- distance travelers and late-night drivers.

Hospital Preparedness Analysis in Disaster Management : Literature Review

Under Act No. 44 of 2009, hospitals have a responsibility to actively engage in disaster situations, provide services to victims as they can, and have an accident prevention and disaster management system. This research aims to find out how prepared some hospitals are in disaster management based on some library studies. The preparation of this article uses a method of systematic literature review using 10 articles from 2019 to 2024 from search databases, namely Google Scholar, Garuda, Sage Journals, and ScienceDirect. Although hospitals have policies and standard operational procedures to cope with disasters, the findings suggest that their implementation by health personnel is not optimal. Although disaster response teams, K3RS teams, and abuse teams have been formed, education and training efforts are still not at their maximum. Hospitals are important in disaster management, but many still need improvements such as special guidelines, infrastructure, and intensive training. Preparedness includes planning, organization, movement, control, and recovery. Ready hospitals have emergency response teams, training programs, and early warning systems.

Accident Prevention System

Accident prevention system represents a groundbreaking innovation in vehicular safety technology. This advanced system integrates cutting- edge technologies such as eye blink sensors, GPS modules, Arduino and GSM communication to detect and mitigate potential hazards during driving. The accident prevention system incorporates a GPS module, enabling precise location tracking and providing crucial data for emergency responders. The integration of these technologies aims to significantly reduce the risk of accidents caused by driver inattention, fatigue, or other safety-critical factors. This abstract outline the comprehensive approach of accident prevention system, highlighting its potential to revolutionize road safety by leveraging state-of-the-art sensor technologies and intelligent communication systems. Key Words: Eye blink sensor, Arduino, GPS Module, GSM Module.

A Survey on Vehicle Tracking and Accident Prevention System

A Survey on Vehicle Tracking and Accident Prevention System

Analysis of AP1000 Small-Break Loss-of-Coolant Accident Using Reactor Transient Simulator

The Westinghouse Electric Company’s Advanced Passive Reactor (AP1000) is characterized by the incorporation of passive safety systems (PSSs) designed to ensure core cooling during transient events. The assessment of PSSs requires evaluation of their performance through a combination of experiments and simulations employing various thermal-hydraulic codes. In addition, detailed evaluation of PSSs for a specific reactor system transient analysis such as loss-of-coolant-accident analysis supports understanding representative integral effects test facility development and the further evolution model development and assessment process. Developing a reactor system code is a complex and time-consuming process that requires significant engineering expertise and effort. It can take several months to even years to complete in the early stages of reactor system design and analysis. However, this process can be expedited through the use of transient simulator models for similar reactor systems, which can be used for lesson learning and training purposes. This study uses the Personal Computer Transient Analyzer (PCTRAN) code. The main advantage of PCTRAN is its ease of use and ability to run faster than real time. This study presents the results obtained for a small-break loss-of-coolant accident (SBLOCA) for two breaks using the full version (licensed) of PCTRAN. The purpose of this investigation is to evaluate the overall system behavior during the postulated SBLOCA event as well as assess the capability of the PCTRAN code to reproduce the system response during transient events. The obtained results were compared with the Westinghouse NOTRUMP system code. The PCTRAN code proved to be reliable in predicting the qualitative behavior of the system in both transient cases. As for the system response, it was found that it is contingent on the activation time of the PSSs. The differences in reactor coolant system pressure between the two codes were attributed to the critical flow model and simplification of mass and energy balance. Despite PCTRAN’s limitations, it can still provide a reasonable prediction of various reactor parameters such as pressure, mass flow rate, and void fraction during a SBLOCA scenario. It is worth noting that PCTRAN currently employs a bulk approach similar to that of the Modular Accident Analysis Program (MAAP) and MELCOR codes. However, the upcoming version of PCTRAN will include an artificial intelligence–based detection and accident prevention system, as well as different models for different reactor components. Consequently, PCTRAN has the potential to be upgraded to match the system thermal-hydraulic codes of the U.S. Nuclear Regulatory Commission and become more widely used in cybersecurity to safeguard nuclear power plants from cyberattacks.

Smart Vehicle Accident Prevention and Road Safety System with Real Time Data Acquisition

Smart Vehicle Accident Prevention and Road Safety System with Real Time Data Acquisition

VEHICAL ACCIDENT PREVENTION SYSTEM FOR MOUNTAIN ROADS

Vehicle accident prevention system can be a major step in accident safety on mountain roads. In past 100s of accident and death on mountain roads, some even fall from the cliff which are not traced after that have been noticed. Such accidents not only cause loss of human life but also major loss financially not just to the individual but also the government. Mountain roads are narrow and any such accidents can force it to be closed for hours which can be a huge issue. This project addresses the pressing issue of mountain road safety through the deployment of two strategically positioned ultrasonic sensors in U curves. The primary objective is to detect oncoming vehicles, precisely measure distances, and promptly activate warnings on the opposite side. By leveraging real-time data and proactive measures, the system aims to significantly reduce accidents in challenging terrains. The integration of red LED lights and a buzzer enhances visibility and auditory awareness. This innovative approach reflects a crucial step forward in accident prevention, particularly in mountainous regions, where traditional safety measures fall short.

Driving Behavior during Left-Turn Maneuvers at Intersections on Left-Hand Traffic Roads.

Understanding left-turn vehicle-pedestrian accident mechanisms is critical for developing accident-prevention systems. This study aims to clarify the features of driver behavior focusing on drivers' gaze, vehicle speed, and time to collision (TTC) during left turns at intersections on left-hand traffic roads. Herein, experiments with a sedan and light-duty truck (< 7.5 tons GVW) are conducted under four conditions: no pedestrian dummy (No-P), near-side pedestrian dummy (Near-P), far-side pedestrian dummy (Far-P) and near-and-far side pedestrian dummies (NF-P). For NF-P, sedans have a significantly shorter gaze time for left-side mirrors compared with light-duty trucks. The light-duty truck's average speed at the initial line to the intersection (L1) and pedestrian crossing line (L0) is significantly lower than the sedan's under No-P, Near-P, and NF-P conditions, without any significant difference between any two conditions. The TTC for sedans is significantly shorter than that for trucks with near-side pedestrians (Near-P and NF-P) and far-side pedestrians in Far-P. These insights can contribute to the ongoing development of accident-prevention safety systems for left-turning maneuvers at intersections.

Fuzzy-Based Road Accident Risk Assessment

It is necessary to extensively investigate the causes of road accidents with the utmost precision to harness future technological advancements, such as autonomous driving and intelligent accident prevention systems. Nevertheless, since most accidents are attributed to simple human errors, unraveling the complex root-cause factors poses a considerable challenge. This is where fuzzy logic can offer a potential solution: it is essential to understand even seemingly straightforward errors, such as speeding, to identify external factors that could play a pivotal role in future accident prevention. A more in-depth examination and comprehension of elements like road curvature, slope, and their correlation with accidents are necessary. Additionally, it is crucial to explore how the frequency of accidents on specific road segments varies under diverse weather conditions. This article analyzes which curves can be considered more dangerous and the factors that render them risky. The fuzzy model presented in this article is primarily capable of estimating the risk of a given road segment based on its curvature characteristics. The model results presented in the article indicate that sections of the road can become more risky due to multiple curves and curves with a radius of less than 80 m. The model assesses risk based on the physical characteristics of road segments, primarily the curvature radius, while, typically, other road risk assessment models rely on traffic volume and accident counts.

Alcohol and Drowsiness Detection in Smart Transportation System

Abstract: Drunk driving is a major contributing factor in the rising number of unintentional deaths that occur in the modern day. Drunk driving is an extremely dangerous practice that can result in car accidents and injuries on the road. Numerous preventative actions had been implemented, including license suspension, fines, and the seizure of motor vehicle permits. Notwithstanding the numerous measures implemented, the proportion of collisions caused by intoxicated drivers continues to rise. The purpose of this module is to shield people from needless deaths brought on by intoxicated and sleep-deprived drivers in traffic accidents. This module includes a Wi-Fi module and an alcohol detection sensor (MQ-3) based on the Raspberry Pi model 3. We are incorporating an automated drowsy driver monitoring and accident prevention system as part of the design of our major project.

Railway Accident Prevention Using Sensor

Rail accidents pose a significant threat to both human life and infrastructure. This abstract presents a comprehensive overview of the railway accident prevention system that incorporates various sensors for effective monitoring and early detection of potential threats. The proposed system includes sensors such as ultrasonic Sensor and Vibration Sensor. These sensors work in tandem to collect real-time data on various parameters, including train location, Accident, obstacles on the track. Obstacles on the right of way of the train can cause derailment, collision, injuries to train passengers and loss of properties, Railway accident prevention and protection are a key part of a wider picture of transport safety. so, there is a need to look at various ways to prevent or reduce the frequency and severity of these accidents by using Arduino based safety system to mitigate these accidents. The aim of this paper is to simulate a program in Proteus to detect obstacles on the right of way of trains. Arduino code is written to detect obstacle on the track in the train. By implementing these features in real time application, we can avoid accidents up to a very significant margin. The railway accident prevention system aims to minimize the occurrence of accidents, reduce response time, and enhance overall safety in railway operations through the use of advanced sensor technologies.

Driver Safety: Accident Prevention and Detection System

The integrated Accident Prevention and Detection System is a groundbreaking venture poised to elevate vehicular safety with advanced technology. By amalgamating a NodeMCU microcontroller, alcohol detection sensor, eye blink sensor, and GSM module, this system offers a holistic solution. Monitoring alcohol levels and signs of fatigue, the sensors feed data to the NodeMCU, the brain of the system. Real time analysis allows the system to foresee potential collisions and promptly intervene. Beyond collision prevention, the GSM module enables emergency communication, instantly alerting authorities via SMS in case of a looming collision. With remote monitoring capabilities and GPS tracking for accurate location data, this system is tailored for adaptability and user- friendliness. By combining these elements, it not only detects impairment but also proactively mitigates risks, standing as an innovative safeguard for road safety. Key Words: NodeMCU microcontroller, Eye Blink Sensor, GSM Module, Alcohol Detection Sensor, SMS Alerts, Vehicle Safety, Remote Monitoring, GPS Tracking.

건설현장의 KOSHA-MS 영향요인 연구

Despite the implementation of diverse policies and systems by the government aimed at mitigating severe disasters such as deaths, the occurrence of fatal incidents within the construction industry remains alarmingly high, comprising 53% of the industry as a whole. Consequently, this research endeavor was undertaken with the aim of identifying an efficacious approach for KOSHA-MS(Korea Occupational Safety and Health Agency Management System), the pivotal component of the construction site accident prevention system, to enhance its efficacy and effectiveness. In this study, the independent variables were comprised of four human factors and two occupational factors. These variables were constructed based on interviews with forty safety and health management managers, as well as safety managers, from twenty construction sites operated by S Construction. A review of previous research was also conducted. The dependent variable, on the other hand, was the configuration of KOSHA-MS. A survey encompassing a total of 151 construction employees and workers was conducted between 1, November, 2023, and 21, November, 2023. The gathered data underwent statistical analysis utilizing the SPSS program.&#x0D; The study found that the survey items had good validity and reliability. Additionally, the roles of safety and health managers and management supervisors, were identified as significant human factors, while hazardous work was identified as a significant occupational factor impacting KOSHA-MS. The findings of this study indicate that effective managerial roles and the management of hazardous work take part in a crucial role in the practical and effective implementation of KOSHA-MS.

Implementation of an Occupational Safety and Health Management system (A Study of the Implementation of Occupational Safety and Health at PT PLN Indonesia Power, Barrru)

This research aims to determine: Implementation of Occupational Safety and Health Management at PT. PLN Indonesia Power, Barru, by collecting data obtained by observation, interviews, documentation. The results of this research show that PLN Indonesia Power UJP PLTU Barru considers it necessary to implement a system occupational safety and health management in every activity carried out. The implementation of an Occupational Safety and Health Management System (SMK3) in a company is basically a requirement stated in Law Number 13 of 2003 concerning Manpower Article 87 that companies are required to implement an Occupational Safety and Health Management System that is integrated with the company's management system. Based on interview procedures, the implementation of occupational safety and health in the work accident prevention and management system at PLN Indonesia Power PLTU Barru OMU has been carried out. Based on Rahmat Kamruddin's presentation as Senior Environmental K3 Supervisor, factors that influence the running of K3 include communication. Communication at work will influence the work process and is even an essential part of it.

A review on recent driver safety systems and its emerging solutions

Road safety and accident prevention are critical concerns in modern transportation. This paper presents a comprehensive survey of driver safety systems, focusing on the latest advancements in this field. We analyze the existing literature to identify key research trends in driver safety systems, encompassing various categories of solutions. Our survey delves into the reasons behind road accidents and assesses the effectiveness of emerging technologies and solutions in accident prevention. By categorizing and evaluating these solutions based on the Internet of Things and Machine Learning, we provide valuable insights into the landscape of road accident detection and prevention systems. This survey not only highlights the current state of the art but also serves as a reference for future research and innovation in the domain of driver safety. Abbreviations IoT: Internet of things; CNN: Convolutional Neural Network; SVM: Support vector machine; HRV: Heart rate variability; RRI: R-R Interval; MSPC: Multivariate Statistical process control; EAR: Eye aspect ratio; HUD: Head-up display; GPS: Global positioning system; CAN: Controller area network; GPU: Graphics processing unit; IR: Infrared; GSM: Global system for mobile communication; EEG: Electroencephalogram; PCA: Principal component analysis; SVC: Support vector classifier; SdsAEs: Stacked denoising sparse autoencoders; ECG: Electrocardiogram; LED: Light emitting diode; NFC: Near field communication; PSO: Personal security officer; PPG: Photoplethysmography; EDA: Electrodermal activity; EMG: Electromyography; LCD: Liquid crystal display; RF SoCs: Radiofrequency system on chip; PLR: Piecewise linear representation; BAC: Blood alcohol content; BPNN: Backpropagation Neural Network; ADSD: Automated driver sleepiness detection; EOG: Electroocoulogram; KNN: K nearest neighbor; CBR: Case-based reasoning; RF: Random forest; NIR: Near-infrared; LBP: Local binary pattern; PERCLOS: Percentage of Eye Closure; SVD: Singular value decomposition; FFT: Fast Fourier transform; LSTM: Long short-term memory; DDD: Drunk driver detection; BLE: Bluetooth low energy; SWM: Steering wheel movements; M-SVM: Mobile-based Support Vector Machine; AI: Artificial intelligence; ML: Machine learning; DL: Deep learning; PCA: Principal component analysis; IPCA: Incremental principal component analysis; ANN: Artificial neural network; CAV: Connected and automated vehicles

ВОПРОСЫ СОВЕРШЕНСТВОВАНИЯ ТРАНСПОРТНОЙ ОТРАСЛИ В УСЛОВИЯХ РАЗВИТИЯ ПОДКЛЮЧЁННЫХ ТРАНСПОРТНЫХ СРЕДСТВ

The article examines topical issues of improving the transportation industry in the context of the active development and implementation of connected vehicles (CVs). The relevance of the topic is driven by the rapid growth in the number of CVs, their increasing impact on the transportation system, and the need for a comprehensive optimization of the industry to fully realize the potential of new technologies. The main objective of the work is to identify key ways and specific measures to improve the transportation industry that will allow maximizing the benefits of CVs. To achieve this goal, a systems approach is used, which involves a comprehensive consideration of the complex interrelationships between vehicles, infrastructure, and transportation services. The implementation of Intelligent Transportation Systems (ITS) plays a crucial role in optimizing the interaction of these components. The article identifies the main opportunities and challenges associated with the development of CVs. New opportunities include improving road safety, reducing emissions, optimizing logistics and transportation, and enhancing mobility. At the same time, new challenges are emerging, including the need to ensure cybersecurity of CVs, standardization of heterogeneous systems and technologies, and their seamless interaction. The impact of CVs on key aspects of the transportation industry – safety, environment, economy, and social sphere – is analyzed in detail. Specific ways to improve safety are shown through accident prevention systems and driver monitoring systems. The potential of CVs to reduce emissions through traffic optimization and development of alternative modes of transportation is considered. Ways to increase efficiency through logistics optimization, vehicle maintenance, and driver routing are identified. Social effects in the form of increased mobility and new services for passengers are highlighted. The scientific novelty lies in the comprehensive systems consideration of a wide range of problems and ways to improve the transportation industry, taking into account the rapid development of CVs. The practical significance is the specific recommendations on applying a systems approach and implementing ITS to achieve maximum effect. Further research directions include a detailed elaboration of the proposed specific measures to maximize the benefits and minimize the risks associated with the proliferation of CVs. In particular, it is recommended to further optimize logistics processes, vehicle fleets and driver activities, accelerate the development of alternative modes of transportation and services to improve passenger comfort and safety, and establish close cooperation among all stakeholders.

AI-Driven Autonomous Accident Prevention and Alertness System

AI-Driven Autonomous Accident Prevention and Alertness System