Application of risky driving behavior in crash detection and analysis

Road transport is been used for moving people and all kinds of goods through-out the world. However, it is one mode of transportation that is prone to accidents and it faces a plethora of never-ending challenges, such as the fre-quent loss of lives and valuables when accident occurs. The best course of action to handle these issues is to set up an autonomous incident detection system using wireless communication, 5G technologies and the Internet of Things. IoT is a seamless technology that increases the connectivity between humans and machines. It is web-based, and improves communication between vehicle to vehicle, vehicle to infrastructures, transfer of data and information to predict incident occurrences through various networks and frameworks such as eCall, OneM2M and integration of mobile broadband. Additionally, internet of things is being adopted for public safety; for in-stance, it can speed up first responders’ response times to situations by dis-playing the best routes to a scene of an accident. The rapid development of 5G is happening in parallel with developments of internet of things (IoT), artificial intelligence (AI), and smart platforms for novel applications such as mission-critical communications. 5G is a new generation technology that op-erates on the Ultra High Spectrum Band UHSB. It is an innovation that uses the pedestrians-vehicle-road-cloud, and the communication between vehicle locations and temperature of high-quality connection.

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A Review of Road Accidents Detection through Wireless Technology—5G, MIMO and Internet of Things

Internet of Things (IoT) and 5G are enabling intelligent transportation systems (ITSs). ITSs promise to improve road safety in smart cities. Therefore, ITSs are gaining earnest devotion in the industry as well as in academics. Due to the rapid increase in population, vehicle numbers are increasing, resulting in a large number of road accidents. The majority of the time, casualties are not appropriately discovered and reported to hospitals and relatives. This lack of rapid care and first aid might result in life loss in a matter of minutes. To address all of these challenges, an intelligent system is necessary. Although several information communication technologies (ICT)-based solutions for accident detection and rescue operations have been proposed, these solutions are not compatible with all vehicles and are also costly. Therefore, we proposed a reporting and accident detection system (RAD) for a smart city that is compatible with any vehicle and less expensive. Our strategy aims to improve the transportation system at a low cost. In this context, we developed an android application that collects data related to sound, gravitational force, pressure, speed, and location of the accident from the smartphone. The value of speed helps to improve the accident detection accuracy. The collected information is further processed for accident identification. Additionally, a navigation system is designed to inform the relatives, police station, and the nearest hospital. The hospital dispatches UAV (i.e., drone with first aid box) and ambulance to the accident spot. The actual dataset from the Road Safety Open Repository is used for results generation through simulation. The proposed scheme shows promising results in terms of accuracy and response time as compared to existing techniques.

5G and IoT Based Reporting and Accident Detection (RAD) System to Deliver First Aid Box Using Unmanned Aerial Vehicle.

This report shows the outcome by applying large scale data mining techniques on the Finnish roads. From the research study it is very difficult task to perform because the collected data have uncertainty, incomplete and error values. So the data exploration is a challenging task. The\n data used in the process have been collected from Finnish road administration data sets. The data used in the process have been collected from Finnish road administration data sets. The main target of our project is to look into practicability of Robust clustering, to find the associations\n and repeated item sets and applying apprehend methods for the analysis of road accidents. While the results display the selected mining techniques and methods were capable to the understandable patterns. To calculate the accident frequency count as a parameter /c-means algorithm is used to\n cluster the locations. To characterize the surface conditions association rule mining is used. data mining skills disclosed different environmental reasons associated with road accidents. Intersection on highways have been identified as a dangerous for fatal accidents.

Navyasri Mungamuri

Papers

Car Accident Detection and Notification System Using Smartphone