Analysis of Data from Software Sensor for Smart Airbags Deployment

Elnashar, Elsayed Ahmed; Zlatev, Zlatin

doi:10.4172/2168-9695.1000181

Cited by 4 publications

(2 citation statements)

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“…A safe road traffic system is defined as one that accommodates drivers' and pedestrians' safety [15], [16]. Several new types of technologies have been deployed to enhance driver safety, such as intelligent airbags [17], automatic vehicle brakes [18], self-control systems, and to name a few. However, these efforts seem insufficient to reduce the risks and crashes on the roads because road infrastructure also plays an essential role [19].…”

Section: Introductionmentioning

confidence: 99%

Visualization and Analysis of Safe Routes to School based on Risk Index using Student Survey Data for Safe Mobility

Jin

Khudoyberdiev

Kim

2022

JOIV : Int. J. Inform. Visualization

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Risk analysis is important in heterogeneous industrial domains to enable sustainable development. Data is the basis for emphasizing the potential risk elements for improving efficiency, quality, and safety. For supplying safe routes to schools based on risk analysis, the risk assessment of routes is one of the widely used and very effective methodologies to filter the most dangerous roads, intersections, or specific points on roads. This paper presents a visualization and analysis of the risk assessment approach based on the risk index model using geographical information, including routes, danger points, and student survey data. The proposed risk index model is used for deriving a risk index based on geographical information, including danger points and a route's path. The model includes an equation to calculate the distance of danger points to the path using the coordinates of each location. The survey data is mainly comprised of route and survey information that is analyzed and preprocessed for the input data of the risk index model. The survey mainly consists of basic information on the route, survey participants, school route information, and school route coordinates. The data is classified into the school route data set and the school route danger points data set, and these values are applied to the analysis and the risk index model. Also, the risk index model is designed and developed through the analysis of routes.

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Section: Introductionmentioning

confidence: 99%

Visualization and Analysis of Safe Routes to School based on Risk Index using Student Survey Data for Safe Mobility

Jin

Khudoyberdiev

Kim

2022

JOIV : Int. J. Inform. Visualization

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“…Depending on these characteristics, the degree of reliability of the results is subsequently determined. In recent years, with the development of technology, many of the quantities whose measurement previously required complex, bulky and expensive apparatuses can now be counted with mobile-integrated sensors [2,3,4,6]. Bruwer et al [1] offer a solution to the problem of using a mobile phone accelerometer by compensating for its deviations by adding a Kalman filter.…”

Section: Introductionmentioning

confidence: 99%

Acceleration Measurement of Road Vehicles by Mobile Phone

Ivanov¹

2019

ARTTE

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The paper reviews existing solutions for the application of an acceleration sensor built into a mobile phone. A drawback of the results published in the available literature is that the experimental studies are performed in laboratory conditions and that high-complexity procedures and algorithms are used. It is necessary to perform field surveys, taking into account the factors influencing the measurement of the acceleration with a mobile phone. The studies and results obtained are complementary to those available from the literature in that the measurements are made "on the road". Factors that influence measurement accuracy in real-life conditions are defined. The results obtained show that mobile phones, regardless of brand and model, should be used to make such measurements and comparisons before being used for such purposes in order to make objective results and conclusions in scientific developments.

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