Predictive System for Road Condition Monitoring based on Open Climate and Remote Sensing Data - A Case Study with Mountain Roads
Kairanbayeva A. Nurakynov S. Zhantayev Z. Nurtas M. Nurpeissova G. Panyukova D. Mitkov A. Talgarbayeva D. Kudaibergenov M.
April 2024Engineered Science Publisher
Engineered Science
2024#28
Roads are a crucial component of a countrys economic development. Therefore, monitoring and maintaining roads are primary tasks for transportation departments. This study proposes a cost-effective approach to reduce these expenses by introducing a predictive system. This system leverages openly accessible data sources, such as climate and remote sensing information. The foundational framework of this system relies on regression and neural network models, which have been trained using the aforementioned datasets, as well as data from on-site road inspections. These models assign varying weights to input parameters, elucidating the influence of both meteorological conditions and landscape characteristics on the roads overall condition. The resultant system offers forecasts for nine distinct attributes of road sections, each defined by their geographical coordinates. Furthermore, it categorizes the roads condition and provides a visual representation of this data on a geographical map. By exclusively utilizing openly accessible meteorological and remote sensing data, this system has the potential to serve dual purposes, facilitating remote diagnostics and aiding in road design support.
Climate data , Forecasting , Meteorological data , Neural network , Open data , predictive , Regression model , Remote sensing , Road diagnostics , Road maintenance
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Institute of Ionosphere, Almaty, 050020, Kazakhstan
Department of Mathematical and Computer Modeling, International Information Technology University, Almaty, 050040, Kazakhstan
Engineering Institute, Caspian University, Almaty, 050000, Kazakhstan
Alternativa Club, Almaty, 050060, Kazakhstan
Institute of Ionosphere
Department of Mathematical and Computer Modeling
Engineering Institute
Alternativa Club
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