An integrated approach to designing an automated processing system for Big Data on the haulage process by transport vehicles
R.N. Safiullin1, M.S. Prisyazhnyuk2, A.Z. Parra1, R.R. Safiullin1, А.А. Ungefuk1
1 Empress Catherine II Saint Petersburg Mining University, Saint Petersburg, Russian Federation
2 Leningrad Region Transport Committee, St. Petersburg, Russian Federation
Russian Mining Industry №4 / 2025 p. 122-129
Abstract: The article discusses the issues of assessing the haulage efficiency by mining dump trucks using an algorithm for an automated system to process Big Data collected from sensors and GLONASS/GPS-based devices mounted on the vehicles in real time mode. Techniques are proposed to reduce the time required for on-line data processing and analysis, including the design of distributed processing infrastructure, real-time optimization algorithms, and machine learning methods for managing and analyzing the data from sensors, GPS systems and other intelligent devices of the vehicles. The developed algorithm to process Big Data of the haulage process takes into account the collection, storage, analysis, visualization of the data as well as a structural model for determining the technical and operational performance indicators of the haulage process, i.e. the delivery time, vehicle load factor, volume of cargo transported, mileage utilization factor, fuel consumption, idle time and availability factor.
Keywords: automated system, Big Data processing algorithm, assessment of the haulage process, mining dump trucks
For citation: Safiullin R.N., Prisyazhnyuk M.S., Parra A.S. Safiullin R.R., Ungefuk А.А. An integrated approach to designing an automated processing system for Big Data on the haulage process by transport vehicles. Russian Mining Industry. 2025;(4):122– 129. (In Russ.) https://doi.org/10.30686/1609-9192-2025-4-122-129
Article info
Received: 16.04.2025
Revised: 05.06.2025
Accepted: 16.06.2025
Information about the authors
Ravill N. Safiullin – Dr. Sci. (Eng.), Professor, Professor of the Department of Transport and Technological Processes and Machines, Empress Catherine II Saint Petersburg Mining University, Saint Petersburg, Russian Federation; https://orcid.org/0000-0002-8765-6461; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Michael S. Prisyazhnyuk – Cand. Sci. (Eng.), Chairman of the Leningrad Region Transport Committee, St. Petersburg, Russian Federation; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Arias Zunilda Parra – Postgraduate Studentof the Department of Transport and Technological Processes and Machines, Empress Catherine II Saint Petersburg Mining University, Saint Petersburg, Russian Federation; https://orcid.org/0000-0003-1715-7998; email: This email address is being protected from spambots. You need JavaScript enabled to view it.
Ruslan R. Safiullin – Cand. Sci. (Eng.), Associate Professor, Associate Professor of the Department of Transport and Technological Processes and Machines, Empress Catherine II Saint Petersburg Mining University, Saint Petersburg, Russian Federation; https://orcid.org/0000-0003-2315-3678; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Aleksandr A. Ungefuk – Cand. Sci. (Eng.), Associate Professor Associate Professor of the Department of Transport and Technological Processes and Machines, Empress Catherine II Saint Petersburg Mining University, Saint Petersburg, Russian Federation; https://orcid.org/0000-0003-1473-9095; e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
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