Pavel Maschenko
Deputy general director
LocoTech-Signal
| In 2004 graduated from Russian University of Transport (MIIT) with a degree in Automation, Telemechanics and Communication in Railway Transport. In 2007 defended his Ph.D. thesis on the topic: "Improving the efficiency of devices for interval control of train traffic, given the level of electromagnetic interference created by future potential electric rolling stock." In 2012 received a second higher education with a degree in State and Municipal Administration. 15 years of experience in the railway industry, including participation and leadership in the development, design and implementation of modern safety and train control systems for subways and mainline railways. In the period 2014-2019 worked in various positions in the development of innovative software and hardware in the Russian offices of Bombardier Transportation and Siemens corporations in the field of rail traffic control systems. Since 2020 - Deputy General Director of LocoTech-Signal LLC, General Director of ATM LLC, members of the group of companies led by Transmashholding JSC, united by a common strategy for digitalization of railway transport. LocoTech-Signal LLC, ATM LLC develop products and solutions for automation of signaling devices, train traffic control systems and machine vision systems for technological processes of enterprises, including automation movement of locomotives. Author of over 40 scientific articles and patents for inventions. |
Machine vision for the automation of traction vehicles in undustrial transport
Digitalization covers more and more industries, and Machine Vision has become the most popular technology in the modern world. Machine Vision technology allows you to improve vehicle management performance through advanced infrastructure diagnostics. Machine Vision Center of Competence was found in May 2020 on the basis of LocoTech-Signal LLC in order to develop digital solution to face railway transport challenges. Machine vision is digital solution based on artificial intelligence allows remote control of locomotives with minimal human intervention. In particular, it provides: reliable monitoring of the condition and actions of the driver, energy-efficient control of the movement of the locomotive itself, detection of obstacles to prevent collisions. You will learn more details about machine vision, its structure and place in the ecosystem of similar solutions for industrial railway transport. He will share his experience in implementing projects based on machine vision and real cases results.