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Japanese
A Train
  • Mostafiz Hossain
  • September 22, 2020

AI-based Rail Corridor Monitoring

Artificial Intelligence (AI) is not a new field; researchers have been working with AI since the 1950s. Today, AI is helping to make all modes of transportation safer and more efficient by identifying potential risks, tracking vehicles or monitoring traffic lights to improve safety. For decades, railways around the world have suffered from lack of innovation. However, in more recent times, AI has found adoption in several railway-related applications such as automation of train scheduling, workforce planning, asset management, intelligent signaling systems,
detecting defects on the railway tracks, etc. AI is also being used to build efficient network simulators which can help railway companies run trains with minimum disruption, resulting in saving fuel and electricity.

Even though the railway networks around the world have become more efficient and organized, passengers still face disruptions and delays due to insufficient information at railway terminals and delayed responses every other day. This has led to railway companies starting to adopt AI applications to process information in real time and improve customer experience.

At Ignitarium, we have been solving a variety of industrial problems with AI, ranging from civil infrastructure, transportation, food, footwear, automotive and solar. We have also showcased our capability to detect anomalies on railway tracks, with our aerial-based analytics solution. Check this link.

One of the solutions we have developed is an application to count the wagons in a freight train using pre-installed camera infrastructure. The key challenge was to deal with the acute field of view (FoV) and yet maintain high count accuracy even when trains are passing by at high speeds. Note that if camera angles could be controlled to change to a more orthogonal FoV, the problem statement would have been a whole lot simpler.

Fig.: Automatic Wagon detection and counting from non-orthogonal FoV

Once the application receives the video feed, it transforms the latter into several adjacent frames. From each frame, the area of interest is separated, which in this specific case, are those pixels which represent the train itself. Then a perspective transformation or change of angle of the frame is performed to get a proper view of the train. The transformed frames then go through a detection network to correctly identify individual wagons. Once wagons are detected, a tracking algorithm is employed to sequentially count the number of wagons from each of the frames. The application keeps counting the wagons and displays the count on screen as the train passes through.

The algorithm can be extended to numerous other related applications, a few examples of which are listed below:
 counting the number of containers (including vertically stacked) on a flatbed wagon
 detecting position of special cars in a passenger rake
 counting the number of locomotives in a freight train
 fine tuning the scheduling of level crossing barrier closure timings by timing the crossing time of a passenger or freight train

In conclusion, with the right combination of AI and Image processing algorithms, and ever-increasing compute horsepower, there is huge scope of improving the efficiencies of traditional industries like railways.

278 thoughts on “AI-based Rail Corridor Monitoring”

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      Siby has over 31 years of experience in the semiconductor industry. In his last role at Wipro Technologies, he headed the Semiconductor Industry Practice Group where he was responsible for business growth and engineering delivery for all of Wipro’s semiconductor customers. Prior to that, he held a vast array of crucial roles at Wipro including Chief Technologist & Vice President, CTO Office, Global Delivery Head for Product Engineering Services, Business Head of Semiconductor & Consumer Electronics, and Head of Unified Competency Framework. He was instrumental in growing Wipro’s semiconductor business to over $100 million within 5 years and turning around its Consumer Electronics business in less than 2 years. In addition, he was the Engineering Manager for Enthink Inc., a semiconductor IP-focused subsidiary of Wipro. Prior to that, Siby was the Technical Lead for several of the most prestigious system engineering projects executed by Wipro R&D.

       

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      He completed his MTech. in Electrical Engineering (Information and Control) from IIT, Kanpur and his BTech. from NIT, Calicut

       

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      Chief Technology Officer

       

      As CTO, Sujeeth is responsible for defining the technology roadmap, driving IP & solution development, and transitioning these technology components into practically deployable product engineering use cases.

       

      With a career spanning over 30+ years, Sujeeth Joseph is a semiconductor industry veteran in the SoC, System and Product architecture space. At SanDisk India, he was Director of Architecture for the USD $2B Removable Products Group. Simultaneously, he also headed the SanDisk India Patenting function, the Retail Competitive Analysis Group and drove academic research programs with premier Indian academic Institutes. Prior to SanDisk, he was Chief Architect of the Semiconductor & Systems BU (SnS) of Wipro Technologies. Over a 19-year career at Wipro, he has played hands-on and leadership roles across all phases of the ASIC and System design flow.

       

      He graduated in Electronics Engineering from Bombay University in 1991.

       

      SUJITH MATHEW IYPE Co-founder & CTO

      SUJITH MATHEW IYPE

      Co-founder & COO

       

      As Ignitarium's Co-founder and COO, Sujith is responsible for driving the operational efficiency and streamlining process across the organization. He is also responsible for the growth and P&L of the Semiconductor Business Unit.

       

      Apart from establishing a compelling story in VLSI, Sujith was responsible for Ignitarium's foray into nascent technology areas like AI, ML, Computer Vision, and IoT, nurturing them in our R&D Lab - "The Crucible".

       

      Prior to founding Ignitarium, Sujith played the role of a VLSI architect at Wipro Technologies for 13 years. In true hands-on mode, he has built ASICs and FPGAs for the Multimedia, Telecommunication, and Healthcare domains and has provided technical leadership for many flagship projects executed by Wipro.

       

      Sujith graduated from NIT - Calicut in the year 2000 in Electronics and Communications Engineering and thereafter he has successfully completed a one-year executive program in Business Management from IIM Calcutta.

       

      RAMESH SHANMUGHAM Co-founder & COO

      RAMESH SHANMUGHAM

      Co-founder & CRO

      As Co-founder and Chief Revenue Officer of Ignitarium, Ramesh has been responsible for global business and marketing as well as building trusted customer relationships upholding the company's core values.

      Ramesh has over 25 years of experience in the Semiconductor Industry covering all aspects of IC design. Prior to Ignitarium, Ramesh was a key member of the senior management team of the semiconductor division at Wipro Technologies. Ramesh has played key roles in Semiconductor Delivery and Pre-sales at a global level.

      Ramesh graduated in Electronics Engineering from Model Engineering College, Cochin, and has a Postgraduate degree in Microelectronics from BITS Pilani.