Current Experience
Solution support engineer
- Efftronics system's Pvt Ltd
- Jan 2021 – Jul 2022
- 1 yr 6 mos
Highest Level Of Education
Ramachandra college of engineering in Eluru (JNTUK University)
- Bachelor of technology
- Jun 2016 - Oct 2020
About Me
To work in an organisation where I can use my abilities as well as learn new skills while contributing to the growth of the organization.
Experience
Efftronics system's Pvt Ltd
1 yr 6 mos
Solution support engineer
Full-time
Jan 2021 - Jul 2022
Roles & Responsibilities ... Read more
Analog & Digital validation activities, Network Handling, Front End Processor (FEP) & Failure Analysis System (FAS) works, Complete actual commissioning of the project with the customer, Execution of AMC.
EDFC CP-203R
Working as "site incharge" at EDFC CP-203R project under EFFTRONICS SYSTEM'S PVT LTD along with SIEMENS and L&T.
- Preparation of primarily and detail design document for PMC approval.
- Strong knowledge on railway signalling domain principles.
- Project planning for executive.
- Meeting with PMC and Siemens representatives.
Installation and Testing commissioning.
- Data logger's
- RTU (Remote Terminal Unit).
- FEP (Front End Processor).
- PHMU (Point Health Monitoring Unit).
- SHMU (Signal Health Monitoring Unit).
- BHMU (Battery Health Monitoring Unit).
- PVDU (Point Voltage Detection Unit).
Education
Ramachandra college of engineering in Eluru (JNTUK University)
4 yrs 4 mos
Bachelor of technology
Jun 2016 - Oct 2020
Vignan junior college
1 yr 10 mos
Intermediate
Jun 2013 - Apr 2015
Vignan concept High school
11 mos
Secondary school
Jun 2012 - May 2013Certifications | Licence
Basics of Artificial intelligence
07 July, 2021
Foundations of Artificial intelligence
13 June, 2021
Preparation of TOC
29 October, 2022
Patents | Awards and recognitions | Memberships
Patents or Awards not yet added
Skills
Preparation of SIP.
(signal interlocking plan)
Preparation of TOC.
( table of control )
Basic knowledge on ERTMS.
( European Rail Traffic Management System )
Basic knowledge on CBTC.
( Communication Based Train Control )
Designing of SIP in AUTO CAD.
( Computer-Aided Design ).
Designing of SIP in MICROSTATIONS.
Language Proficiency
Telugu
Native or Billingual
English
Professional Working
Hindi
Professional Working
- Posted 2 years ago
Artificial Intelligence In Railway
Introduction Railway signaling is the process of controlling train movements to ensure safety, efficiency, and punctuality. The traditional railway signaling system is based on physical signals, such as colored lights and semaphore arms, which are placed alongside the track to communicate with the train driver. However, with the advent of modern technology, there has been a shift towards automated signaling systems that use artificial intelligence (AI) to improve safety and efficiency. In this article, we will explore the application of AI in railway signaling, its benefits and challenges, and the future of AI in this field. Benefits of AI in Railway Signaling Improved Safety AI can play a crucial role in improving safety in railway signaling. By using sensors and cameras, AI can detect obstacles on the track, such as fallen trees, animals, or even people, and alert the driver or activate the emergency brakes. AI can also monitor the speed and position of trains to prevent collisions and derailments. Enhanced Efficiency AI can optimize train schedules and routing, resulting in reduced waiting times and improved punctuality. AI can also monitor and control the speed and acceleration of trains, leading to energy savings and reduced wear and tear on equipment. Predictive Maintenance Predictive maintenance is another application of AI in railway signaling. AI systems can analyze data from sensors and other sources to predict equipment failures and recommend maintenance actions. This approach can reduce downtime, improve reliability, and extend the life of equipment.AI can help predict equipment failures and recommend maintenance actions, resulting in reduced downtime and improved reliability. By analyzing data from sensors and other sources, AI can detect potential issues before they become critical and schedule maintenance proactively. Challenges of AI in Railway Signaling Integration with Legacy Systems The integration of AI systems with existing railway signaling infrastructure can be challenging due to the complexity and heterogeneity of legacy systems. Compatibility issues, data formats, and communication protocols are some of the challenges that need to be addressed to ensure seamless integration. Reliability and Safety AI systems must be highly reliable and safe, given the critical nature of railway signaling. Any failure or malfunction can have severe consequences, including loss of life and property damage. Ensuring the reliability and safety of AI systems requires rigorous testing, validation, and certification procedures. Data Quality and Privacy AI systems depend on high-quality data to function correctly. However, data quality can be compromised due to various factors, such as sensor malfunction, environmental factors, or human error. Additionally, AI systems must adhere to strict data privacy regulations to protect sensitive information, such as train schedules and passenger data. Integration of AI The integration of AI in railway signaling systems is not without its challenges. Legacy infrastructure and compatibility issues can pose significant obstacles to the implementation of AI systems. Data formats and communication protocols vary between different signaling systems, which can hinder data sharing and interoperability. In addition, ensuring the reliability and safety of AI systems requires rigorous testing, validation, and certification procedures. Data quality can also be compromised due to various factors, such as sensor malfunction, environmental factors, or human error. Furthermore, AI systems must adhere to strict data privacy regulations to protect sensitive information, such as train schedules and passenger data. Examples of AI in Railway Signaling Autonomous Trains Autonomous trains are a significant application of AI in railway signaling. These trains use AI algorithms to control their speed, acceleration, and braking, allowing them to operate without human intervention. Autonomous trains offer several benefits, such as improved safety, reduced operating costs, and increased capacity. Traffic Management Traffic management is another area where AI can be applied in railway signaling. AI algorithms can optimize train schedules and routing to reduce waiting times, improve punctuality, and increase capacity. AI can also monitor and control the speed and acceleration of trains, leading to energy savings and reduced wear and tear on equipment. Real-time Monitoring Real-time monitoring of trains and track conditions is another application of AI in railway signaling. AI algorithms can analyze data from sensors and cameras to detect obstacles on the track, such as fallen trees or animals, and alert the driver or activate the emergency brakes. AI can also monitor train speeds and positions to prevent collisions and derailments. The Future of AI in Railway Signaling The future of AI in railway signaling is promising, with advancements in machine learning, deep learning, and other AI technologies. AI has the potential to revolutionize railway signaling by improving safety, enhancing efficiency, and reducing maintenance costs. However, to realize these benefits, railway operators must overcome the challenges of integrating AI systems with legacy infrastructure, ensuring the reliability and safety of AI systems, and maintaining data quality and privacy. Conclusion In conclusion, the adoption of AI in railway signaling systems offers significant benefits, such as improved safety, enhanced efficiency, and predictive maintenance. AI systems can use sensors and cameras to detect obstacles on the track, monitor train speeds and positions, optimize train schedules and routing, and predict equipment failures. However, railway operators must overcome the challenges of integrating AI systems with legacy infrastructure, ensuring the reliability and safety of AI systems, and maintaining data quality and privacy. The future of AI in railway signaling is promising, with advancements in machine learning, deep learning, and other AI technologies.
Read Full Article- Posted 9 months ago
Introducing 5G Technology
Introduction: The integration of 5G technology into railway signalling systems represents a significant leap forward in the realm of rail transportation. With its unparalleled speed, reliability, and connectivity, 5G has the potential to revolutionize how trains are controlled, monitored, and managed, ultimately leading to safer, more efficient railway operations. Addressing Traditional Challenges: Traditional railway signalling systems have long grappled with challenges such as limited capacity, latency issues, and the need for extensive infrastructure. By harnessing the power of 5G technology, these challenges can be effectively addressed, ushering in a new era of innovation and progress in railway signalling. Advantages of 5G Technology: The introduction of 5G technology brings several key advantages to railway signalling: 1.Ultra-Fast Speeds: 5G networks offer blazing-fast data speeds, enabling real-time communication and decision-making between trains and control centers. 2. Low Latency: With ultra-low latency capabilities, 5G ensures near-instantaneous response times, critical for ensuring the safety and efficiency of train operations. 3. Massive Connectivity: 5G supports a vast number of connected devices and sensors, facilitating seamless communication and data exchange across the railway network. 4. Flexibility and Scalability: Unlike traditional signalling systems, which rely on fixed infrastructure, 5G-based solutions are highly flexible and scalable, adapting to evolving operational requirements with ease. Applications of 5G in Railway Signalling: The integration of 5G technology opens up a myriad of applications in railway signalling, including: 1. Communication-Based Train Control (CBTC): 5G enables the deployment of CBTC systems, which provide precise train positioning, automatic train operation, and dynamic traffic management, leading to increased capacity and safety. 2. Remote Monitoring and Maintenance: 5G-powered sensors and IoT devices facilitate remote monitoring of track conditions, equipment health, and train performance, enabling predictive maintenance and reducing downtime. 3. Enhanced Passenger Experience: With onboard 5G connectivity, passengers can enjoy high-speed internet access, multimedia streaming, and real-time information updates, enhancing their overall travel experience. 4. Augmented Reality (AR) for Maintenance: Maintenance technicians can leverage AR-based applications powered by 5G to access digital manuals, overlay maintenance instructions on physical equipment, and troubleshoot issues more efficiently. Conclusion: The introduction of 5G technology in railway signalling marks a significant milestone in the evolution of rail transportation. By leveraging the speed, reliability, and connectivity of 5G networks, railway operators can enhance safety, capacity, and passenger experience while driving operational excellence and cost-effectiveness. As the global rail industry embraces the opportunities presented by 5G, it is poised to unlock the full potential of next-generation signalling systems and shape the future of rail transportation worldwide.
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