Intelligent Trains: Reality or Just Software Development Case Studies?
Artificial intelligence (AI) has been around since the 1950s, but now has AI reached the point of maturity where it might become a regular tool in the rail business? Take a look at how AI is currently being used in the rail industry and what wider adoption may imply for the future.
Is AI merely a craze, or does the industry need to grow to adopt these game-changing technologies?
The Fourth Industrial Revolution is driving computers on new dimensions and becoming more integrated into people’s daily lives.
Letters and digits are interpreted from sounds, pictures, and videos.
The problem of data overload — is clearer than ever.
The rail industry is no exception as consumers adjust to the digitization of retail and other sectors. The digitalization of the railway sector must go hand in hand with the world’s huge revolution in industry processes owing to new breakthroughs in modern technology instead of being in software development case studies.
Although artificial intelligence is still in its early stages, it is gaining ground in the public transportation industry. According to an online poll done by UITP AP CTE in early 2018, which received responses from 48 public transportation organizations for, 62% of organizations were either utilizing or exploring the case study on application software with AI-powered solutions. As mentioned previously, from the 17 use-cases gathered, UITP discovered that they all shared a common philosophy: the use of AI technologies is primarily to improve the quality and efficiency of tasks performed by employees, rather than to reduce or replace staff; this debunks the myth that AI will take over the future workforce.
Society has entered the artificial intelligence (AI) era
AI in public transportation is one of the most important options for unlocking the potential of data to enhance the quality and efficiency of public transportation, particularly in railroad business case in software engineering.
Industry 4.0 technologies have been widely implemented in the railway industry, concentrating mostly on maintenance and control duties required in railway infrastructure, due to its high potential. The scientific community has come to employ these technologies in a variety of ways to tackle a variety of challenges, including train breakdowns, railway station security, rail system control, and communication in difficult-to-reach locations, among others.
The railway sector is one of the most important industries in terms of economic development and commuting in countries. The application of emerging technologies in industry processes, such as Artificial Intelligence (AI), the Internet of Things (IoT), and Cloud Computing, has the potential to alter productivity and employment as discussed by researchers on software development case studies.
As a result, the railway industry has changed dramatically.
The Fourth Industrial Revolution, which is characterized by the blending of physical and digital sophisticated technologies which promotes the expansion of seamless automation and infinite connection with software project management case studies and answers. The notion of seamless mobility and efficient interconnection is becoming a reality because of breakthroughs in digital technologies such as artificial intelligence (AI), big data analytics, the Internet of Things (IoT), and blockchain.
Sadly, it is said that rail traffic has doubled worldwide by 2020, providing a challenge for both train operators and commuters.
So, how can operators deal with complex, aging infrastructure, and technology to keep up with changing industry dynamics? How can they improve maintenance processes to guarantee that trains run on schedule every time?
What Does Artificial Intelligence Signify for the Rail Industry?
Although artificial intelligence is still in its infancy, it is gaining ground in the public transportation industry. With the 17 use-cases gathered, UITP discovered that they all shared a common philosophy: the use of AI technologies is primarily to improve the quality and efficiency of tasks performed by employees, rather than to reduce or replace staff.
This debunks the myth that AI will take over the future workforce, as suggested by many software project case study examples.
Any technology that helps enhance customer experience, reduce operational delays, and keep trains running is well worth investigating in the rail sector.
Artificial intelligence may be applied in a number of ways as the industry creates more data than ever before for business cases in software engineering through smart sensors and applications:
- Delay-Time Prediction
- Cloud Computing
- Operational Intelligence
- Biometrics
- Intelligent Signaling Systems
Furthermore, AI-powered video analytics play an important role in increasing the capabilities of railroads’ predictive maintenance or condition-based maintenance, and security management.
AI can assist in the optimization of complicated railway systems to recognize, rethink, and reorganize itself
To combat train delays and optimize train scheduling in their separate complicated and crowded railway networks, urban railway operators are looking into creative solutions that employ neural networks and deep reinforcement learning (AI applications).
Additionally, to better estimate mobility demand and train management. Passengers’ expectations are moving as a result of the advancement of digitalization and the sharing economy, from traditional set timetables to agile, on-demand, and informational public transportation systems.
What is the present situation?
While computer control of railway networks is now taken for granted, BJIT’s history as a developer of Platform Application is regarded as a very important and helpful application for automatically saving energy, as well as for reducing the number of accidents and errors, increasing productivity, and lowering infrastructure costs.
Over the previous two decades, BJIT has continued to benefit from advancements in computer functionality and performance with cutting-edge technology, along with image processing-based solutions that run in real-time at low cost.
BJIT takes pride in its track record of creating safe, dependable, and pleasant Platform Application deployed in multiple railway platforms in Japan through deep learning-based solutions that can be improved over time.
The future of AI in railways
It is apparent that AI systems have the potential to be strong and capable of addressing the fundamental difficulties that railways face today. Experts are also recruited for further studies on software development case studies for future concepts of AI-driven solutions that have the potential to revolutionize the industry.
However, AI is not a panacea and, like any other technology, has limitations. The cornerstone of any AI system is data — quality, quantity, integrity, and legality are all crucial considerations. Humans also play a crucial role in realizing the benefits that AI solutions offer.
The rail industry is in an exciting period
Artificial intelligence will increase safety, reduce delays, save money, and improve customer service. However, in the future, the sector will also need to discover efficient power options. Get in contact with BJIT today to discuss how we can assist you with digitalization.
