Smart Rail … how disruptive technologies are transforming rail travel

July 8, 2018

The global railway tech market is expected to reach an annual value of 185 billion Euro.

Railways are often thought to see little change, yet the rail industry has always been a frontier in technology advances and mobility. With the digitalization, however, change in the industry has moved up a gear. Emerging startups bring new possibilities to the table; possibilities that shorten the timeline of innovation thus shaking up the entire industry. The global market volume for railway technology is expected to grow at a compound annual growth rate of 2.6% to reach an average annual value of 185 billion Euros between 2019 and 2021. Startups and their technologies dramatically contribute to this process as they are the forerunner of innovation. StartUs Insights analyzed 500+ companies and their innovations, and this is what they found:

Automatic Train Control (ATC)

Automatic train operation entails trains loaded with sensors, GPS data, cameras, and computer systems that have enormous potential to become the most efficient means of transportation in the near future. Though these trains are still linked to the control room, signals from GPS satellites accompanied with the data collected from sensors and cameras help trains process data in real-time, allowing them to make decisions according to various scenarios. ATC will, therefore, enable trains to understand and maneuver around obstacles as well as avoid any possibility of collision.

Israeli RailVision develops Automated Early Warning System (AEWS). This system provides an alarm for any suspicious interfering object with a preliminary classification of any object nature. Presented to the driver as a visual image on the board monitor, this information will be used for additional exploration of the obstacle ahead.

Internet of Trains

The Internet of Things (IoT) already led to various improvements in the railroad industry among which are smart ticketing, rail analytics, dynamic route scheduling as well as train and capacity planning. The application for the Internet of Trains, however, goes much further. It enables rolling stocks, signals, rails, and stations to work cooperatively through the use of intelligent onboard devices. Monitors that are connected to cloud-based applications capture and storage vital data in real-time. As a result, operators are skilled to analyze this information and optimize schedules as well as passenger comfort, to name only two application areas.

Perpetuum improves the efficiency, safety, and quality of fleet management and services through wireless condition monitoring. The startup directly delivers data on assets to improve end-user experience and plan ahead to make rolling stock available to meet customer demands, maximising the overall safety and efficiency.

Predictive Maintenance

Real-time information gathering and monitoring lead to cost reduction as well as improved efficiency and safety, which are only a few reasons predictive maintenance is implemented increasingly throughout the rail industry. Sensors along with monitoring software provide information of bearings, wheels, and bogies. The continuous inspection and diagnosis support operators in intervening quickly to patch up or replace equipment. What is more, operators can not only react to malfunctions but also anticipate potential failure and act before it occurs. Minimising interruption, promoting safety and avoiding costly delays are all benefits that come with predictive maintenance.

The software developed by Dutch Semiotic Labs predicts technical failures. The startup’s solution supplies instructions in the form of algorithms to convert data into information about when and why a system fails. Using this information, operators are able to take to prevent or to solve problems.

Artificial Intelligence (AI)

Artificial intelligence acts as an enabler for many innovations in the rail industry, such as the development of robotics, which in the near future will perform all sorts of maintenance and repair works on railways. Moreover, AI technology is used to develop fully autonomous systems applicable to build autonomous trains along with smart infrastructure components allowing for interconnected trains capable of communicating with each other. Other use cases for AI in the rail industry are intelligent language processing chatbots and the establishment of a connected system that notifies the train where it has to stop based on the customer’s ticket purchase.

Neuron soundware works with artificial intelligence to detect malfunctioning machines using audio signals. The pre-processing of the input data via a complex physical sensor model allows the neural network to recognize and identify important features with high confidence. The Czech company focuses on the early detection of mechanical malfunctions and offers predictive maintenance, real-time mechanical issue detection, and remote equipment diagnosis.

Smart Sensors

Next-Generation trains today are already fitted with hundreds of sensors, allowing engineers to remotely monitor the health of trains without the need to pull them off service. Now, smart sensors are used to decrease failure rate and enhance the reliability of trains, tracks, and signals. Moreover, these sensors present actionable data that predicts the failure of heating or A/C as well as damage to overhead lines and generates alerts about this equipment’s need for treatment.

Italian IVM develops monitoring systems based on systems of integrated sensors. The startup has vast experience in MEMS (Micro-Electro-Mechanical System) technology accelerometer sensors; hardware and software design as well as the implementation of low-power wireless networks for acquisition systems of accelerometric signals; and the extraction of information-diagnostic content from the data acquired by the monitoring systems through the use of specific processing algorithms.

Big Data

In railway operations and maintenance (O&M), big data plays a significant role. Its use equips companies with the necessary data to perform predictive analytics thus pave the way for advanced analysis and better decision making. The employment of advanced data analysis tools leads to critically improved performance and safety measures in railway systems while it also enhances the data-driven railway transportation system design, planning, operation, and management.

One example for a startup supporting companies in this regard is Delphisonic. The Turkish company supplies big data analytics equipment to carry out measurement and real-time condition monitoring tasks efficiently and securely. The solution, called Real-Time Railway Condition Monitoring, remotely monitors facilities in real-time and detects abnormalities which operators can immediately handle.

Cloud Computing

As we have already established, today’s trains run on a number of applications that all generate a vast amount of data. The storage of this data along with the accurate presentation analysis of it is a challenge to the rail industry. Cloud-based technology grants the storage of data collected in real-time while simultaneously providing absolute accessibility and saving substantial cost. Furthermore, cloud services can easily connect to other software for the analysis of collected data and provide operators with all necessary information to make a decision.

Nexiot develops cloud solutions for smart freight rail sensors. The Swiss startup’s servers and databases provide a secure undistributed repository for rapid access and big data analytics. Their cloud infrastructure is tailor-made and provides all things required to connect assets, including device management tools to Nexiot’s smart sensor as well as other IP based third-party devices through standard interfaces.

Drones

Drone technology is expected to have a significant impact on the rail industry as they are used for infrastructure monitoring, capable of collecting detailed data in remote and difficult to access areas. Making use of drones significantly reduces the risk, time, and cost of accessing these areas with the workforce. Furthermore, the gathered data such as visual, thermal, and multispectral data, allow for intelligent management thus increasing the resilience and lifespan of an asset.

RailPod’s aim is to make global rail infrastructure safer and more cost effective to maintain, operate and monitor through the use of automated ‘inspection’ drones. The startup’s drones increase the frequency and quality of day-to-day railroad track inspections through advanced sensing technologies and data as a service (DaaS).

Biometric Ticketing

Biometric ticketing includes facial and fingerprint scans, voice verification, retina, and vein scans, among other possibilities. It is expected that passengers soon will pay using their fingerprint or eye scan. The technology uses infrared lights flashing at a rapid pace to help a camera secure the shape, texture, and orientation of a body part in immense detail. Biometric ticketing is believed to solve the overcrowding issues train stations across Europe face on a daily basis as the recognition technology can end railway ticket barriers and the associated rush-hour queues.

Customer Clever strengthens the development of facial recognition technology. The UK-based startup’s solution is smart enough to recognize people who are wearing glasses and cannot be tricked by a photograph, owing to its 3D scanning capabilities. The startup also claims their system is capable of telling apart identical twins.

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