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Java IoT Authors: Liz McMillan, Zakia Bouachraoui, Yeshim Deniz, Elizabeth White, Pat Romanski

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All Aboard the IoT Railway

Rail represents a major component of infrastructure

IoT Railway

In many parts of the world, rail represents a major component of infrastructure – for the transportation of both humans and goods. In fact, railways are critical to some of the major industries like oil and gas, agriculture, and food refrigeration/transport. Much like those industries have, over the years, adopted automated, machine-to-machine (M2M) technology, railroads have similarly deployed more advanced technology over the years as well.

Railways began the “automation” process by adding Automatic Equipment Identification (AEI) tags back as early as 1989. These sensors track the specific item tagged, but they have no way of knowing how the train is operating as a whole. Companies also began deploying RFID tags to track goods being transported along the different lines. The AEI sensors could provide information on the rail car and would interact with the various readers along the route. The additional sensors were great for location awareness, but still lacked the ability to monitor all the moving parts on the train. Still, with these two initial steps, the early stages of Internet of Things (IoT) technology began to come into focus for the railroad industry.

IoT Railway Solution

The rail industry needed a way to develop a more intelligent infrastructure that enabled Sensor-2-Server (S2S) data transmission via a network of Wi-Fi and voice, video, data and sensor control systems. Due to the massive amount of data collection a system like this would develop, railways are now developing a fully digital service that is directed toward centralized facilities capable of aggregating data from different sources and streams and analyzing that data in real-time. For instance, today, railroad sensors monitor everything from rail car and locomotive health, to track conditions, air temperatures, stress gauges and component conditions. Having a centralized system allows operators to take that data being collected  and use it to develop predictive maintenance practices; that is, the ability to predict when a section of rail or a specific component is in need of repair or near failure.

Predictive maintenance is only one component of IoT integration for the rail industry, but it is one that can potentially transform practices across the board, ultimately saving companies time and money – valuable elements for an industry centered on logistics.

Across the pond, the University of Huddersfield’s Institute of Railway Research has found that tracks can be monitored with inexpensive sensors set to operate by the vibrations of oncoming trains. According to the research, the sensors will still operate if one of the sensors is damaged, because of a built-in fail-safe. These sensors are projected to detect both approaching trains and the real-time conditions of the track.

Adding an IoT network to trains can help improve safety and efficiency with traffic congestion, monitoring and control speed. Even the non-critical business operations have the ability to operate efficiently on the train with the help of modern sensors.

Beyond rail sensor networks, there is also the consideration of the passengers as well. If railroads can implement Wi-Fi networks on passenger cars, passengers will be able to receive travel updates, railroad companies can develop specific apps for their travelers, and riders can enjoy the utility of internet in areas that previously lacked service.

Although rail remains largely an industrial consideration in the United States, the growth of IoT technology available to the greater industry bodes well for the continued development of this infrastructure around the world.

More Stories By Scott Allen

Scott is an executive leader with more than 25 years of experience in product lifecycle management, product marketing, business development, and technology deployment. He offers a unique blend of start-up aggressiveness and established company executive leadership, with expertise in product delivery, demand generation, and global market expansion. As CMO of FreeWave, Scott is responsible for product life cycle/management, GTM execution, demand generation, and brand creation/expansion strategies.

Prior to joining FreeWave, Scott held executive management positions at Fluke Networks (a Danaher Company), Network Associates (McAfee), and several start-ups including Mazu Networks and NEXVU Business Solutions. Scott earned his BA in Computer Information Systems from Weber University.

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