Industrial Networks LLC (INet), a pioneer in industrial logistics systems, has officially announced the launch of Smart AEI Tag, which happens to mark the next evolution in AEI Tag technology for the rail industry.
According to certain reports, the new Smart AEI Tag is specifically designed to bring forth real-time tracking, comprehensive connectivity, and unmatched durability for railcar monitoring and management.
To understand the significance of such a development, we first need to acknowledge that, while legacy AEI Tag has been the standard for railcar tracking for over 30 years, it still seems to be overly reliant upon a much older technology. This technology on its part, has proven unable to participate in real-time tracking. Not just that, it also requires significant investment in infrastructure, equipment, and maintenance to implement or update. Owing to these very limitations, developing systems to accurately track railcars in real-time, both across the railyard and in transit, has been prohibitively expensive and labor intensive for all but the simplest of scenarios. In fact, even in those simplest of scenarios, the technology would provide you with nothing more than an information snapshot, which is out of date right on arrival.
Against that, the Smart AEI Tag (SAEI) system offers you a significantly more cost-effective solution, all while ensuring better efficiency, safety, and accuracy within a railyard, as well as across regional and national rail lines. More on the same would reveal how the Smart AEI tag will combine INet’s newly released SMRT technology, a technology capable of participating in a highly efficient, decentralized, massive, self-optimizing and self-healing BLE mesh network, with a decentralized, self-healing, private 5G NR+ network.
The technology in question will even come bearing legacy AEI chip for backwards compatibility to ensure a seamless transition between the current rail ecosystem and the new Smart Rail Ecosystem. For instance, when we talk in the railyard context, the technology will effectively leverage SMRTag™ mesh network to provide tracking of all railcars with sub-meter precision and the most accurate geo-location. On the other hand, once we move out of the railyard, Smart AEI Tag will switch to the SMRT Train mesh configuration which, by the way, allows for the SMRTags™ to communicate with each other, and at the same time, provide railroad the setup it requires to track railcars wherever they move.
As for when in-transit, each locomotive is expected to carry a SMRT Hub. This Hub will have the responsibility to receive transmissions from the Smart AEI Train mesh network and then relay that information to the company’s secure, highly available, distributed data centers. Upon receiving the stated information, these centers can provide the railroads with comprehensive live telemetry and sensor data.
“We are very pleased to be able to offer the rail industry these revolutionary Smart AEI Tags which offer significant improvements over the conventional AEI tag while simultaneously preserving existing rail infrastructures.” said Jimmy Finster, President of Industrial Networks. “We believe the new Smart AEI Tag has the potential to transform the rail industry.”
Despite the updated capabilities and features, the Smart AEI Tag will retain current industry-standard AEI Tag dimensions for a more seamless transition. Not just that, it will also, as in compliance with the wider industry benchmarks, integrate revolutionary applications that transform the older AEI technology from simple segmented point-in-time data into a real-time integrated IoT data ecosystem. By doing so, it will connect every part of the freight rail supply chain.
Among other things, we ought to mention how the Smart AEI Tags actually pack together a continually expanding list of integrations with various different sensors including, but not limited to, rail car health, collision detection, and rail car speed. Thanks to the given sensors, Smart AEI Tag system will be able to provide a complete, live, operational profile of every rail car that each customer requires, with the details covering complete status, current location, and estimated arrival time. This IoT information, when placed next to information from the customer, can be used for building AI models that will recommend best customer service and delivery strategies for the freight rail industry.
