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RFID Simulations for Faster, Smarter and Cost-Effective IoT
Internet of Things sensors and RFID tags offer accurate and valuable insights using real-time data analytics.
Feb 23, 2020—
Organizations are implementing Internet of Things (IoT) projects for many reasons—improved ROI, keeping up with digital transformation, innovation for competitive advantage and more. However, as they begin initiating these intricate applications involving multiple servers and sensors connected to the cloud, their initial concerns (determined in a recent study conducted by Altair and TDWI) of security, collecting real-time reliable data, hardware integration, cost and proving probable ROI often become challenging.
Radio frequency identification (RFID) technology, commonly used in manufacturing and supply chain logistics to track products, shipments and other assets, implemented with IoT applications, can solve these challenges for many use cases. For example, enabling data capture collected in real time, RFID can provide a more efficient and economical way to monitor assets when connected to the internet.
RFID and Simulation
RFID on its own delivers on many of these accounts. Whereas alternative IoT methods like barcodes would require an optical line of sight, RFID can read multiple tags at once to capture real-time data quickly and accurately. Add simulation and you up the ante even further. This increases efficiency by running through a vast number of scenarios before production begins, to speed up development and eliminate time usually spent on prototyping. With simulation, trial and error is minimized and the project is ultimately simplified before the pilot.
Take for instance, the case of a large tire manufacturer that uses RFID to track the lifecycle of its smart tires. Because tires receive a great deal of wear and tear, RFID tags can't be placed on the outside of tires, and if they're embedded within the tires, there is a risk of performance degradation. Electromagnetic simulations helped significantly reduce the time to production for the manufacturer by optimizing the RFID tag antenna design and location with fewer prototyping iterations.
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