![]() ![]() If the technology gains traction, real-time analytics should be possible at anytime, anywhere. The team–led by Romit Roy Choudhury, an associate professor of electrical and computer engineering and computer science at Illinois, jointly with Sharon Yang from Intel–has developed advanced motion tracking algorithms from the various incomplete and noisy measurements of inertial measurement unit (IMU) sensors and wireless radios, fitted inside a ball and players’ shoes. ![]() It’s only accessible to big clubs,” says Mahanth Gowda, a PhD candidate in computer science and lead author of the study, “Bringing IoT to Sports Analytics.” “We want to cut down the expense significantly by replacing cameras with inexpensive internet-of-things devices (costing less than $100 in total) to make it possible for many other organizations to use the technology.” “There’s a lot of interest in analyzing sports data though high-speed cameras, but a system can cost up to $1 million to implement and maintain. In an effort to make big data analytics more accessible for the sports industry, researchers from the University of Illinois at Urbana-Champaign have utilized IoT devices–low-cost sensors and radios–that can be embedded into sports equipment (e.g., balls, rackets, and shoes), as well as in wearable devices. Data for these analytics is currently sourced through cameras in stadiums and courts and is incredibly expensive to acquire. Sports analytics–tracking how fast the ball is moving or how players move across the field–is becoming a key component of how coaches make decisions and fans view games. ![]() They employ inferencing algorithms that can track movement to within a few centimeters, and accurately characterize 3-D ball motion, such as trajectory, orientation, and revolutions per second. The sensors are wrapped in a protective case and embedded in a cricket ball. ![]()
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