Low-Cost Sensitive Cricket LED stump Design and It’s Implementation Using Deep Learning

This research proposes a low-cost, sensitive cricket LED stump design to address the high costs and accessibility issues of current methods in professional cricket. The system uses a Raspberry Pi Zero 2 W and a deep learning model built on IMU sensor data to activate an LED indicator based on real-time data processing. Current methods are expensive and complex, making them unsuitable for mass usage. To overcome these challenges, the proposed method uses sophisticated machine-learning techniques and affordable technology. A hybrid deep learning model combines convolutional layers and Long Short-Term Memory (LSTM) networks to optimize temporal and spatial data characteristics. The Raspberry Pi Zero 2 W interface ensures effective real-time execution and short inference times. The proposed approach achieves a 97.94% testing accuracy, making it a suitable substitute for more general cricket applications. This approach could lead to more people having access to high-precision detecting systems in the game.