This study uses chess as a starting point and employs a magnetic reed switch array to detect the position of chess pieces. Diodes are incorporated into the design to prevent ghosting effects, finally, Arduino UNO is used as the controller of the smart chessboard. The chessboard is equipped with RGB LED lights at the bottom to provide move prompts for users, displaying different lighting based on the type of move made. 　　Through a simple design and efficient computational performance, we successfully created a smart chessboard capable of recognizing player moves and providing correct move suggestions according to international chess rules. This allows complete beginners to learn and master all chess rules during gameplay. Additionally, with a lightweight AI which is based on the Minimax algorithm and an AI using Efficiently Updatable Neural Networks (NNUE) we explored the performance differences between the two. This enables the smart chessboard to offer a certain level of playing strength without being connected to a computer, while conserving computational resources, thus supporting players to improve their skill.