Presentations often require seamless interaction with digital slides, yet traditional methods such as handheld remotes limit presenter mobility and reduce engagement of the listener. These limitations are present in environments where flexibility and easier control are crucial elements, such as classrooms, meetings, and public speaking events. To address these challenges, we propose the Real-Time IoT Based Gesture-Driven Interface for Presentations, a wearable gesture-controlled based idea integrated into a wristband. The system implements both a baseline rule-based gesture recognition method and a machine learning- based approach, allowing a comparison of accuracy and latency between the two methods. Hand movements are processed by a microcontroller and transmitted wirelessly to a cloud platform, which triggers slide transitions through serverside keyboard events. A built-in push button enables gesture activation, while a toggle switch provides multiple data transmission modes via Bluetooth and WiFi. Experimental results show that the Machine learning-based system improves recognition accuracy and reduces latency compared to the baseline method, providing presenters with enhanced mobility and more precise control.