Gesture recognition integrated into Internet of Things (IoT) systems is an emerging area of research with significant potential for various applications. This system primarily focuses on recognizing hand gestures to facilitate communication, especially for individuals with speech impairments. The proposed hand gesture recognition system employs sensors, such as flex sensors and accelerometers, to accurately capture hand movements. These sensors are connected to an IoT device, which processes the data and translates gestures into meaningful commands or text. The system is designed to be cost-effective, making it accessible for users who require assistive technologies. One notable application of this technology is in aiding communication for speech-impaired individuals. By converting recognized gestures into text or speech, the system enables users to interact more effectively with their environment and with others. The integration of machine learning algorithms enhances the accuracy and efficiency of gesture recognition, allowing for real-time processing and feedback. Overall, the hand gesture recognition system using IoT aims to improve accessibility and communication for differently-abled individuals, showcasing the potential of combining hardware and software solutions to address real-world challenges in human-computer interaction.