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This study aims to develop an intuitive and efficient smart home control system by utilizing hand tracking and speech recognition technologies. These technologies employ the OpenCV, Mediapipe, PyAudio, and Speech Recognition libraries to recognize hand gestures and voice commands in real-time. The system is developed using a Raspberry Pi connected to a webcam and microphone as input devices, and a relay to control electronic appliances. The results show a high accuracy rate at optimal light intensity for hand tracking and a specific distance for speech recognition. This system is implemented in an IoT environment to control devices such as lights and door locks. The research is expected to contribute to the development of smarter and more user-friendly smart homes.

The development of technology with digital image processing is often utilized to solve various problems in image processing, such as facial recognition, object detection, and interaction between users. In this study, we developed an interactive hand gesture-based game titled "Slap Mosquito" that utilizes image processing techniques to control the game through hand gestures. Using Rapid Application Development (RAD), Python, OpenCV, and Pygame methodologies, this game allows users to slap mosquitoes virtually in real-time through hand gesture recognition that is read by the camera and translated into in-game actions. RAD allows rapid development iterations and improvements based on user feedback, which is essential for improving system responsiveness and accuracy. This study focuses on detection precision, system responsiveness, and the impact of lighting on game performance, as measured using frames per second (FPS) and user gameplay results. The test results show that optimal lighting meets high detection accuracy, while low lighting conditions have a negative impact on accuracy and responsiveness. The results of this study provide insights for further development of gesture-based applications, especially regarding the importance of optimizing technical parameters and RAD methodology in improving user experience.    

The purpose of this study is to explain and describe the movement structure of Sayak Dance in Air Batu Village, Ranah Pemberap District, Merangin Regency, Jambi Province. This type of research is qualitative research with descriptive methods. Research instruments are researchers themselves and assisted by supporting instruments such as stationery and cameras. Data was collected through observation, interviews, and documentation. The steps of analyzing data are data collection, data reduction, data presentation and conclusions. The results showed that the relationship of basic elements, Sayak Dance has basic elements related to the attitude of the movement of body parts, starting from the head, body, hands, feet. The attitudes and movements contained in the Sayak Dance consist of: 1) attitudes and movements seen in a) the attitude of the head is upright, upright motion on the head does not exist. 2) Posture and gestures are seen in: a) upright, upright and leaning forward posture b) Motion on the body is absent 3) Posture and hand gestures are seen in: a) attitude on the hand lift sambah b) motion on the hand open straight sambah, open right sambah, pat me up, pat the right side of the leaf, pat the bottom slap, pat the back 4) attitude and motion on the feet seen in: a) attitude of the right foot, squat, middle stance, right lift, lift left, and bend. The grammatical hierarchical relationship system contained in Sayak Dance consists of 15 motifs, 8 phrases, 4 sentences and 1 cluster. Sayak dance includes syntagmatic relationships, relationships that are like links that cannot be separated or exchanged between the sati and others.

The innovation of the robot cars today is moving very fast. The robot car is capable of being driven without using manual remote controls. One form of technological development in robot car control is by using hand gestures. The microcontrolle placed in the palm of the hand will read the direction of movement of our hands, then the instructions are transmitted to the robot car.  The transmission system used in the microcontrolled circuit in the palm of the hand and the receiver circuit inside the robot car must be properly attached. This is influenced by the quality of programming language levels and the arduino mini pro and MPU-6050 circuits. Hand gesture directional readings are able to be easily readable and directly transmitted by the NRF24L01 module via radio waves. The response power of the robot car in receiving hand-move instructions can be received as far as 45 m. In addition to using a good arduino mini pro, the addition of antenna modules will also increase the quality and distance of the connection is getting farther..