ABSTRACT
Range-based gesture systems are attracting researchers for developing a single-point control system for IoT devices using edge-fog computing. Single-point control system is an emerging field for fulfilling the requirements of smart home. Most of the previous work usage extra sensors, wearable devices, or additional resources with a higher network connectivity to cloud will be the reason for increasing cost and latency. This chapter presents a hand gesture-based recognition system that uses the camera and microphone of an edge device to recognize gesture and voice commands of users for selecting the function of consumer device, and again the camera of an edge device is used to set the range of that function. All these computations are done on fog devices (laptop). A higher recognition accuracy, i.e., about 70%, is achieved by using an open-source computer vision library (Open CV) and machine learning algorithm CNN, which mainly focuses on real-time image processing and computer vision. Pyttsx3 and speech recognition are Python packages that are used for speech recognition.
