Application of Deep neural network for an Effective user experience in an interactive platform

The technical community is becoming more concerned with the interface between humans and machines to increase the capability of the real device to fulfill the user's expectations and improve the interpretation of human control as accurately as possible. Intelligent systems that can mold themselves to their users' characteristics need dedicated research and development. A user-controlled, interactive robot visualizer that actively searches for and brings the viewer an item they choose. As a result, this study aims to present a Deep neural network-based interactive platform (DNNIP) to enhance understanding concerning the thinking of the end user. A deep neural network (DNN) and particle filtering may estimate the user location. The robot will first use location data to navigate the user's area, then face recognition to provide service at the user's location. The artificial bee colony (ABC) algorithm is a famous meta-heuristic optimization method based on how honeybees find sustenance. ABC is great at exploring low manipulation ability, low response, and high accuracy in robot interaction. Consequently, the experiments' findings demonstrate that the suggested model is a smart, more effective, and more reliable tool than conventional communication techniques.