REAL TIME ENVIRONMENT MAPPING USING SENSOR AGGREGATION NETWORKS
Advent of computer vision and machine learning algorithms in the field of data science have encouraged development of intelligent systems incorporating simple hardware and software processing techniques and one such area of research is into virtualization of the physical environment using real time object detection and mapping techniques. The domain of object detection and classification is one that has a diverse variety of applications ranging from collision avoidance, virtual reality gaming, augmented reality, education, healthcare and so on. The purpose of this paper is to identify intelligent sensor systems and aggregations of object detection techniques, with the goal of understanding how each individual sensor works independently and as a subcomponent of a larger complex sensor aggregation system capable of generating a depth map of its surroundings. The research also tries to establish a critical list of applications that make use of sensor networks, as well as the complexity of constructing them.