Movement detection and object recognition provide various applications to improve our lives. Recently, Professor Dina Katabi’s group created the sensor-generating wireless signal that can pass through a wall, allowing us to locate people and detect their movements within their homes. Some of its applications include monitoring the elderly, detecting falls, analyzing heartbeats for health issues, and remotely controlling lights, among others. However, there are two main problems: fictitious human detection caused by wall reflection, and time-consuming setup caused by manually measuring and drawing floor plans. The goals of my SuperUROP project are to detect the walls and differentiate between signals from real humans and those from wall reflection, and to automate the generation of floor plans using the sensor’s data.

I am participating in this SuperUROP project because I like its innovative ideas about using wireless signals to detect people’ s movement and differentiate objects. Moreover, I am very interested in computer vision after taking Advances in Computer Vision (6.869) last year. I want to develop my knowledge and research-level skills. I would like to publish a paper and come up with some additional useful applications from this SuperUROP project.