A KAIST team has featured a new technology, “Knocker”, which identifies objects and executes actions just by knocking on it with the smartphone. Software powered by machine learning of sounds, vibrations, and other reactions will perform the users’ directions.
What separates Knocker from existing technology is the sensor fusion of sound and motion. Previously, object identification used either computer vision technology with cameras or hardware such as RFID (Radio Frequency Identification) tags. These solutions all have their limitations. For computer vision technology, users need to take pictures of every item. Even worse, the technology will not work well in poor lighting situations. Using hardware leads to additional costs and labor burdens.
Knocker, on the other hand, can identify objects even in dark environments only with a smartphone, without requiring any specialized hardware or using a camera. Knocker utilizes the smartphone’s built-in sensors such as a microphone, an accelerometer, and a gyroscope to capture a unique set of responses generated when a smartphone is knocked against an object. Machine learning is used to analyze these responses and classify and identify objects.
The research team under Professor Sung-Ju Lee from the School of Computing confirmed the applicability of Knocker technology using 23 everyday objects such as books, laptop computers, water bottles, and bicycles. In noisy environments such as a busy café or on the side of a road, it achieved 83% identification accuracy. In a quiet indoor environment, the accuracy rose to 98%.
The team believes Knocker will open a new paradigm of object interaction. For instance, by knocking on an empty water bottle, a smartphone can automatically order new water bottles from a merchant app. When integrated with IoT devices, knocking on a bed’s headboard before going to sleep could turn off the lights and set an alarm. The team suggested and implemented 15 application cases in the paper, presented during the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2019) held in London last month.
Professor Sung-Ju Lee said, “This new technology does not require any specialized sensor or hardware. It simply uses the built-in sensors on smartphones and takes advantage of the power of machine learning. It’s a software solution that everyday smartphone users could immediately benefit from.” He continued, “This technology enables users to conveniently interact with their favorite objects.”
The research was supported in part by the Next-Generation Information Computing Development Program through the National Research Foundation of Korea funded by the Ministry of Science and ICT and an Institute for Information & Communications Technology Promotion (IITP) grant funded by the Ministry of Science and ICT.
< Research Group of Professor Insik Shin (center) > KAIST researchers have developed mobile software platform technology that allows a mobile application (app) to be executed simultaneously and more dynamically on multiple smart devices. Its high flexibility and broad applicability can help accelerate a shift from the current single-device paradigm to a multiple one, which enables users to utilize mobile apps in ways previously unthinkable. Recent trends in mobile and IoT tec
2019-07-20Sangeun Oh, a Ph.D. candidate in the School of Computing was selected as a Google PhD Fellow in 2017. He is one of 47 awardees of the Google PhD Fellowship in the world. The Google PhD Fellowship awards students showing outstanding performance in the field of computer science and related research. Since being established in 2009, the program has provided various benefits, including scholarships worth $10,000 USD and one-to-one research discussion with mentors from Google. His resear
2017-09-27Research team of Professor Dong-Soo Han of the School of Computing Intelligent Service Lab at KAIST developed a system for providing global indoor localization using Wi-Fi signals. The technology uses numerous smartphones to collect fingerprints of location data and label them automatically, significantly reducing the cost of constructing an indoor localization system while maintaining high accuracy. The method can be used in any building in the world, provided the floor plan is availa
2017-04-06Professor Sung-Ju Lee of the Department of Computer Science at KAIST has been appointed to serve as a technical program chair of IEEE INFOCOME. The computer communication conference, started in 1982, is influential in the research fields of the Internet, wireless, and data centers. Professor Lee is the first Korean to serve as a program chair. He has been acknowledged for his work in network communications. In the 34th conference, which will be held next year, he will take part in selecting 65
2015-07-02