Novel Identification Tech Featured Pattern: P1447 January 2020
Abstracts in this Pattern:
Most existing object-recognition systems rely on visual data and machine learning to identify what a camera is looking at. However, visual data have a variety of drawbacks, including that they lack information about texture, softness, and weight distribution—information that is vital for enabling robots to handle everyday objects effectively. Researchers at the Korea Advanced Institute of Science and Technology (KAIST; Daejeon, South Korea) have developed machine-learning software that can identify an object without the use of visual data or special hardware. The Knocker (https://nmsl.kaist.ac.kr/projects/knocker) software requires users to tap an object with a smartphone and then uses data from the smartphone's sensors—including accelerometers, gyroscopes, and microphones—to classify and identify the object.
Wearable technology can provide substantial information about objects and activities. For example, researchers at the Carnegie Mellon University (CMU; Pittsburgh, Pennsylvania) Human-Computer Interaction Institute are using data from the sensors in smartwatches to identify what wearers are doing with their hands. The researchers made a few alterations to a smartwatch's operating system, enabling the use of accelerometer data and even bioacoustic sounds to distinguish among 25 common activities, including petting an animal, pouring a drink, typing, and washing dishes. The researchers report that their method is 95% accurate if the smartwatch is on the wearer's dominant arm. And researchers at the Massachusetts Institute of Technology (MIT; Cambridge, Massachusetts) have developed a sensor-enabled glove that provides object-related information. The glove uses a force-sensitive film on its palm and fingers and a network of conductive silver threads to "detect the weight and shape of an object its wearer is holding, as well as the pressure created as the hand moves." Data from the sensors pass to a neural network that finds patterns to identify, for example, whether an object has edges or is spherical.
Further advances in object recognition are important for numerous applications, including dexterous robots and a variety of health-care and assistive technologies. Such advances will also benefit wearable devices by enabling them to determine with a high degree of accuracy what wearers are doing.
The Development of this Pattern
Data Points
- SC-2019-12-04-104
Researchers at the Korea Advanced Institute of Science and Technology have developed machine-learning software that can identify an object without the use of visual data or special hardware. - SC-2019-12-04-050
Researchers at the Carnegie Mellon University Human-Computer Interaction Institute are using data from the sensors in smartwatches to identify what wearers are doing with their hands. - SC-2019-12-04-004
Researchers at the Massachusetts Institute of Technology have developed a sensor-enabled glove that provides object-related information.
Implications
P1447 — Novel Identification Tech
Advances in neural networks and sensors can enable a variety of devices to identify objects and activities.
Previous Alerts
- SoC088 — Sensor Synergies (February 2005)
The practice of tapping synergies among various sensor systems will soon become standard procedure for reducing costs and optimizing the benefits of sometimes expensive sensors. - SoC560 — Rise of Machine Vision (January 2012)
Machine vision can provide a deep and comprehensive understanding of the environment that vastly outstrips what a biological visual system can provide. - P0428 — Visual-Identification Software (December 2012)
Machine-vision software is enabling new consumer applications that can identify everyday objects. - SoC750 — Photos: More Than Meets the Eye (September 2014)
Photo-analysis applications will have multiple benefits for consumers and society, but they will also present several threats to privacy. - SoC811 — Visionary AI (July 2015)
Machine vision and imaging technologies will play a major role in the transition to an economy in which AI and robotics are increasingly important. - P1303 — Wearable Functionalities (January 2019)
As wearable technologies advance, functionalities of an increasingly wide variety become wearable.