3M INNOVATIVE PROPERTIES COMPANY (20240233383). SYSTEM AND METHOD FOR CLASSIFYING TASK simplified abstract
Contents
SYSTEM AND METHOD FOR CLASSIFYING TASK
Organization Name
3M INNOVATIVE PROPERTIES COMPANY
Inventor(s)
John W. Henderson of St. Paul MN (US)
Sophia S. Liu of Denver CO (US)
Andrew W. Long of Woodbury MN (US)
Jordan J.W. Craig of White Bear Lake MN (US)
SYSTEM AND METHOD FOR CLASSIFYING TASK - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240233383 titled 'SYSTEM AND METHOD FOR CLASSIFYING TASK
The abstract describes a method of classifying a task by capturing images and audio signals over a period of time, then using machine learning models to classify them and determine the corresponding task.
- Obtaining images and audio signals over a period of time
- Classifying images using a trained machine learning model
- Classifying audio signals using another trained machine learning model
- Merging the results to determine the task
- Utilizing a merging algorithm to combine probabilities and labels
Potential Applications: - Task classification in various industries such as security, healthcare, and retail - Automated monitoring and analysis of activities based on audio and visual data
Problems Solved: - Efficient task classification without manual intervention - Real-time monitoring and analysis of tasks based on multiple data sources
Benefits: - Improved accuracy and speed in task classification - Enhanced automation and efficiency in monitoring processes - Potential for predictive analytics based on task classification data
Commercial Applications: Title: Automated Task Classification System This technology can be used in security systems for identifying suspicious activities, in healthcare for monitoring patient care tasks, and in retail for analyzing customer behavior patterns.
Prior Art: Prior research may include studies on multi-modal data fusion for task classification and machine learning models for audio and image analysis.
Frequently Updated Research: Research on improving machine learning models for multi-modal data fusion and real-time task classification systems is ongoing.
Questions about the technology: 1. How does the merging algorithm combine the probabilities and labels from the image and audio classifications? 2. What are the potential challenges in implementing this automated task classification system in real-world scenarios?
Original Abstract Submitted
a method of classifying a task includes obtaining a plurality of images via an image capturing device and an audio signal via an audio sensor for a predetermined period of time. the method further includes classifying, via a first trained machine learning model, the plurality of images to generate a list of first class probabilities and a list of first class labels. the method further includes classifying, via a second trained machine learning model, the audio signal to generate a list of second class probabilities and a list of second class labels. the method further includes determining, via a merging algorithm, a list of third class probabilities and a list of third class labels based on the lists of first and second class probabilities. the method further includes determining the task corresponding to the predetermined period of time based on the list of third class probabilities.
