View source for 17961230. AUTOMATED COLLECTION OF PRODUCT IMAGE DATA AND ANNOTATIONS FOR ARTIFICIAL INTELLIGENCE MODEL TRAINING simplified abstract (Insight Direct USA, Inc.)

=AUTOMATED COLLECTION OF PRODUCT IMAGE DATA AND ANNOTATIONS FOR ARTIFICIAL INTELLIGENCE MODEL TRAINING=


==Organization Name==

[[:Category:Insight Direct USA, Inc.|Insight Direct USA, Inc.]]


[[Category:Insight Direct USA, Inc.]]

==Inventor(s)==

[[:Category:Amol Ajgaonkar of Chandler AZ (US)|Amol Ajgaonkar of Chandler AZ (US)]][[Category:Amol Ajgaonkar of Chandler AZ (US)]]

==AUTOMATED COLLECTION OF PRODUCT IMAGE DATA AND ANNOTATIONS FOR ARTIFICIAL INTELLIGENCE MODEL TRAINING - A simplified explanation of the abstract==


This abstract first appeared for US patent application 17961230 titled 'AUTOMATED COLLECTION OF PRODUCT IMAGE DATA AND ANNOTATIONS FOR ARTIFICIAL INTELLIGENCE MODEL TRAINING

==Simplified Explanation==

The abstract describes a method for obtaining images and data to train an AI model for product detection. This involves generating an annotation package with images and data about a product, capturing images of the product with cameras, inputting data about the product into an edge compute device, and creating an annotation package for the product.

* Image collection system at a first product source
* Generation of a first annotation package with images and data about a product
* Placing the product in a first enclosure at the product source
* Initiating a process to obtain images of the product in the enclosure
* Obtaining images of the product with cameras in the enclosure
* Providing images to an edge compute device
* Inputting data about the product into the edge compute device
* Creating an annotation package for the product

== Potential Applications ==
The technology can be applied in various industries such as retail, manufacturing, and logistics for automated product detection and recognition.

== Problems Solved ==
This technology streamlines the process of collecting images and data for training AI models, improving the efficiency and accuracy of product detection systems.

== Benefits ==
- Enhanced accuracy in product detection
- Streamlined data collection process
- Improved training of AI models for product recognition

== Potential Commercial Applications ==
"Automated Product Detection and Recognition Technology in Retail and Manufacturing"

== Possible Prior Art ==
Prior art may include existing systems for image and data collection for AI model training in product detection applications.

== Unanswered Questions ==
1. How does this technology handle variations in product appearance and positioning during image capture?
2. What measures are in place to ensure the security and privacy of the collected data and images?


==Original Abstract Submitted==

A method of obtaining images and data to train an AI model for product detection includes generating, with an image collection system at a first product source, a first annotation package including one or more images of and data about a first product. The first product is placed in a first enclosure located at the first product source. A process for obtaining the one or more images of the first product is initiated in the first enclosure. The one or more images of the first product is obtained with one or more cameras positioned in the first enclosure. The one or more images of the first product is provided to an edge compute device. Data about the first product is input, using an input device, into the edge compute device. An annotation package for the first product is created that includes the one or more images and the data.



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