Consumer Product Tracking via Smart Cabinet Cameras for Real-Time Insights

The patent introduces an intermediary system consisting of sensors, cameras, and image processing algorithms that indirectly observe and measure actual product consumption behavior without requiring direct consumer input. This intermediary system captures images of product containers, identifies products through OCR, and tracks consumption patterns objectively, resolving the contradiction between obtaining consumption data and ensuring its accuracy.

The patent replaces traditional mechanical research methods (interviews, surveys, manual observations) with an automated optical and computational system. Cameras capture images, and machine learning algorithms process these images to extract consumption data, substituting human-based mechanical processes with automated technological systems that provide more accurate and continuous measurement.

The patent enables the consumption tracking system to serve itself by using automatically captured images and AI processing to generate consumption insights without human intervention. The system self-captures data through cameras, self-processes images through OCR and machine learning, and self-generates consumption reports, eliminating the need for representative visits while maintaining data authenticity.

The patent creates a digital copy of the physical consumption environment by capturing images of product containers and using image processing to extract consumption information. This digital copying approach replaces physical visits with virtual observation, maintaining reliability while reducing system complexity and costs.