Retail Floor Automation via Video Analytics and Decision Rules

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Solution Overview

Problem

Manual tasks in retail operations, such as checking availability or price of items, are inefficient and prone to inconsistent decisions due to reliance on human expertise in conventional video analysis systems.

Innovation Solution

A floor operations automation system utilizing an intelligent video module, decision rules, and profiles to analyze video analytics data and autonomously decide on actions without human intervention, integrating with existing surveillance systems to automate tasks like restocking or managing store operations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Extent of automation

If conventional video analysis systems are used, then video capture capability is provided, but human decision-making is still required leading to inconsistent decisions and dependency on employee expertise

Engineering Contradiction:

Improvedecision-making automationVSAvoiddecision consistency

Core Design Contradiction:

Extent of automationVSReliability

Solution Approach 1:

The system enables self-service automation where the video analysis system automatically makes operational decisions without human intervention. The decision engine analyzes video data and autonomously determines actions such as restocking requirements, shelf compliance, and loss prevention measures, eliminating dependency on employee expertise and ensuring consistent decision-making.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces the mechanical system of human decision-making with an automated decision engine that processes video analytics data. This substitution transforms manual visual inspection and judgment into an automated computational process that consistently applies predefined business rules and algorithms to make reliable decisions.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Productivity

If manual tasks are performed by employees, then flexibility and adaptability are maintained, but efficiency and productivity are reduced due to time-consuming physical checks

Engineering Contradiction:

Improveoperational efficiencyVSAvoidtime for manual checks

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The system implements continuous monitoring and analysis of retail floor conditions through automated video capture and real-time analytics processing. Unlike manual checks that occur periodically, the automated system continuously tracks inventory levels, shelf compliance, and customer behavior, eliminating idle time between checks and maintaining constant operational awareness.

Inventive Principle:

Principle #20Continuity of useful action

Solution Approach 2:

The patent replaces manual physical inspection tasks with automated video analysis and image processing. Employees no longer need to physically walk to shelves to check inventory or compliance; instead, computer vision algorithms automatically analyze video feeds, dramatically reducing the time required for these tasks while increasing operational efficiency.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Area of stationary object

If more video cameras and analysis capacity are deployed, then monitoring coverage is improved, but system complexity and computational requirements increase

Engineering Contradiction:

Improvemonitoring coverage areaVSAvoidsystem complexity

Core Design Contradiction:

Area of stationary objectVSDevice complexity

Solution Approach 1:

The system divides the retail environment into distinct monitoring zones, each handled by specific video cameras and analysis modules. This segmentation allows the system to manage large coverage areas by breaking them into smaller, independently analyzed sections, reducing the computational complexity of processing entire store footage at once while maintaining comprehensive monitoring.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The video analysis system is designed with multi-functional capabilities that allow the same infrastructure to perform multiple tasks simultaneously - inventory monitoring, shelf compliance checking, customer behavior analysis, and loss prevention. This universality maximizes the utility of deployed cameras and computational resources, reducing overall system complexity by consolidating multiple monitoring functions into a single integrated platform.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS11443259B2Automatic floor-level retail operation decisions using video analytics

Publication Date: 2022.09.13 DOORDASH INC

AI summary

A floor operations automation system can include an intelligent video module, profiles, decision rules, and a decision module. The intelligent video module can be configured to generate video analytics data from video captured by video cameras within a retail location. The profiles can contain data that represents a business practice or policy of the retail location and/or user-specified preferences for decision-related variables. The decision rules can express actions to be performed in response to predefined conditions within the retail location. The decision module can be configured to decide upon action to be performed, based upon the video analytics data, the profiles, and the decision rules. The decision can be made without direct input from a human agent of the retail location. The actions can affect a business system and/or a human agent associated with the retail location.