Cart Object Monitoring with a Docking Station and List Verification
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Solution Overview
Problem
Processes for tracking objects in and/or removing from carts are prone to errors, inaccuracies, and susceptible to fraudulent and/or abusive activities.
Innovation Solution
A system utilizing sensors and a docking station on a cart to monitor objects, which includes a computing system that cross-references detected objects against a stored user-generated list, using various sensors to identify and verify the presence and characteristics of objects, and provides notifications or navigation instructions based on the comparison.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional manual tracking methods are used to monitor objects in carts, then the system is simple and easy to operate, but the process is prone to errors and inaccuracies
Solution Approach 1:
The patent replaces manual mechanical tracking methods with an automated sensor-based system. Sensors detect objects in carts and transmit data to a computing system, which automatically cross-references against stored lists and generates notifications. This substitution of mechanical manual tracking with automated sensing and computing resolves the contradiction by achieving high measurement precision while the system handles the complexity automatically.
Solution Approach 2:
The system performs self-service through automated object detection, data cross-referencing, and notification generation without requiring manual intervention. The sensors automatically monitor objects, the computing system automatically compares detected objects against stored lists, and notifications are automatically generated and sent to users. This automation resolves the contradiction by eliminating human error while managing system complexity through programmed operations.
2Reliability
If automated sensor-based tracking is implemented, then measurement precision improves, but the system becomes more complex
Solution Approach 1:
The system implements feedback through automated notification delivery to users when objects are detected in carts that should not be there, or when expected objects are missing. This feedback mechanism enhances reliability by providing real-time alerts, while the automated nature of the feedback delivery manages the complexity through programmed response protocols.
Solution Approach 2:
The computing system acts as an intermediary between the sensors and the users. It receives data from sensors, performs cross-referencing against stored lists, and generates notifications for users. This intermediary role enhances reliability through centralized processing while managing complexity by consolidating multiple functions in a single computing system rather than distributing them across multiple complex components.
3Object-affected harmful factors
If manual monitoring processes are used, then the system is simple, but it is susceptible to fraudulent and abusive activities
Solution Approach 1:
The patent replaces manual monitoring with automated sensor-based detection and computing system analysis. Sensors automatically detect objects and the computing system cross-references them against stored lists to identify fraudulent or abusive activities. This automation eliminates human susceptibility to fraud and abuse while managing complexity through automated verification protocols.
Solution Approach 2:
The system provides feedback by automatically generating notifications when fraudulent or abusive activities are detected, such as when objects are placed in carts that should not contain them, or when expected objects are missing. This automated feedback mechanism enhances security by providing real-time alerts to prevent harmful factors, while the programmed detection logic manages complexity through predefined verification rules.
Data Source
AI summary
A technique for monitoring objects in a cart is disclosed. A cart is configured to receive an object and includes a plurality of sensors configured to detect a location of the cart and a characteristic of an object in the cart. The cart also includes a docking station that can receive an electronic device and operatively and electrically couple the sensors to the electronic device. A computing system is in communication with the electronic device and configured to access a database containing a stored list generated by the user. The computing can identify the object in the cart based, at least in part, on data received from the plurality of sensors and the location of the cart. The computing system can also determine whether the object in the cart is included on the stored list.