Camera-Based Dynamic Item Storage Mapping for Delivery Retrieval
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Solution Overview
Problem
The process of retrieving items from a delivery vehicle for delivery is time-consuming due to inefficient item location methods, as existing systems fail to accurately maintain and update the positions of items during transit, leading to reduced delivery efficiency.
Innovation Solution
A system and method that utilizes a computing device with a camera and controller to generate and dynamically update a real-time map of item locations within a storage area, using label detection and optical character recognition to track item positions, and provide real-time notifications for misplaced items.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If manual item location tracking is used in delivery vehicles, then system complexity is reduced, but item retrieval time increases significantly
Solution Approach 1:
The system creates a digital copy (map) of the physical storage area and item locations within it. The controller generates and maintains a data structure that replicates the spatial arrangement of items, allowing rapid information retrieval without physically searching for items. This digital twin approach enables fast item location lookup while keeping the physical vehicle unchanged.
Solution Approach 2:
The patent replaces manual mechanical searching methods with an automated optical detection system. Image capture devices and controllers automatically detect item positions, labels, and storage locations, substituting human visual search and manual tracking with machine vision and automated data processing systems.
2Productivity
If dynamic real-time tracking of item locations is implemented, then delivery efficiency improves, but system complexity and cost increase
Solution Approach 1:
The system dynamically updates the item location map in real-time as items are added to or removed from the storage area. The controller continuously maintains an accurate representation of current item positions, enabling adaptive retrieval operations that respond to changing cargo configurations during delivery routes.
Solution Approach 2:
The system performs self-updating of item location data through automated image capture and processing. The image capture device and controller work autonomously to detect, record, and update item positions without requiring manual intervention, making the tracking system maintain itself automatically.
3Measurement precision
If automated image recognition is used to track items, then item location accuracy improves, but processing time and computational requirements increase
Solution Approach 1:
The system performs preliminary organization of item data during the loading phase, creating and storing the item location map in advance. By pre-processing and structuring location information before delivery operations begin, the system enables rapid retrieval during actual delivery without requiring intensive real-time processing.
Data Source
AI summary
A method includes: receiving a selection of an active operating mode selected from a generating mode and an updating mode; obtaining an image depicting a storage area; detecting, in the image, a label disposed on an item in the storage area; determining (i) an identifier of the label, and (ii) a location of the label in the storage area; determining whether the label is included in a map of the storage area; and when the label is not included in the map: (i) when the generating mode is active, inserting a record into the map, the inserted record containing the identifier of the label, and the location of the label, and (ii) when the updating mode is active, generating a notification via an output device.