Confidence Event Recorder for Delivery Tracking Accuracy
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current systems lack accurate methods for tracking item delivery in distribution networks, which hinders the ability to adjust routes and provide reliable expected delivery windows to receivers.
Innovation Solution
A system comprising a barcode scanner, GPS unit, and mobile computing device that scans items, generates confidence data, and calculates expected delivery times based on historical data and recalculation factors, communicating these windows to recipients.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional tracking methods are used, then the system is simpler, but delivery tracking accuracy is insufficient
Solution Approach 1:
The system segments the delivery tracking process into distinct confidence events (confidence source, confidence activity, confidence data) that can be independently captured and processed. Each segment includes specific components like barcode scanners at delivery points, mobile computing devices with GPS, and dedicated databases for storing different types of delivery information, enabling accurate tracking without requiring a monolithic complex system
Solution Approach 2:
The patent introduces confidence data as an intermediary element that bridges the gap between raw tracking data and delivery expectations. This intermediary layer processes and validates data from multiple sources (barcode scanners, GPS units, mobile devices) before generating expected delivery windows, thereby improving accuracy while managing system complexity through structured data handling
2Reliability
If more tracking data is collected, then delivery window reliability improves, but data processing complexity increases
Solution Approach 1:
The system performs preliminary actions by pre-establishing confidence events and confidence sources before actual delivery occurs. Historical data about delivery routes, times, and confidence events is stored in advance in databases, allowing the system to process new delivery data against pre-defined frameworks and reduce real-time processing complexity while maintaining high reliability
Solution Approach 2:
The patent employs parameter changes by adjusting confidence levels and recalculation factors based on the type of confidence event and historical performance. Different delivery scenarios assign different weights and parameters to various data sources, allowing the system to manage processing complexity by focusing computational resources on the most impactful parameters for each specific delivery situation
Data Source
AI summary
A system and method for accurately sort items for delivery and track the delivery of items in an item distribution network using a purpose built confidence event recorder. Items can then be tracked while out for delivery through the use of confidence data recorded by a confidence event recorder carried by an item carrier. Confidence data can be used to accurately record when and where item carriers deliver items and can be used for generating and transmitting an expected delivery window.