AI-Based Mailable Item Screening for Contraband Detection
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Solution Overview
Problem
The high volume of mailable or shippable items processed by delivery services makes manual identification of suspicious items for content inspection and testing burdensome and costly, with existing technologies unable to consistently and cost-effectively identify candidates for prohibited and restricted content.
Innovation Solution
An artificial intelligence-based system that acquires and processes data on physical and digital characteristics of items to generate virtual models, create unique feature sets, and compare them to reference sets to autonomously identify candidates for content inspection and testing, using machine learning and sensor data to divert items for inspection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual screening methods are used to identify suspicious items, then inspection accuracy can be maintained through trained personnel, but the cost and time consumption increase significantly due to the large volume of items processed
Solution Approach 1:
The patent replaces manual mechanical screening processes with an automated computerized system that uses sensors, image processing, and machine learning algorithms to identify suspicious items. This substitution maintains inspection accuracy through sophisticated detection algorithms while dramatically reducing screening time and operational costs by processing items automatically without human intervention for initial screening.
Solution Approach 2:
The system creates virtual models or digital representations of physical items through sensor data and image processing. These digital copies are then analyzed by algorithms to identify suspicious characteristics, allowing rapid automated assessment without handling physical items manually, thus reducing time loss while maintaining detection accuracy.
2Reliability
If high-tech inspection equipment is deployed to inspect a large percentage of items, then detection capability improves, but the cost of installation and operation becomes prohibitively expensive
Solution Approach 1:
The patent implements a two-tier screening approach where a computerized system first performs preliminary screening of all items using cost-effective sensors and image processing. Only items flagged as suspicious by this initial screening are then subjected to more expensive high-tech inspection equipment. This partial application of advanced inspection resources maintains high detection capability for suspicious items while avoiding the prohibitive cost of inspecting every item with expensive equipment.
Solution Approach 2:
The computerized screening system acts as an intermediary between items and high-tech inspection equipment. It pre-processes items using lower-cost technologies and selectively directs only suspicious items to expensive inspection equipment, thereby reducing overall system cost while maintaining reliable detection capability through the intermediary filtering layer.
3Productivity
If more inspection resources are allocated to process higher volume of items, then screening throughput increases, but operational costs and resource requirements become unsustainable
Solution Approach 1:
The system implements self-service automation where computerized algorithms autonomously screen items, identify suspicious characteristics, and make decisions about which items require further inspection. This self-service capability eliminates the need for large numbers of human screeners, dramatically increasing screening throughput while reducing operational costs and resource requirements by replacing manual labor with automated intelligent processing.
Solution Approach 2:
The patent transforms the screening process from manual human-based operations to automated computer-based operations, fundamentally changing the operational parameters. This parameter change enables processing of much higher item volumes through automated systems with lower marginal costs, increasing productivity while making operational costs sustainable through economies of scale and reduced per-item processing expense.
Data Source
AI summary
Computerized system, method, and processor-executable code, as may be executed by an artificial intelligence-based system, for carrying out an autonomous process are provided. Disclosed embodiments may be used to autonomously screen in real-time mailable or shippable items being conveyed through an item processing system to identify item candidates for content inspection and/or testing to check for prohibited and/or restricted content (e.g., contraband) prior to item sortation and distribution for delivery to recipients. Disclosed embodiments make effective use of algorithms involving machine vision, machine learning, and data-intensive and/or sensor-driven tasks.