Destination Validation Using Wireless Network Profiles
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In densely populated areas, delivery personnel often face difficulties in confirming arrival at the correct target location due to unfamiliarity with the location and similarities in street addresses, leading to potential incorrect deliveries.
Innovation Solution
A method that compares identifying features of the target location, such as visible street addresses, exterior building features, and wireless communication network profiles, using a confidence score to validate the correct arrival, and updates a database with observed features for future reference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If GPS is used for location validation, then positioning is provided, but reliability deteriorates in densely populated areas with similar street addresses
Solution Approach 1:
The validation system is segmented into multiple independent feature types (visual features, wireless network features, walking profile features). Each feature type is validated separately and then combined to produce the final validation result. This segmentation allows the system to handle complex validation tasks by breaking them down into manageable components, improving reliability without overwhelming complexity in any single area.
Solution Approach 2:
Multiple different types of features (visual, wireless network, walking profile) are merged and combined to create a comprehensive validation system. The system integrates these diverse feature types through a unified validation process that combines their individual results, achieving higher reliability through synthesis of multiple data sources rather than relying on a single validation method.
2Measurement precision
If multiple identifying features are compared, then validation accuracy is improved, but processing time increases
Solution Approach 1:
The system performs preliminary actions by pre-processing and organizing feature data before the actual validation comparison. Features are pre-categorized, pre-validated for quality, and pre-arranged in a structured format that facilitates rapid comparison during the validation process. This preliminary organization reduces the time required for the actual comparison operation while maintaining high accuracy.
Solution Approach 2:
The validation system operates continuously by comparing multiple features in an uninterrupted sequence. Rather than validating features one at a time with significant pauses, the system processes visual features, wireless network features, and walking profile features in a continuous flow, maintaining productive action throughout the validation process to minimize total processing time while achieving comprehensive accuracy.
3Reliability
If visual features and wireless network profiles are collected, then location confirmation reliability is improved, but data storage requirements increase
Solution Approach 1:
The system extracts only the essential and most discriminative features from the available data. Rather than storing all possible data about a location, the system identifies and stores only the critical visual features, wireless network characteristics, and walking profile attributes that are necessary for reliable validation. This extraction process reduces storage requirements while maintaining the reliability needed for accurate location confirmation.
Solution Approach 2:
The system applies local quality by storing and processing features with different levels of detail appropriate to their specific purposes. Critical identification features are stored with high precision, while less critical features are stored with lower detail. The system also selectively stores only those features that are relevant to the specific validation task at hand, rather than uniformly storing all data at maximum quality, thereby reducing overall storage requirements while maintaining necessary reliability.
Data Source
AI summary
A method for confirming arrival at a target location includes comparing, by one or more controllers, properties of a plurality of identifying features of the target location with properties of a corresponding plurality of corresponding features of a present location to result in a plurality of comparisons. The method additionally includes identifying, by one or more controllers, the present location as the target location if the plurality of comparisons concludes that the present location is the target location. The properties of a plurality of identifying features of the target location include at least one property of one or more wireless communication networks expected to be detectable at the target location.