Mobile App Access Point Prioritization
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Solution Overview
Problem
Access control systems are complex and require users to manage multiple keycards and codes, making them cumbersome, and there is a need to simplify user interaction by predicting and prioritizing access points based on user behavior.
Innovation Solution
A mobile application that presents a prioritized list of access points authorized to the user, using learned patterns from past behavior, including time, location, and sequence, and includes a 'help request' feature for assistance, utilizing indoor tracking and GPS for precise location inference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If access control systems use multiple keycards and codes to control access, then security and access control capability are improved, but system complexity and user burden increase
Solution Approach 1:
The mobile device serves multiple functions: it acts as a keycard, a code entry device, and a communication bridge between the user and the access control system. The single mobile device replaces multiple traditional access control accessories (keycards, codes), reducing system complexity while maintaining security through the access control system's ability to manage multiple authorization methods through one interface
Solution Approach 2:
The mobile device functions as an intermediary between the user and the access control system. It communicates with the access control system via wireless transmission, carrying user credentials and receiving authorization responses. This intermediary role simplifies the user interface while the access control system maintains security through backend credential verification
2Adaptability or versatility
If access control systems present all authorized access points to users, then complete access options are provided, but user interface complexity and selection difficulty increase
Solution Approach 1:
The system performs preliminary actions by predicting which access points the user is most likely to need based on historical behavior patterns, time of day, and location data. These predicted access points are prioritized and presented first in the interface, allowing users to quickly access frequently used locations without having to search through all authorized access points
Solution Approach 2:
The user interface applies local quality by providing different presentation styles for different access points based on their predicted importance. Frequently accessed access points receive prominent positioning and visual emphasis, while less frequently used access points are presented in standard format, optimizing the interface for the user's specific needs at each moment
3Measurement precision
If access control systems require precise location tracking for help requests, then assistance accuracy is improved, but privacy concerns and system complexity increase
Solution Approach 1:
The mobile device leverages its existing multi-functionality by utilizing already-present components (GPS receiver, wireless communication capabilities) for location tracking and help request functionality. Rather than adding dedicated tracking hardware, the system repurposes the mobile device's universal capabilities to provide precise location information for security assistance
Solution Approach 2:
The mobile device performs self-service by using its own built-in location tracking capabilities (GPS, cellular triangulation) to determine and communicate the user's position to the access control system. The device autonomously provides location data without requiring external tracking infrastructure, reducing overall system complexity while maintaining precision
Data Source
AI summary
An access control system includes a mobile application executing on a mobile computing device rendering a graphical user interface (GUI), which presents available access points, which are prioritized based on predictions of the next access points to be engaged. These predictions are based on prioritized lists of access points associated with times of day, days of the week and/or locations. The prioritized lists are modified based on recently selected access points, authorization status, prescribed schedules and/or prescribed sequences of access points. A selection pane of the GUI includes graphical elements associated with the access points. Graphical elements associated with the access points predicted to be next engaged by the user are displayed near the top of the selection pane. An inferred location of the user, based on the predictions, is sent to a monitoring center in response to selecting a help request option.