AI-Guided MFD Connection Layer for Mobile Device Pairing
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Solution Overview
Problem
Connecting a mobile device to a multi-function device (MFD) is often difficult and frustrating due to reliance on static connection methods that may not work, requiring constant monitoring and troubleshooting, especially when shared among multiple users.
Innovation Solution
A mobile device scans for MFDs in its vicinity, communicates a connection request to a device recognition system, which uses a trained MFD connection algorithm to provide dynamic connection instructions, and troubleshoots issues using a trained MFD connection algorithm.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If static connection methods (QR-Code, NFC, manual entry) are used to connect mobile device to MFD, then connection can be established, but the process is difficult and frustrating requiring constant monitoring and troubleshooting
Solution Approach 1:
The patent applies dynamics by transitioning from static connection methods to a dynamic AI-driven approach. The system continuously learns from connection outcomes and adapts its recommendations in real-time, making the connection process adaptive rather than fixed. The AI model dynamically selects and refines connection methods based on accumulated data from multiple users and devices.
Solution Approach 2:
The patent implements feedback mechanisms where connection success or failure data is fed back to the AI model. The system monitors connection outcomes and uses this feedback to continuously improve its recommendations. This closed-loop feedback system enables the AI to learn from both successful and unsuccessful connection attempts, progressively enhancing its ability to guide users through the most effective connection methods.
2Adaptability or versatility
If multiple static connection methods are provided for user selection, then various connection scenarios can be addressed, but the system lacks adaptability when methods fail or are incompatible
Solution Approach 1:
The patent applies self-service by enabling the AI system to automatically select and optimize connection methods without requiring user expertise. The system independently analyzes connection parameters, device compatibility, and historical data to determine the most appropriate connection approach. This self-service capability allows the system to adapt to new devices and scenarios automatically, improving both versatility and reliability.
Solution Approach 2:
The patent utilizes parameter changes by dynamically adjusting connection parameters based on AI analysis. The system modifies connection settings, protocols, and methods according to real-time conditions and learned patterns. This dynamic parameter adjustment enables the system to adapt to different device configurations and environmental conditions, enhancing both adaptability and connection success rates.
3Ease of repair
If manual monitoring and troubleshooting by device owners is required, then connection issues can be addressed, but the process becomes complex and time-consuming
Solution Approach 1:
The patent introduces an AI intermediary that mediates between the user and the complex troubleshooting process. Instead of requiring users to directly navigate complex diagnostic procedures, the AI assistant acts as an intermediary that interprets connection issues, formulates appropriate troubleshooting steps, and guides users through simplified procedures. This intermediary layer significantly reduces the perceived complexity for end users.
Solution Approach 2:
The patent applies preliminary action by having the AI system proactively identify and resolve potential connection issues before they become problematic. The system continuously monitors connection parameters and predicts potential failures, implementing corrective actions in advance. This proactive approach simplifies troubleshooting by preventing many issues from occurring in the first place, rather than requiring complex reactive troubleshooting.
Data Source
AI summary
A method (500) for wirelessly connecting a mobile device (182) to a multi-function device (MFD) (100), comprising: scanning (530) for one or more MFDs within a vicinity of the mobile device; communicating (540), by the mobile device, a connection request to a device recognition system (400); receiving (550), by the mobile device from the device recognition system, connection instructions comprising instructions for connecting to one or more MFDs in the vicinity of the mobile device, wherein the instructions for connecting to the one or more MFDs are selected by the device recognition system using a trained MFD connection algorithm (464); and connecting (560), by the mobile device utilizing the connection instructions, to one of the one or more MFDs in the vicinity of the mobile device