Usage-Based Data Transfer Control for Connected Devices
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Solution Overview
Problem
Current solutions for managing budgets associated with network-connected devices are inefficient, as they require manual intervention for bill payments and lack real-time adjustments based on actual usage, leading to potential overages and errors, especially when devices are outside user control or subject to variable costs like weather changes.
Innovation Solution
A system that uses a centralized hub to monitor and manage network-connected devices, comparing actual usage to expected usage, automatically adjusting operations and payments, and allocating funds to a holding account for pre-authorized payments, with features for predictive adjustments based on data sources like weather forecasts and historical usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual intervention is used for bill payments and budget management, then users have direct control over payments, but the process is inefficient and prone to errors
Solution Approach 1:
The system enables automatic bill payment processing where the budget management system autonomously monitors usage, compares actual vs. expected usage, and executes payments without manual user intervention. The system self-manages the entire billing cycle from monitoring to payment execution.
Solution Approach 2:
The system continuously monitors actual usage data from connected devices, compares it against expected usage thresholds, and uses this feedback to automatically adjust payments and notify users of budget status. This closed-loop feedback mechanism ensures accurate and timely payments.
2Measurement precision
If real-time monitoring and automatic adjustments are implemented, then usage accuracy and budget control are improved, but system complexity increases
Solution Approach 1:
The budget management system performs multiple functions including monitoring usage data, comparing actual vs. expected usage, calculating payments, executing transactions, and generating notifications. This multi-functional approach consolidates complexity into a single unified system rather than requiring separate components for each function.
Solution Approach 2:
The system combines budget management, usage monitoring, payment processing, and user notification functions into an integrated platform that works with multiple connected devices. This merging reduces overall system complexity by providing a centralized management interface.
3Speed
If automatic payment authorization is used, then payment processing speed is improved, but control over individual payments is reduced
Solution Approach 1:
Users pre-configure their budget parameters, usage thresholds, and payment preferences in advance. The system then uses these pre-set instructions to automatically execute payments when usage conditions are met, eliminating the need for real-time user decisions while maintaining user-defined control parameters.
Solution Approach 2:
The system provides continuous feedback to users about their budget status, actual usage, and upcoming payments. This transparency allows users to maintain awareness and control over their automatic payment system while enjoying the speed benefits of automation.
4Use of energy by moving object
If predictive adjustments based on weather forecasts and historical data are implemented, then energy optimization is improved, but data processing requirements increase
Solution Approach 1:
The system uses historical usage data and weather forecasts to predict future energy consumption patterns and proactively adjusts device operations or user behavior before peak consumption occurs. This predictive approach optimizes energy usage by preparing adjustments in advance rather than reacting to actual consumption.
Data Source
AI summary
The present disclosure involves systems, software, and computer-implemented methods for implementing a data transfer control based on information received from connected devices. In one instance, operations include loading an expected usage amount for a group of connected devices. Signals representing actual usage amounts associated with the group are received from at least device in the group. The actual usage amounts can be compared to the expected usage amount. An authorization of at least one payment-related action associated with the at least one group of connected devices is automatically transmitted to a payment system in response to determining that the usage amount is less than or equal to the expected amount, and at least one instruction to perform a corrective action associated with the group is automatically transmitted to at least one connected device of the group in response to determining that the actual amount exceeds the expected amount.