Cloud Broker Service for Digital Assistant Automation
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Solution Overview
Problem
Current online computing systems fail to provide proactive services by combining user data from multiple accounts, limiting their ability to automate tasks and provide alerts without significant user intervention, especially in distributed computing environments.
Innovation Solution
A cloud-based broker service that aggregates multiple accounts and credentials, monitors device contexts, and utilizes this information to automate tasks and provide alerts, leveraging cloud components like the Azure Platform for data storage, data collectors, and an assistant module for real-time monitoring and action.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If current online computing systems store credentials for multiple accounts, then data integration for viewing is enabled, but proactive services that combine user data to automate tasks are not provided
Solution Approach 1:
The broker service automatically performs tasks by monitoring device context and executing actions based on aggregated account data without requiring user intervention. For example, it automatically determines traffic conditions affecting appointments and can proactively reschedule meetings or send notifications, allowing the system to serve itself rather than requiring manual user operation.
Solution Approach 2:
The broker service acts as an intermediary layer between multiple account credentials and the user device. It aggregates data from various accounts, monitors device context, and automatically executes tasks by mediating between the stored credentials and the actions needed, thereby enabling automation without direct user involvement in each task execution.
2Ease of operation
If mobile devices aggregate information for easier viewing, then data accessibility is improved, but background processing capabilities are limited due to battery constraints
Solution Approach 1:
The patent extracts the computationally intensive background processing functions from the mobile device and relocates them to a cloud-based broker service. The mobile device retains only the lightweight functionality for data aggregation and display, while the broker service handles the complex analysis and automation tasks in the cloud, thereby maintaining data accessibility without burdening the device's battery resources.
3Productivity
If a user manually checks traffic conditions and determines departure times, then travel planning is achieved, but time and effort are consumed
Solution Approach 1:
The broker service performs preliminary actions by continuously monitoring device context and pre-calculating optimal departure times based on aggregated account data and real-time traffic conditions. When an appointment is detected, the system has already prepared traffic analysis and can immediately determine the best departure time without requiring the user to manually check conditions, thereby completing the task more efficiently and saving time.
Data Source
AI summary
A cloud-based broker service may be provided for computing devices in a distributed computing environment. The broker service may aggregate user accounts and user account credentials utilized for accessing online services by the computing devices. The broker service may monitor a context of the computing devices associated with the user accounts. The broker service may then utilize the context, data associated with the user accounts and data associated with the user account credentials to automate tasks and/or provide alerts associated with the data.