IoT Update Scheduling via Network and User Data Analysis
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Solution Overview
Problem
Current systems for updating connected objects often lead to disruptions and unavailability of services due to unregulated and resource-intensive updates, causing network saturation and impacting users and third-party devices.
Innovation Solution
An optimization process that includes network and user data surveillance, analysis of available communication and user time periods, and determination of an optimal update schedule to minimize disruptions and resource consumption, using an application module to prioritize and manage updates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If updates are implemented by all connected objects at the same time, then updates are completed efficiently, but network saturation occurs and service availability decreases
Solution Approach 1:
The patent implements periodic action by dividing updates into different time periods or phases. Instead of all connected objects updating simultaneously, the system schedules updates to occur in staggered time windows, allowing network traffic to be managed in periodic cycles that prevent saturation while maintaining overall update progress.
Solution Approach 2:
The patent applies segmentation by dividing the update process into separate components or stages that can be executed independently. Updates are segmented by object type, priority level, or time window, allowing the system to manage multiple update streams without overwhelming the network infrastructure.
2Ease of manufacture
If updates are carried out without regulation or ordering, then implementation is simple, but resource consumption increases and network performance degrades
Solution Approach 1:
The patent changes key parameters of the update process, such as timing, priority, and scheduling constraints. By adjusting these parameters based on network conditions and object characteristics, the system optimizes resource consumption while maintaining automated update implementation without requiring complex manual regulation.
Solution Approach 2:
The patent introduces dynamic scheduling where update timing and priorities are adjusted in real-time based on network conditions, object availability, and resource constraints. This dynamic approach allows the system to adapt to changing conditions automatically, maintaining simplicity while reducing overall resource consumption.
3Loss of time
If updates are implemented during high-activity periods, then update timing is convenient, but user experience deteriorates due to service disruptions
Solution Approach 1:
The patent implements feedback mechanisms that monitor network activity levels, user behavior patterns, and service usage metrics. This feedback information is used to dynamically adjust update scheduling, identifying optimal time windows where updates can be performed with minimal impact on user experience while maintaining timing efficiency.
Solution Approach 2:
The patent applies preliminary action by analyzing historical data and predicting optimal update windows before scheduling actual updates. The system performs preliminary assessments of network conditions and user patterns to proactively identify the best times for updates, preventing service disruptions before they occur.
Data Source
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AI summary
The invention relates to an optimization method (1) for updating connected objects (IoT1, IoT2, IoT3) comprising at least one requesting connected object and an application module (13) installed on said requesting connected object, characterized in that the method comprises: - a monitoring step (200) of network data, - a monitoring step (300) of user usage data, - a monitoring step (400) of third-party usage data, - a network data analysis step (250), said analysis including the identification of available communication time periods, - a user usage data analysis step (350), including the identification of available user usage time periods, - a third-party usage data analysis step (450), including the identification of available third-party usage time periods.- a step of determining (700) at least one update schedule for the requesting connected object based on available time periods.