AI Network Selection Using Historical and Predictive Data
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Solution Overview
Problem
Current communication devices select networks based on default or present information, limiting their potential and leading to reduced quality of service.
Innovation Solution
A system and method that utilize artificial intelligence algorithms to select communication networks based on historical, present, and future data, optimizing parameters such as network quality, security, and availability by accessing knowledge from internal, external, or collective device experiences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If communication devices use only default or present information for network selection, then the device complexity is reduced, but the quality of service deteriorates
Solution Approach 1:
The system performs preliminary actions by collecting and storing historical network performance data, present network conditions, and predicting future network states before actual network selection is needed. This allows the AI algorithm to make informed decisions based on pre-analyzed data, improving service quality without adding complex real-time processing requirements to the device.
Solution Approach 2:
The patent introduces an intermediary AI algorithm that acts as a mediator between raw network data and network selection decisions. This intermediary layer processes historical, present, and future data to generate optimized network selection recommendations, thereby improving quality of service while keeping the core device architecture relatively simple by offloading complex analysis to the AI intermediary.
2Reliability
If communication devices use AI algorithms with historical, present, and future data for network selection, then the quality of service is improved, but the device complexity increases
Solution Approach 1:
The network selection system is segmented into distinct functional components: historical data analysis module, present network condition monitoring module, future network prediction module, and AI-based decision-making module. This segmentation allows each component to handle specific tasks independently, improving overall system reliability through specialized processing while managing complexity by dividing the AI system into manageable, modular units.
Solution Approach 2:
The system performs preliminary data collection, processing, and storage of historical network performance information, current network conditions, and predicted future network states before actual network selection is required. This preliminary preparation reduces the computational burden during real-time decision-making, improving service quality while keeping instantaneous device complexity manageable.
3Measurement precision
If communication devices collect and analyze more network data (historical, present, future), then the network selection accuracy is improved, but the loss of time for data processing increases
Solution Approach 1:
The system performs preliminary data collection, processing, and storage of historical network performance information, current network conditions, and predicted future network states before actual network selection is required. This preliminary preparation reduces the computational burden during real-time decision-making, improving service quality while keeping instantaneous device complexity manageable.
Solution Approach 2:
The AI algorithm incorporates feedback mechanisms that continuously learn from past network selection outcomes and performance results. This feedback loop allows the system to refine its data processing efficiency over time, improving selection accuracy while optimizing processing speed by learning from historical patterns and reducing redundant computations.
Data Source
AI summary
A system, method, and computer program product are provided for selecting a communication network to utilize based on knowledge and at least one artificial intelligence (AI) algorithm. In operation, a user device identifies a plurality of communication networks to which to potentially connect. The user device accesses knowledge associated with the plurality of communication networks to determine a communication network to utilize. The knowledge includes information associated with historical data, present data, and future data. The user device selects the communication network to utilize based on the knowledge and at least one algorithm (e.g. an artificial intelligence algorithm, etc.). Moreover, the user device connects to the communication network for performing at least one activity.