Unified Data Stream Synthesis for Multi-Device Activity Tracking
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Solution Overview
Problem
Users face challenges in reconciling conflicting data from multiple portable biometric monitoring devices, which can provide inaccurate or overlapping information about user activities and environmental parameters, making it difficult to determine the most accurate data source.
Innovation Solution
A method and system for consolidating overlapping data streams from multiple devices into a unified data stream, using a cloud-based server or local device to receive, parse, and synthesize activity data from various sources, prioritizing data based on accuracy, precision, and user preferences, and storing the unified data for presentation to the user.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple portable biometric monitoring devices are used to track user activities, then data coverage and monitoring capability are improved, but data accuracy and reliability deteriorate due to conflicting information from different devices
Solution Approach 1:
The patent introduces a server as an intermediary component that receives data from multiple portable devices, processes the conflicting information using reconciliation algorithms, and provides unified accurate data to users. The server acts as a mediator that resolves conflicts between devices without requiring changes to the devices themselves.
Solution Approach 2:
The server performs multiple functions including data collection from various device types, data validation, conflict resolution, and result presentation. This multi-functional approach allows the system to handle diverse data sources while maintaining unified output quality.
2Quantity of substance
If data from multiple devices is combined to provide comprehensive activity information, then data completeness is improved, but data consistency deteriorates due to overlapping and conflicting measurements
Solution Approach 1:
The server serves as an intermediary that standardizes data from multiple sources into a consistent format, applying reconciliation rules to ensure data consistency while maintaining completeness. It processes overlapping measurements and selects or combines data to maintain both completeness and consistency.
Solution Approach 2:
The system changes the state of data by transforming raw measurements from multiple devices into reconciled standardized data. This parameter transformation includes validating data ranges, applying correction factors, and converting different measurement formats into a unified consistent representation.
3Reliability
If multiple data streams are processed and reconciled to ensure accuracy, then data reliability is improved, but system complexity increases due to the need for data synthesis and conflict resolution
Solution Approach 1:
The server concentrates the complexity of data reconciliation in a single intermediary component, allowing the portable devices to remain simple data collection units. This centralizes the complex processing logic while keeping the client devices simple and manageable.
Solution Approach 2:
The system employs automated self-service mechanisms through algorithms that automatically detect conflicts, validate data quality, and reconcile measurements without requiring manual intervention. This automation handles the complexity internally while presenting simple reliable results to users.
4Measurement precision
If data from multiple sources is synthesized into a unified stream, then data quality is improved, but information loss occurs during the reconciliation and selection process
Solution Approach 1:
The server transforms raw data parameters into standardized quality-assured parameters through validation and reconciliation processes. This parameter transformation improves measurement precision by filtering out erroneous data while converting diverse formats into a unified precise representation.
Solution Approach 2:
The system implements feedback mechanisms where the server communicates with devices to request clarification or additional data when conflicts are detected. This feedback loop allows the system to recover potentially useful information that might otherwise be lost during reconciliation.
Data Source
AI summary
Methods, devices, and computer programs are presented for creating a unified data stream from multiple data streams acquired from multiple devices. One method includes an operation for receiving activity data streams from the devices, each activity data stream being associated with physical activity data of a user. Further, the method includes an operation for assembling the unified activity data stream for a period of time. The unified activity data stream includes data segments from the data streams of at least two devices, and the data segments are organized time-wise over the period of time.