Multi-Activity Platform Data Normalization
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Solution Overview
Problem
Existing fitness and athletic activity tracking systems are limited by the inability to seamlessly integrate and compare data from different types of activity monitoring devices, which are often incompatible due to varying sensors, calibration, and data recording protocols, leading to inaccurate performance comparisons and the need for users to view data across multiple platforms.
Innovation Solution
A multi-activity platform and system that aggregates and processes data from various devices, allowing users to view activity data in a unified format, normalize metrics, and set goals regardless of the device or activity type, using a shared framework for interoperability between devices and systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If activity monitoring devices use different sensors, calibration methods, and data recording protocols, then each device can be optimized for specific activities, but the devices become incompatible and cannot seamlessly integrate data
Solution Approach 1:
The patent introduces a remote server as an intermediary component that receives activity data from multiple types of monitoring devices, normalizes the data into a common format, and stores it in a centralized database. This server acts as a mediator between devices with different protocols and the user interface, enabling seamless integration without requiring the devices themselves to be compatible with each other.
Solution Approach 2:
The system transforms activity data parameters from various device-specific formats into a standardized set of parameters. The normalization process converts different measurement units, calibration methods, and data structures into a unified representation, allowing the system to handle diversity in device specifications while presenting consistent data to users.
2Adaptability or versatility
If users need to view data from multiple device types, then comprehensive tracking is possible, but users must access multiple platforms increasing the difficulty of operation
Solution Approach 1:
The patent merges the functionality of multiple separate data platforms into a single unified interface. The remote server consolidates data from various device types and the user accesses all this data through one website or application, eliminating the need to switch between different platforms and simplifying the user experience.
Solution Approach 2:
The system creates a universal interface that can display and interact with data from any type of activity monitoring device. The standardized data format serves as a universal language that enables the same user interface to handle diverse data sources, making the system multi-functional and device-agnostic.
3Adaptability or versatility
If goals are limited to single activity types, then performance measurement is simplified, but users are restricted from pursuing multi-activity fitness objectives
Solution Approach 1:
The system segments activity data into distinct activity types while maintaining the ability to aggregate them. Users can define goals for specific activities (e.g., running distance) while the system automatically categorizes and tracks different activity types separately, then allows combination of these segmented data toward unified goals when needed.
Solution Approach 2:
The goal tracking system is made dynamic and adaptable. Users can create goals that are specific to certain activity types or general goals that accept data from multiple activity types. The system automatically adjusts which data sources are relevant based on the goal definition, providing flexibility without requiring complex manual configuration.
Data Source
AI summary
A multi-activity system may be configured to receive, upload, synchronize and process data for a variety of different activity types and/or recorded using multiple types of activity monitoring devices. In one example, an application interface may be defined with a multiple functions that are each useable by various types of devices and for processing multiple types of data. Additionally or alternatively, data for different activity types and/or recorded using different types of monitoring devices may be processed differently. Synchronization of data may further be handled on a device-by-device basis, device-type basis and/or activity-type basis using various tracking parameters.