Wearable Context Detection via Multi-Device Motion Correlation
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Solution Overview
Problem
Wearable computing devices, such as smartwatches, face limitations in performance and functionality due to their small size and limited power sources, which restricts their ability to provide rich, customizable displays with high energy efficiency.
Innovation Solution
A wearable computing device configured with a processor and a first accelerometer that determines motion indicators, collaborating with a mobile telephone's processor via a second accelerometer to execute context-specific actions based on user activity contexts, allowing for efficient and customizable displays without excessive power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If wearable computing devices incorporate more functionality and larger power sources, then performance and display capability are improved, but device size and weight increase
Solution Approach 1:
The system divides functionality between two devices: the wearable computing device handles motion sensing and context detection, while the mobile telephone handles computation-intensive tasks and displays. This segmentation allows the wearable to remain lightweight while the system as a whole provides rich functionality.
Solution Approach 2:
The mobile telephone serves multiple functions: it acts as a computation platform, display device, and communication hub for the wearable computing device. This multi-functionality reduces the need for the wearable to carry all capabilities independently.
2Use of energy by moving object
If wearable computing devices incorporate larger power sources, then energy availability is improved, but device size increases
Solution Approach 1:
The mobile telephone acts as an intermediary energy reservoir, providing additional power for context detection and processing tasks. The wearable maintains a small battery while leveraging the phone's power supply capability through wireless communication and coordinated operation.
Solution Approach 2:
The system performs computation partially on the wearable and partially on the mobile telephone. By offloading excessive computation to the phone, the wearable can use a smaller battery while still achieving the desired functionality through distributed processing.
3Speed
If wearable computing devices perform complex computation locally, then processing speed is improved, but power consumption increases
Solution Approach 1:
The system segments computation tasks between the wearable and mobile telephone based on their respective capabilities. The wearable performs simple motion detection and data preprocessing, while the phone handles complex analysis and context determination, optimizing the balance between speed and power consumption.
4Volume of moving object
If wearable computing devices are made smaller, then wearability is improved, but functionality is reduced
Solution Approach 1:
The mobile telephone provides universal functionality for the system, serving as computation platform, display, and communication device. This allows the wearable to be minimized in size while the phone compensates for reduced functionality through its own capabilities.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This solution enables wearable devices to provide context-specific information and actions while minimizing power usage, extending battery life and enhancing user experience through efficient computation and data exchange with mobile phones.
Implementation Method 1
a first accelerometer that determines a first motion indicator indicative of a motion of the wearable computing device
Implementation Method 2
a second motion indicator indicative of a motion of a mobile telephone communicatively coupled to the wearable computing device, the second motion indicator determined by a second accelerometer of the mobile telephone
Data Source
AI summary
Described systems and methods enable the detection of a user activity context indicative of a user's current activity, by correlating the motion of a wrist-worn device (e.g., watch) with the motion of a mobile telephone. Some embodiments further correlate motion data with a location indicator provided by the mobile telephone, and with a current time of the day. The watch and/or mobile telephone may switch to a context-specific operation mode in response to determining the user activity context.


