Apple inc. (20240097470). OPTIMIZING BATTERY CHARGING WITH SYNCHRONIZED CONTEXT DATA simplified abstract
Contents
- 1 OPTIMIZING BATTERY CHARGING WITH SYNCHRONIZED CONTEXT DATA
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 OPTIMIZING BATTERY CHARGING WITH SYNCHRONIZED CONTEXT DATA - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
OPTIMIZING BATTERY CHARGING WITH SYNCHRONIZED CONTEXT DATA
Organization Name
Inventor(s)
Gina B. Lu of San Francisco CA (US)
Kartik R. Venkatraman of San Francisco CA (US)
Aaron Cotter of San Francisco CA (US)
Alexander D. Palmer of San Jose CA (US)
OPTIMIZING BATTERY CHARGING WITH SYNCHRONIZED CONTEXT DATA - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240097470 titled 'OPTIMIZING BATTERY CHARGING WITH SYNCHRONIZED CONTEXT DATA
Simplified Explanation
The abstract describes a patent application for an electronic device with a power system that can charge the battery based on synchronized context data received from other devices associated with the user.
- The processor of the electronic device receives synchronized context data from other devices.
- Based on the synchronized context data, the processor determines one or more battery charging intervals.
- The power system of the device then charges the battery from an external power source during the identified intervals.
- A machine learning model is used to determine the battery charging intervals.
- The synchronized context data can indicate the user's location.
- If the user is at a different location than the device, the charging intervals are determined based on the expected time for the user to return.
Potential Applications
This technology could be applied in smart devices, wearables, and IoT devices to optimize battery charging based on user behavior and location.
Problems Solved
This technology solves the problem of inefficient battery charging by adapting the charging intervals based on user context and behavior.
Benefits
The benefits of this technology include improved battery life, convenience for users, and optimized power management for electronic devices.
Potential Commercial Applications
Commercial applications of this technology could include smart home devices, fitness trackers, and mobile devices with enhanced battery management features.
Possible Prior Art
One possible prior art could be smartwatches or fitness trackers that adjust battery charging based on user activity levels or location data.
Unanswered Questions
How does the device prioritize charging intervals when multiple users are involved?
The abstract does not specify how the device handles charging intervals when multiple users are associated with the device. This could be a potential area for further development and clarification in the patent application.
What security measures are in place to protect the synchronized context data exchanged between devices?
The abstract does not mention any security measures to protect the synchronized context data shared between devices. Ensuring the privacy and security of this data could be a crucial aspect to address in the implementation of this technology.
Original Abstract Submitted
an electronic device can include a power system including a battery and a processor programmed to: receive synchronized context data from one or more other devices associated with a user of the device, determine, at least in part based on the synchronized context data, one or more battery charging intervals, and operate the power system to charge the battery from the external power source during the identified one or more battery charging intervals. the processor can be programmed to determine the one or more battery charging intervals using a machine learning model. the synchronized context data can provide indication of the user's location. if the synchronized context data indicates that the user is at a different location than the device, the one or more battery charging intervals determined based at least in part on an expected time for the user to return to the location of the device.
