View source for 18462324. SUBMERSION DETECTION, UNDERWATER DEPTH AND LOW-LATENCY TEMPERATURE ESTIMATION USING WEARABLE DEVICE simplified abstract (Apple Inc.)

=SUBMERSION DETECTION, UNDERWATER DEPTH AND LOW-LATENCY TEMPERATURE ESTIMATION USING WEARABLE DEVICE=


==Organization Name==

[[:Category:Apple Inc.|Apple Inc.]]


[[Category:Apple Inc.]]

==Inventor(s)==

[[:Category:Stephen P. Jackson of San Francisco CA (US)|Stephen P. Jackson of San Francisco CA (US)]][[Category:Stephen P. Jackson of San Francisco CA (US)]]

[[:Category:Ti-Yen Lan of Palo Alto CA (US)|Ti-Yen Lan of Palo Alto CA (US)]][[Category:Ti-Yen Lan of Palo Alto CA (US)]]

[[:Category:Yi Wen Liao of San Jose CA (US)|Yi Wen Liao of San Jose CA (US)]][[Category:Yi Wen Liao of San Jose CA (US)]]

[[:Category:Alexandru Popovici of Santa Clara CA (US)|Alexandru Popovici of Santa Clara CA (US)]][[Category:Alexandru Popovici of Santa Clara CA (US)]]

[[:Category:Igor Tchertkov of Los Gatos CA (US)|Igor Tchertkov of Los Gatos CA (US)]][[Category:Igor Tchertkov of Los Gatos CA (US)]]

[[:Category:Rose M. Wahlin of San Francisco CA (US)|Rose M. Wahlin of San Francisco CA (US)]][[Category:Rose M. Wahlin of San Francisco CA (US)]]

[[:Category:Natisa Jeyakanthan of Mountain View CA (US)|Natisa Jeyakanthan of Mountain View CA (US)]][[Category:Natisa Jeyakanthan of Mountain View CA (US)]]

[[:Category:Amit K. Jain of Fremont CA (US)|Amit K. Jain of Fremont CA (US)]][[Category:Amit K. Jain of Fremont CA (US)]]

[[:Category:Kenneth M. Lee of Morgan Hill CA (US)|Kenneth M. Lee of Morgan Hill CA (US)]][[Category:Kenneth M. Lee of Morgan Hill CA (US)]]

==SUBMERSION DETECTION, UNDERWATER DEPTH AND LOW-LATENCY TEMPERATURE ESTIMATION USING WEARABLE DEVICE - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18462324 titled 'SUBMERSION DETECTION, UNDERWATER DEPTH AND LOW-LATENCY TEMPERATURE ESTIMATION USING WEARABLE DEVICE

==Simplified Explanation==

The patent application describes methods for detecting submersion, estimating underwater depth, and low-latency temperature estimation using wearable devices.

* Method involves determining vertical accelerations from both inertial sensor and pressure data, calculating a feature based on the correlation between the two sets of accelerations, and using a machine learning model to determine if the device is submerged in water.
* Another method includes determining the submersion state of the device, and if submerged, estimating water temperature based on ambient water temperature, a temperature error lookup table, and the rate of change of ambient water temperature.

== Potential Applications ==
This technology can be applied in various fields such as:
* Water sports and activities
* Marine research
* Environmental monitoring

== Problems Solved ==
This technology addresses issues such as:
* Accurate submersion detection
* Real-time temperature estimation underwater
* Low-latency data processing

== Benefits ==
The benefits of this technology include:
* Improved safety for water-related activities
* Enhanced data collection for marine research
* Efficient environmental monitoring in water bodies

== Potential Commercial Applications ==
* "Submersion Detection and Temperature Estimation Technology for Wearable Devices


==Original Abstract Submitted==

Embodiments are disclosed for submersion detection and underwater depth and low-latency temperature estimation. In an embodiment, a method comprises: determining a first set of vertical accelerations obtained from an inertial sensor of a wearable device; determining a second set of vertical accelerations obtained from pressure data; determining a first feature associated with a correlation between the first and second sets of vertical accelerations; and determining that the wearable device is submerged or not submerged in water based on a machine learning model applied to the first feature. In another embodiment, a method comprises: determining a submersion state of a wearable device; and responsive to the submersion state being submerged, computing a forward estimate of water temperature based on measured ambient water temperature at the water surface, a temperature error lookup table, and a rate of change of the ambient water temperature.



[[Category:G01C21/16]]