20240085185.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

apple inc.

Inventor(s)

Stephen P. Jackson of San Francisco CA (US)

Ti-Yen Lan of Palo Alto CA (US)

Yi Wen Liao of San Jose CA (US)

Alexandru Popovici of Santa Clara CA (US)

Igor Tchertkov of Los Gatos CA (US)

Rose M. Wahlin of San Francisco CA (US)

Natisa Jeyakanthan of Mountain View CA (US)

Amit K. Jain of Fremont CA (US)

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 20240085185 titled 'SUBMERSION DETECTION, UNDERWATER DEPTH AND LOW-LATENCY TEMPERATURE ESTIMATION USING WEARABLE DEVICE

Simplified Explanation

The abstract describes a patent application for submersion detection, underwater depth estimation, and low-latency temperature estimation using a wearable device.

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

Potential Applications

This technology could be used in various industries such as sports and fitness, marine exploration, and environmental monitoring.

Problems Solved

This technology solves the problem of accurately detecting submersion of a wearable device and estimating water temperature in real-time.

Benefits

The benefits of this technology include improved safety for water-related activities, enhanced data collection for research purposes, and better monitoring of environmental conditions.

Potential Commercial Applications

Potential commercial applications of this technology include smartwatches for swimmers, fitness trackers for water sports enthusiasts, and environmental monitoring devices for researchers.

Possible Prior Art

One possible prior art could be existing wearable devices with water resistance features but lacking the specific submersion detection and temperature estimation capabilities described in this patent application.

How does this technology impact battery life of the wearable device?

The abstract does not mention how the implementation of these features may affect the battery life of the wearable device. This is an important consideration as users would want to know if there are any trade-offs in terms of battery usage.

Are there any limitations to the accuracy of the temperature estimation in different water conditions?

The abstract does not address the potential limitations of the temperature estimation method in varying water conditions such as extreme temperatures or different water compositions. Understanding the accuracy of the estimates in different scenarios is crucial for the practical application of this technology.

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.