CRASH DETECTION ON MOBILE DEVICE

Simplified Explanation: The patent application discusses crash detection on mobile devices using sensor data and machine learning models to determine severe vehicle crashes.

Sensor data from multiple modalities is used to detect a crash event on the device.
Multimodal features, including rotation rate, are extracted from the sensor data.
Machine learning models analyze the multimodal features to compute crash decisions.
A severity model is applied to determine if a severe vehicle crash has occurred involving the device.

Key Features and Innovation:

Crash detection on mobile devices using sensor data and machine learning models.
Multimodal features, including rotation rate, are extracted and analyzed.
Determination of severe vehicle crashes based on computed crash decisions and a severity model.

Potential Applications: This technology can be applied in various industries such as automotive, healthcare, and insurance for real-time crash detection and emergency response.

Problems Solved: This technology addresses the need for accurate and timely crash detection on mobile devices to improve emergency response and safety measures.

Benefits:

Enhanced safety measures through real-time crash detection.
Improved emergency response times.
Potential reduction in the severity of vehicle crashes.

Commercial Applications: Title: Mobile Device Crash Detection Technology for Enhanced Safety Measures This technology can be utilized by automotive companies, insurance providers, and emergency response services to improve safety measures and response times in the event of a crash.

Prior Art: Prior research in the field of crash detection on mobile devices includes studies on sensor data analysis and machine learning algorithms for real-time event detection.

Frequently Updated Research: Ongoing research in the field focuses on improving the accuracy and efficiency of crash detection algorithms on mobile devices through advanced sensor technologies and machine learning techniques.

Questions about Mobile Device Crash Detection Technology: 1. How does this technology differentiate between a severe vehicle crash and a minor incident? 2. What are the potential challenges in implementing this technology on a large scale?

Original Abstract Submitted

embodiments are disclosed for crash detection on one or more mobile devices (e.g., smartwatch and/or smartphone. in some embodiments, a method comprises: detecting a crash event on a crash device; extracting multimodal features from sensor data generated by multiple sensing modalities of the crash device; computing a plurality of crash decisions based on a plurality of machine learning models applied to the multimodal features, wherein at least one multimodal feature is a rotation rate about a mean axis of rotation; and determining that a severe vehicle crash has occurred involving the crash device based on the plurality of crash decisions and a severity model.

Apple inc. (20240329277). CRASH DETECTION ON MOBILE DEVICE simplified abstract

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CRASH DETECTION ON MOBILE DEVICE

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CRASH DETECTION ON MOBILE DEVICE - A simplified explanation of the abstract

Original Abstract Submitted

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