Changeflow GovPing Telecom & Technology Methods and Systems of Predicting Total Loss Ev...
Routine Notice Added Draft

Methods and Systems of Predicting Total Loss Events

Favicon for changeflow.com ChangeBridge: Patent Apps - AI & Computing (G06N)
Published
Detected
Email

Summary

USPTO published patent application US20260091748A1 assigned to Cambridge Mobile Telematics Inc., covering machine learning methods for predicting total loss events. The system uses mobile device sensors to detect crash events and generates confidence scores for total loss predictions using multiple ML models. Application was filed December 9, 2025 and published April 2, 2026.

What changed

Cambridge Mobile Telematics Inc. filed patent application US20260091748A1 disclosing methods for predicting total loss events using machine learning. The system detects crash events through mobile device sensors, records sensor data, and generates feature vectors combining sensor data with additional data types. A first ML model is selected from multiple models based on available data types to generate a confidence score for total loss events.

Patent applications represent early-stage filings and do not impose immediate compliance obligations. R&D teams should monitor relevant patent filings in crash detection and insurance technology to identify emerging technologies and potential prior art. Legal and IP strategy teams may review for freedom-to-operate analysis or potential licensing considerations.

Archived snapshot

Apr 2, 2026

GovPing captured this document from the original source. If the source has since changed or been removed, this is the text as it existed at that time.

← USPTO Patent Applications

METHODS AND SYSTEMS OF PREDICTING TOTAL LOSS EVENTS

Application US20260091748A1 Kind: A1 Apr 02, 2026

Assignee

Cambridge Mobile Telematics Inc.

Inventors

Yuting Qi, Cornelius Young, Rizki Syarif, Burak Erem

Abstract

A mobile device detects a crash event using one or more sensors of a mobile device. The mobile device records a first set of data from the one or more sensors of the mobile device. The mobile device generates a first feature vector including the first set of data and available values for one or more additional data types. The mobile device executes a first machine-learning model selected from a plurality of machine-learning models based on the one or more additional data types for which there are available values to generate a first confidence of a total loss event.

CPC Classifications

B60R 21/013 G06N 5/04 G06N 20/00 G06Q 30/0278 G06Q 40/08 G07C 5/008 H04W 4/40 G06Q 10/20

Filing Date

2025-12-09

Application No.

19414201

View original document →

Get daily alerts for ChangeBridge: Patent Apps - AI & Computing (G06N)

Daily digest delivered to your inbox.

Free. Unsubscribe anytime.

About this page

What is GovPing?

Every important government, regulator, and court update from around the world. One place. Real-time. Free. Our mission

What's from the agency?

Source document text, dates, docket IDs, and authority are extracted directly from USPTO.

What's AI-generated?

The plain-English summary, classification, and "what to do next" steps are AI-generated from the original text. Cite the source document, not the AI analysis.

Last updated

Classification

Agency
USPTO
Published
April 2nd, 2026
Instrument
Notice
Legal weight
Non-binding
Stage
Draft
Change scope
Minor
Document ID
US20260091748A1

Who this affects

Applies to
Technology companies Insurers
Industry sector
5112 Software & Technology
Geographic scope
United States US

Taxonomy

Primary area
Intellectual Property
Operational domain
Legal
Topics
Artificial Intelligence Insurance Technology

Get alerts for this source

We'll email you when ChangeBridge: Patent Apps - AI & Computing (G06N) publishes new changes.

Optional. Personalizes your daily digest.

Free. Unsubscribe anytime.