GPS-Based Event Video Collection for Accident Evidence
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Solution Overview
Problem
Insurance companies face challenges in locating and interviewing witnesses to vehicle accidents, as witness testimonies can be costly, time-consuming, and inaccurate, while video data from dash cameras and smartphones is often overlooked.
Innovation Solution
A system that utilizes GPS data to identify potential witnesses and their video recordings, aggregates video data from various sources using machine learning, and incentivizes users to upload relevant footage to resolve disputes efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If witness interviews are conducted to gather accident information, then information accuracy may improve, but time consumption and cost increase
Solution Approach 1:
The patent uses video recordings from dash cameras and smartphones as copies of the actual accident events. These visual recordings provide objective documentation of what occurred, eliminating the need for subjective witness testimonies. The system aggregates these video copies from multiple sources to create a comprehensive record, which is both accurate and time-efficient compared to interviewing multiple witnesses.
Solution Approach 2:
The patent replaces the mechanical process of manually interviewing witnesses with an automated system that collects, aggregates, and analyzes video data from various sources. The system automatically identifies relevant videos using machine learning algorithms and compiles them into a comprehensive accident record, eliminating the time-consuming manual interview process while maintaining high accuracy.
2Reliability
If police reports are purchased to obtain accident information, then reliable information is obtained, but cost increases
Solution Approach 1:
The patent segments the information collection process by gathering video data from multiple independent sources (dash cameras, smartphones, security cameras) rather than relying on a single police report. Each source provides a specific perspective or angle of the accident, and the system aggregates these segmented views to create a comprehensive and reliable picture of what occurred, often at lower cost than purchasing complete police reports.
Solution Approach 2:
The patent creates a universal system that collects video data from multiple types of devices and sources simultaneously. This multi-functional approach allows the system to gather accident information from dash cameras, mobile phones, security cameras, and other sources, providing reliable information without being dependent on a single expensive police report service.
3Loss of information
If multiple video sources are aggregated to get comprehensive event views, then information completeness improves, but system complexity increases
Solution Approach 1:
The patent introduces a central aggregation system that acts as an intermediary between multiple video sources and the final accident record. This intermediary system automatically collects videos from dash cameras, smartphones, and other sources, processes them through machine learning algorithms to identify relevance, and compiles them into a unified comprehensive record, thereby managing complexity centrally rather than requiring complex integration at each source.
Solution Approach 2:
The patent uses machine learning algorithms that analyze video parameters (such as timestamp, location, visual content) to automatically filter and select relevant videos from the vast amount of data collected. By changing the approach from manual review of all videos to automated parameter-based filtering, the system achieves information completeness while managing complexity through intelligent automation rather than complex manual processes.
Data Source
AI summary
Methods and systems can identify and request video data and information associated with an event. An event location and time associated with the event can be determined. The event can comprise damage to property or injury to a person. A geographic range of interest associated with the event location and a time duration of interest associated with the event time can be determined. One or more users who are determined to have been at or near the event location at the event time can be automatically identified. A request for at least one of information or video data from the geographic range and time duration of interest can be transmitted to the one or more identified users.