Connected Vehicle Audiovisual Recording Memory Management
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Solution Overview
Problem
Connected vehicles face challenges in managing audiovisual recordings due to limited memory, requiring significant user interaction to preserve important recordings and risking loss of valuable footage as memory fills up.
Innovation Solution
An on-vehicle recording system that retrieves a user-defined profile from a cloud-based server to dynamically manage recording quality, upload recordings, and prioritize storage of important segments, using cellular and Wi-Fi connections to upload footage and maintain memory efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If continuous audiovisual recording is performed in a connected vehicle, then complete recording coverage is achieved, but memory capacity is quickly exhausted and valuable footage is lost
Solution Approach 1:
The system performs preliminary classification of recording segments by detecting events (collisions, sudden braking, airbag deployment) and marking them for preservation before memory becomes full. This advance identification ensures valuable footage is protected from overwriting before the memory capacity crisis occurs.
Solution Approach 2:
The system extracts and separates important recording segments from the continuous recording stream by identifying events and creating a distinct preserved category. These extracted segments are protected from the circular buffer overwriting mechanism that affects normal recording, effectively removing them from the memory capacity consumption cycle.
2Adaptability or versatility
If user interaction is required to preserve important recordings, then storage decisions can be customized, but ease of operation deteriorates and valuable footage may be lost
Solution Approach 1:
The system performs self-service by automatically detecting events (collisions, sudden braking, airbag deployment) and autonomously marking segments for preservation without requiring user interaction. The system serves itself by making intelligent storage decisions based on event detection, eliminating the need for manual user intervention while maintaining adaptability through configurable event thresholds.
Solution Approach 2:
The system implements feedback by continuously monitoring vehicle sensors (accelerometers, collision detectors, airbag status) and using this information to dynamically adjust recording preservation decisions. This closed-loop feedback mechanism allows the system to adapt to different driving conditions and automatically preserve important footage without user input.
3Duration of action of moving object
If memory is allocated for continuous recording, then recording duration is extended, but memory efficiency deteriorates and storage is wasted on non-important footage
Solution Approach 1:
The system applies local quality by differentiating storage allocation for different types of recording segments. Important segments identified through event detection receive prioritized preservation and protection from overwriting, while normal non-event segments are subject to standard circular buffer management. This localized quality approach optimizes memory efficiency by concentrating storage resources on valuable footage.
Solution Approach 2:
The system changes parameters by dynamically adjusting the preservation status of recording segments based on detected events. When events are detected (collisions, sudden braking), the system changes the segment status from 'overwritable' to 'preserved', fundamentally altering the memory management behavior for those segments and extending their retention duration without permanently increasing overall memory allocation.
Data Source
AI summary
Methods, apparatus, systems and articles of manufacture disclosed herein may be used to manage audiovisual recording in a connected vehicle. An example disclosed method includes accessing a profile having a recording parameter and a first quality selected by a user from a recording server. The example method also includes comparing a reading from a vehicle sensor to the recording parameter in the profile to determine whether to record a video. Additionally, the example method includes, in response to determining to record the video, storing the video using the first quality to a memory located in the vehicle.