Camera Security Event Detection With Buffered Alert Reporting
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Solution Overview
Problem
Existing video collection and sharing platforms, particularly in vehicles, lack automatic detection and reporting of high-priority events such as burglaries or vehicle break-ins, and are prone to data loss when connectivity is disrupted.
Innovation Solution
A video data collection and sharing platform that utilizes sensor modules to detect high-priority events, such as burglaries or thefts, by analyzing inputs like digital sound signatures and accelerometer signals, and communicates alerts through a network connection to a remote server, generating video clips and notifying users within a specified time limit.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If video data is continuously recorded and stored locally, then data availability is improved, but device storage capacity is consumed and data loss risk increases when connectivity is disrupted
Solution Approach 1:
The system performs preliminary actions by continuously recording video data into local buffer memory before connectivity is needed. This ensures that video data is already captured and stored locally, making it immediately available for transmission when connectivity is restored or for local playback, thus improving data availability without requiring large long-term storage capacity.
Solution Approach 2:
The system implements a buffer management mechanism where video data is continuously written to a circular buffer in local memory. When the buffer is full, older data is automatically overwritten (discarded) until new data can be transmitted. This allows the system to maintain a rolling window of recent video data, ensuring recent events are captured while managing limited storage capacity efficiently.
2Reliability
If video data is transmitted continuously to remote server, then data synchronization is improved, but network bandwidth is consumed and data loss risk increases during connectivity disruptions
Solution Approach 1:
The system transmits video data to the remote server in periodic batches rather than continuously. Video data is accumulated in the local buffer and transmitted together when connectivity is available. This periodic transmission approach reduces network bandwidth consumption compared to continuous streaming while maintaining data synchronization by regularly updating the server with the latest video data.
Solution Approach 2:
The system prepares video data for transmission by buffering it locally before actual network transmission occurs. This preliminary buffering action allows the system to accumulate data and transmit it efficiently when network conditions permit, reducing the impact on network bandwidth while ensuring data is ready for synchronization when connectivity is available.
3Measurement precision
If automatic event detection is implemented, then high-priority event identification is improved, but processing time is increased and false positives may occur
Solution Approach 1:
The system extracts and analyzes only specific sensor inputs that are relevant to detecting high-priority events, such as glass breakage sound patterns, acceleration thresholds, or motion detection triggers. By focusing on extracting only the critical features from sensor data rather than processing all video data uniformly, the system improves event detection accuracy while minimizing processing time and avoiding false positives from irrelevant data.
4Reliability
If video data is buffered in local memory, then data retention during connectivity loss is improved, but memory capacity is consumed and data transmission delay increases
Solution Approach 1:
The system buffers only a partial amount of video data in local memory - specifically, a rolling buffer of recent video data rather than storing all historical data. This partial buffering approach ensures that the most recent and potentially most valuable video data is retained during connectivity loss, while limiting memory consumption and reducing the amount of data that needs to be transmitted when connectivity is restored, thereby minimizing transmission delay.
Data Source
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AI summary
A video data collection and sharing platform is provided capable of detecting high-priority events and communicating alerts to users. A high-priority event is captured by a video capturing device with one or more sensor modules, including one or more video cameras for recording video footage. A network connection is established and input from one or more sensor modules is received. The input includes image data from the one or more video cameras. An input from the one or more sensor modules is analyzed to determine a potential high-priority event. Upon determining a potential high-priority event, conditions of the network connection are measured and an amount of data to be transmitted to a remote server through the network connection is determined based, at least in part, on the measured conditions of the network connection.