Camera-Aware Storage Forecasting for Video Retention

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Solution Overview

Problem

Existing video surveillance systems face challenges in accurately predicting storage capacity depletion, leading to potential loss of video content or excessive cloud storage fees due to inaccurate historical pattern-based predictions.

Innovation Solution

A computing system predicts future storage capacity depletion by analyzing operating parameters of cameras and retention policies, generating alerts when capacity is nearing exhaustion, and optionally transferring content to alternative storage.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If historical pattern-based predictions are used to predict storage capacity depletion, then the system can generate storage capacity predictions, but the predictions become inaccurate when camera conditions or storage capacity change

Engineering Contradiction:

Improvestorage capacity prediction accuracyVSAvoidadaptability to changing camera conditions and storage capacity

Core Design Contradiction:

Measurement precisionVSAdaptability or versatility

Solution Approach 1:

The system dynamically adjusts prediction parameters based on real-time camera operating conditions and storage capacity changes. Instead of using static historical patterns, the system continuously updates its prediction model to reflect current system state, thereby maintaining accuracy under varying conditions.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system incorporates feedback mechanisms that monitor actual storage capacity consumption and camera performance in real-time. This feedback loop allows the prediction model to be continuously refined and adjusted, ensuring it remains accurate despite changes in camera conditions or storage capacity.

Inventive Principle:

Principle #23Feedback

2Quantity of substance

If local on-premises storage is used, then storage costs are reduced, but storage capacity is limited and video content can be lost when capacity runs out

Engineering Contradiction:

Improvestorage capacityVSAvoidvideo content retention reliability

Core Design Contradiction:

Quantity of substanceVSReliability

Solution Approach 1:

The system performs preliminary actions by predicting future storage capacity depletion before it occurs. This allows the system to proactively alert users or automatically transfer data to additional storage resources, preventing video content loss before it happens rather than reacting after capacity is exhausted.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system introduces an intermediary prediction and alert mechanism between the camera storage system and the user. This intermediary layer provides advance warning and enables proactive management of storage capacity, allowing users to take corrective actions before video content is lost.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Quantity of substance

If cloud-based storage is used, then storage capacity is increased, but storage costs increase significantly

Engineering Contradiction:

Improvestorage capacityVSAvoidstorage cost

Core Design Contradiction:

Quantity of substanceVSLoss of energy

Solution Approach 1:

Instead of continuously using expensive cloud storage capacity, the system employs partial action by utilizing local storage for the duration predicted before capacity depletion occurs. This approach minimizes the need for excessive cloud storage subscriptions by planning data retention locally for the anticipated retention period.

Inventive Principle:

Principle #16Partial or excessive action

Solution Approach 2:

The system performs preliminary prediction of when cloud storage capacity will be exhausted, allowing users to plan data retention strategies in advance. This enables optimization of cloud storage usage by only subscribing to additional capacity when actually needed, rather than continuously paying for excessive storage.

Inventive Principle:

Principle #10Preliminary action

4Reliability

If inaccurate storage capacity predictions are made, then users may pay for excessive cloud storage capacity, but video content loss risk increases

Engineering Contradiction:

Improvevideo content retentionVSAvoidstorage capacity utilization efficiency

Core Design Contradiction:

ReliabilityVSQuantity of substance

Solution Approach 1:

The system uses feedback from actual storage consumption patterns and camera performance to continuously refine predictions. This feedback mechanism ensures predictions become increasingly accurate over time, reducing both overpayment for cloud storage and the risk of video content loss.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS20250317534A1Storage management for a video surveillance system

Publication Date: 2025.10.09 GENETEC

AI summary

A video surveillance system comprising video content generated by a camera, a storage device, and a computing system adapted to receive the video content from the camera. The computing system adapted to store the video content in the storage device, determine whether the storage device will run out of storage capacity based on an operating parameter of the camera and a retention policy associated with the video content stored in the storage device, and generate an alert in response to determining that the storage device will run out of storage capacity.