Cloud-Native NVR with AI Video Analytics and Universal Camera Integration
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Solution Overview
Problem
Existing NVR systems face limitations in compatibility with different IP camera manufacturers, processing power for advanced video analytics, and scalability, leading to increased costs and complexity in surveillance systems.
Innovation Solution
A novel NVR design that incorporates universal camera-integration capabilities, an intelligent video processing module using AI-powered machine learning models, and direct cloud access, enabling seamless integration with various IP cameras, optimized video processing, and efficient cloud storage utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional NVRs store video footage locally on built-in hard drives or connected NAS devices, then data security and access control are improved, but scalability and flexibility in access are worsened
Solution Approach 1:
The patent transitions from a single-dimension local storage architecture to a multi-dimensional architecture that combines local storage with cloud storage capabilities. The NVR system can simultaneously maintain local copies of video footage while syncing selected clips to cloud storage, enabling both secure local access and flexible remote access through multiple dimensions of data storage and retrieval.
2Reliability
If NVRs are constrained to work with IP cameras from the same manufacturer, then system compatibility and support are improved, but versatility and cost-effectiveness are worsened
Solution Approach 1:
The patent implements a universal camera-integration module that can work with IP cameras from multiple manufacturers simultaneously. The module includes a pool of communication protocols that can be activated based on the camera manufacturer, allowing the NVR to seamlessly support cameras from different vendors without requiring separate systems or proprietary configurations.
Solution Approach 2:
The camera-integration module acts as an intermediary layer between the NVR and various IP camera manufacturers. It includes a pool of communication protocols that mediate between the NVR's core functionality and the diverse protocols used by different camera manufacturers, enabling compatibility without direct manufacturer-specific integration.
3Device complexity
If NVR processors have limited capabilities, then device complexity and cost are improved, but ability to perform computationally intensive tasks such as video compression and advanced video analytics are worsened
Solution Approach 1:
The patent introduces an AI module as an intermediary that handles computationally intensive video analytics tasks. The AI module receives video data from the camera-integration module, performs advanced analysis such as object detection and recognition, and generates video clips of interest. This intermediary architecture allows the NVR to perform sophisticated analytics without requiring the main processor to handle all computational loads directly.
4Adaptability or versatility
If IP cameras upload footage directly to cloud services, then local storage requirements are reduced, but bandwidth usage increases and control over video data storage is lost
Solution Approach 1:
The patent extracts only the necessary video data for cloud upload by implementing AI-powered selection at the NVR level. The AI module analyzes video footage and identifies only the clips of interest that meet specific criteria, extracting these selected clips for cloud upload rather than transmitting all raw footage. This selective extraction significantly reduces bandwidth consumption while maintaining cloud storage benefits.
Solution Approach 2:
The NVR system performs self-service by automatically analyzing video footage through the AI module and autonomously determining which clips should be uploaded to cloud storage. The system independently makes decisions about data selection, compression, and upload timing without requiring manual intervention, thereby optimizing bandwidth usage and maintaining control over video data storage.
Data Source
AI summary
This application describes an AI-powered Cloud-native Network Video Recorder (NVR) apparatus. This apparatus features multiple Power over Ethernet (PoE) ports, processors, computer-readable memories, and firmware implementing a camera-integration module, an Artificial Intelligence (AI) module, and a cloud-access module. The camera-integration module enables efficient connection and video data reception from heterogeneous cameras. The AI module processes the video data, identifying and generating clips of interest, optimizing surveillance efficiency. Finally, the cloud-access module facilitates the uploading of these clips to cloud storage, ensuring accessible and secure data management. This innovative NVR apparatus enables users to deploy a cloud-native video surveillance system using existing camera devices, significantly lowering the cost of adoption.