USE CASE
Enabling Computer Vision at the Edge
Accelerate computer vision deployments at the edge with a secure, scalable platform that simplifies AI model management and orchestration across diverse hardware.
Streamline Computer Vision Deployments with Simplified AI Model Management and Orchestration
Accelerate Computer Vision Rollouts
Secure Camera Data Processing
Leverage Diverse and Underpowered Hardware
Scale Model Deployments Across Variable Connectivity
Computer Vision is Transformative and Complex
The convergence of artificial intelligence and edge computing is transforming industries by enabling real-time decision-making and smarter operations. Computer vision, the technological capability that allows computers to capture and analyze images and videos at the edge, enables several use cases for fleet management, including predictive maintenance, object or defect detection, retail shrinkage reduction, worker safety monitoring, and quality control. However, deploying, monitoring, and orchestrating computer vision Al models at the edge introduces complex challenges from limited computing resources and dealing with a manual, time-intensive deployment process, to managing large-scale, distributed systems securely and efficiently.
How ZEDEDA Simplifies Computer Vision Projects
ZEDEDA’s edge computing platform provides a unified solution for deploying, orchestrating, and managing computer vision software, hardware and supporting services at the edge. It addresses the complex challenges of deploying and managing computer vision AI models at the edge, including limited computing resources, security, and connectivity. ZEDEDA supports large-scale zero-touch deployments leveraging a Zero Trust security model, and simplifies management through a unified interface. This reduces hardware and operational costs and centralizes management across distributed environments.
Accelerate Computer Vision Rollouts
- Eliminate manual processes with pre-configured software and hardware to reduce deployment time.
- Reduce deployment time with automated provisioning and configuration of devices.
- Deploy and manage devices remotely from a single location.
- Support camera data contextualization at the edge without having to deploy additional, dedicated systems.
Secure Camera Data Processing
- Zero Trust security model protects against cyber threats.
- Protect against unauthorized access with strict device authentication and authorization mechanisms. Protect IP from tampering or theft.
- Protect data and communications with secure communication channels and data encryption, in-flight and at rest.
- Maintain the integrity of computer vision systems in the face of digital and physical security threats.
Leverage Diverse and Underpowered Hardware
- Lower deployment costs and simplify management by abstracting heterogeneous and constrained hardware.
- Support and share GPUs, including NVIDIA Jetson-based hardware.
- Manage all edge devices from a single pane of glass.
- Ensure device health through real-time monitoring and health checks.
- Simplify software maintenance with automated software updates and patching.
Scale Model Deployments Across Variable Connectivity
- Supports large-scale deployments and efficient management of distributed systems, even with poor and low bandwidth connections.
- Handle large deployments with scalable architecture supporting thousands of distributed edge nodes.
- Automated device onboarding and provisioning.
- Manage distributed systems effectively with centralized management and orchestration capabilities.
- Enable diverse connectivity options, e.g., 2G, 4G, 5G, cable, satellite, and microwave.
Revolutioning Rail Freight
Learn how this Class I railroad operator relies on ZEDEDA to meet new federal railway safety regulations, deploying computer vision and AI inference technology on 20,000 edge nodes distributed over thousands of miles of tracks.
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