Computer Vision
Enabling Computer Vision at the Edge
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, which allows computers to capture and analyze images and videos, 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 manual, time-intensive deployment processes, to managing large-scale, distributed systems securely and efficiently.
ZEDEDA Simplifies Your Computer Vision Projects
ZEDEDA’s edge intelligence 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, 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.
- Reduce deployment time with automated provisioning and configuration of devices.
- Deploy and manage devices and AI models remotely from a single location.
- Support camera data contextualization at the edge without additional dedicated systems.
Secure Camera Data Processing
- Protect against cyber threats with a Zero Trust security model.
- Guard against unauthorized access with strict device authentication and authorization.
- Protect IP from tampering or theft.
- Protect data and communications with secure 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
- Eliminate hardware complexity, reducing deployment costs and simplifying management.
- Support and share GPUs, including NVIDIA Jetson-based hardware.
- Manage edge devices from a single pane of glass.
- Ensure device health through real-time monitoring and health checks.
- Simplify software lifecycle maintenance with automated software updates and patching.
Scale AI Deployments Across Any Network
- Supports large-scale deployments and efficient management of distributed systems, even with poor and low bandwidth connections.
- Automated Zero Touch 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.
Five Things to Know about Computer Vision at the Edge
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