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Description
Azure IoT Edge is a comprehensive service that operates on the Azure IoT Hub platform. It allows you to deploy cloud-based workloads, artificial intelligence applications, Azure services, third-party tools, or custom business logic on Internet of Things (IoT) edge devices using standard container technology. By relocating specific workloads closer to the network edge, these devices can minimize their communication time with the cloud, respond more swiftly to changes in their local environment, and maintain functionality even during prolonged periods without internet access. You can implement models that have been developed and refined in the cloud directly on-site. For instance, when a predictive model is used on a factory camera for quality assurance and detects an anomaly, IoT Edge can initiate an alert, process the relevant data locally, or forward it to the cloud for more in-depth evaluation. Furthermore, your edge devices can be managed securely and effectively, ensuring reliable operation even in scenarios of limited or no connectivity. The device management feature of Azure IoT Edge automatically updates and synchronizes the current state of each device. This seamless integration fosters enhanced operational efficiency, enabling businesses to harness the full potential of their IoT solutions.
Description
The Internet of Things (IoT) encompasses billions of physical devices globally that are interconnected and actively gathering and sharing data. By leveraging IoT data alongside IBM Cloud® technologies, organizations can derive meaningful insights that enhance nearly every facet of their operations while also paving the way for innovative business models. Begin by linking your device to an IBM Cloud recipe, utilizing open and lightweight protocols like MQTT or HTTP for connectivity. Efficient management of connected devices allows applications to access both real-time and historical data. Secure APIs facilitate the integration of your applications with the data generated by these devices, enabling seamless interaction. You can develop analytical applications either within the IBM Cloud, on another cloud platform, or on your own servers. The IBM Watson IoT® Platform provides a straightforward method to connect, gather, and process IoT data quickly. Additionally, you can leverage the analytics service for effective visualization and AI-enhanced analytics in the cloud, leading to informed decision-making and operational efficiency. This integration ultimately transforms the way businesses operate and create value in the digital landscape.
API Access
Has API
API Access
Has API
Integrations
Azure IoT Hub
Azure Kinect DK
Azure Marketplace
Docker
IBM Cloud
IBM Cloud Messages for RabbitMQ
IBM Watson IoT Platform
Microsoft 365
Microsoft Azure
Microsoft Defender for Cloud
Integrations
Azure IoT Hub
Azure Kinect DK
Azure Marketplace
Docker
IBM Cloud
IBM Cloud Messages for RabbitMQ
IBM Watson IoT Platform
Microsoft 365
Microsoft Azure
Microsoft Defender for Cloud
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Microsoft
Founded
1975
Country
United States
Website
azure.microsoft.com/en-us/services/iot-edge/
Vendor Details
Company Name
IBM
Founded
1911
Country
United States
Website
www.ibm.com/cloud/internet-of-things
Product Features
IoT
Application Development
Big Data Analytics
Configuration Management
Connectivity Management
Data Collection
Data Management
Device Management
Performance Management
Prototyping
Visualization
Product Features
Data Analysis
Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics
IoT
Application Development
Big Data Analytics
Configuration Management
Connectivity Management
Data Collection
Data Management
Device Management
Performance Management
Prototyping
Visualization