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Average Ratings 0 Ratings
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
KINEXON collects real-time localization information and converts it into impactful actions for various sectors, including industry, sports, and entertainment. Unlock insights that were previously out of reach by utilizing our advanced technology, allowing you to turn data into strategic advantages. Are you aware that you can enhance operational efficiency by harnessing real-time location data from interconnected assets for applications like automated order processing, quality assurance, or inventory restocking? By automating processes that involve numerous moving assets, you can greatly reduce the risk of human error and the burden of time-consuming manual operations, leading to heightened overall efficiency. With millions of containers utilized globally in manufacturing, poor management of these assets can lead to significant waste of both time and financial resources. Implementing automated container management systems, which rely on accurate RTLS data regarding container locations and status on the production floor, significantly boosts transparency and utilization of containers, ultimately optimizing operations. Moreover, this level of efficiency can lead to a more streamlined workflow and improved productivity across the board.
API Access
Has API
API Access
Has API
Integrations
Azure IoT Hub
Azure Kinect DK
Azure Marketplace
Docker
Microsoft 365
Microsoft Azure
Microsoft Defender for Cloud
NVIDIA DRIVE
SAP Cloud Platform
Smartabase
Integrations
Azure IoT Hub
Azure Kinect DK
Azure Marketplace
Docker
Microsoft 365
Microsoft Azure
Microsoft Defender for Cloud
NVIDIA DRIVE
SAP Cloud Platform
Smartabase
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
KINEXON
Founded
2012
Country
Germany
Website
kinexon.com
Product Features
IoT
Application Development
Big Data Analytics
Configuration Management
Connectivity Management
Data Collection
Data Management
Device Management
Performance Management
Prototyping
Visualization
Product Features
IoT
Application Development
Big Data Analytics
Configuration Management
Connectivity Management
Data Collection
Data Management
Device Management
Performance Management
Prototyping
Visualization