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What is Data Collection Core?

The Data Collection Core, developed by Iotsmart, is an innovative software solution designed for the efficient real-time collection of data from OPC Servers and a variety of devices, processing this information while enabling simultaneous output to multiple storage solutions to consolidate data from all connected devices in a single, centralized hub. It can be deployed in either cloud environments or on-premises settings, utilizing options such as Azure IoT Edge, AWS IoT Edge, or virtual machines configured with containers. This versatility guarantees accurate data acquisition directly from sensors while seamlessly interfacing with OPC UA and HTTPS outputs, facilitating the integration of numerous devices with performance levels that exceed traditional client solutions. Furthermore, the system is equipped with server redundancy for both OPC UA and MQTT, which enhances reliability and ensures continuous operation. Our dedicated team of IoT experts is readily available to offer assistance, providing troubleshooting support and customized customer service to improve your overall experience. By allowing us to manage your digital solutions, you can focus on effectively operating your business without distractions. The entire system is conveniently packaged using Docker images, which simplifies deployment across various cloud platforms, including Azure and AWS, and guarantees both flexibility and scalability for your operations. This comprehensive approach enables businesses to harness the full potential of their IoT infrastructure.

What is CloudMQTT?

CloudMQTT is an outstanding solution for enabling communication in the "Internet of Things" realm, particularly for low-power sensors and mobile devices such as smartphones, embedded systems, and microcontrollers like Arduino. It simplifies the entire process of establishing and managing a hosted Mosquitto message broker, allowing your team to focus on developing products without the complexities of server upkeep. By delegating these critical tasks to experts, you can achieve remarkable performance and dependability. The CloudMQTT WebSocket client also enables seamless monitoring of messages flowing between your device and the browser, which is invaluable for testing and debugging, as it allows for the visualization of real-time data from various sensors or devices. Furthermore, by adding team members, you can create separate CloudMQTT accounts while effectively overseeing a collective pool of instances, which helps streamline notification management and billing duties. This adaptability not only fosters teamwork but also ensures that everyone remains synchronized with the goals of the project, ultimately leading to a more efficient workflow. With such features, CloudMQTT proves to be a vital asset for any team looking to enhance their IoT projects.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

$5 per month
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

IoTSmart

Company Location

Mexico

Company Website

iotsmart.io

Company Facts

Organization Name

CloudMQTT

Company Website

www.cloudmqtt.com

Categories and Features

IoT

Application Development
Big Data Analytics
Configuration Management
Connectivity Management
Data Collection
Data Management
Device Management
Performance Management
Prototyping
Visualization

Categories and Features

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