iot-dashboard is an open-source Internet of Things (IoT) data visualization and monitoring tool. It allows users to easily create customizable dashboards to visualize and monitor data from IoT devices and sensors in real-time.
An open-source Internet of Things (IoT) data visualization and monitoring tool for creating customizable dashboards to visualize and monitor data from IoT devices and sensors in real-time.
What is Iot-dashboard?
iot-dashboard is an open-source Internet of Things (IoT) data visualization and monitoring web application. It provides an intuitive graphical interface that allows users to easily create customizable dashboards to visualize and monitor data from IoT devices, sensors, and other data sources in real-time.
Some key features of iot-dashboard include:
Support for connecting to various data sources such as MQTT brokers, REST APIs, databases, and more
Drag-and-drop dashboard designer to create customized layouts
Various built-in widget types such as charts, gauges, maps, tables, and more for data visualization
Responsive layouts that adapt to mobile, tablet, and desktop screens
User management, access controls, and data access policies
Annotations and reporting capabilities
Open source under the MIT license with an active developer community
iot-dashboard enables faster IoT application development by providing pre-built components to visualize, monitor, and alert on data feeds. It can be used for monitoring applications in smart homes, smart factories, smart farming, healthcare, smart cities, and more. The open-source nature also allows custom plugins and widgets to be developed for specific use cases.
Iot-dashboard Features
Features
Real-time data visualization
Customizable dashboards
Support for various data sources like MQTT, REST API, Websockets
Drag and drop interface for building dashboards
Variety of widgets like charts, gauges, maps, buttons, etc
Role based access control
Alerting and notifications
Pricing
Open Source
Pros
Open source and free to use
Easy to set up and use
Very customizable and extensible
Active community support
Cons
Limited built-in analytics capabilities
Can be resource intensive for large scale deployments
Requires technical expertise to fully utilize features
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