IoTPlotter
IoTPlotter is an open-source data visualization and analysis tool for the Internet of Things. It allows users to easily connect to IoT devices and sensors, collect data in real-time, and visualize the data through customizable dashboards and charts.
iot
data-visualization
dashboards
charts
IoTPlotter: Open-Source Data Visualization for IoT
An open-source data visualization and analysis tool for the Internet of Things, allowing real-time data collection and customizable dashboards and charts.
What is IoTPlotter?
IoTPlotter is an open-source software application designed specifically for visualizing and analyzing data from Internet of Things (IoT) devices and sensors. It provides an intuitive graphical interface that allows users to easily connect various IoT devices, collect sensor data in real-time, and visualize the data through fully customizable dashboards and charts.
Some of the key features of IoTPlotter include:
- Compatible with major IoT protocols like MQTT, CoAP, HTTP, WebSocket, and more
- Easy device and sensor connection over LAN or cloud services
- Real-time data monitoring with millisecond precision
- Custom dashboards with drag-and-drop widgets like charts, gauges, maps, tables, etc.
- Analyze historical data with reporting and exporting functions
- Collaboration tools to share dashboards and data externally
- Open-source software with community support for extensions
IoTPlotter can connect to consumer IoT devices like wearables and home automation sensors as well as industrial equipment in manufacturing plants, energy meters in utilities, temperature monitors in logistics, and more. The software runs on Linux, Windows and OS X and offers a user-friendly way to gain visibility into IoT data without coding.
IoTPlotter Features
Features
- Real-time data visualization
- Customizable dashboards and charts
- Connects to IoT devices and sensors
- Collects and analyzes IoT data
- Open-source and self-hosted
Pricing
- Open Source
Pros
Free and open-source
Easy to set up and use
Customizable visualizations
Scalable for large datasets
Self-hosted for data privacy
Cons
Requires technical expertise to set up
Limited built-in analytics features
Not suitable for non-technical users
Need to manage own server infrastructure
Official Links
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