IoT platforms and tools are considered as the most significant component of the IoT ecosystem. When developing smart IoT devices, companies are usually completely forgotten after deployment and maintenance, although in most cases it is more important than anything else. RemoteIoT is IoT device management, data collection, processing and visualization of IoT solutions. Using the RemoteIoT platform, companies will be able to remotely monitor their Raspberry Pi’s CPU/RAM usage and any other custom parameters they want within minutes.
1. Sign up for the RemoteIoT IoT management platform, which is completely free for makers and personal use.
2. Log in to the dashboard and register the Raspberry Pi to the platform. Click the “Register New Device” button at the top of the dashboard, then copy the registration command and run it on the Raspberry Pi’s terminal. The Raspberry Pi device should appear in the “Device” page within a minute.
3. Click on the recently appeared Raspberry Pi. Users will notice that multiple boxes are displayed under the device table. Users can clearly view the real-time resource usage of the device-RAM / CPU in the “System Activity” section. Also, users can set up a CloudWatch alarm to send a notification when an event triggers a condition in one of their alarm policies.
4. Users can use built-in templates to create various types of charts, such as area charts, line charts, meter charts, etc., to make interesting and practical dashboards. User can export historical data with the Chart API and integrate it with external services.
The RemoteIoT IoT management platform enables users to track, monitor, and manage physical IoT devices, and push software and firmware updates to the IoT devices remotely. In addition, the RemoteIoT IoT management platform provides permissions and security features to ensure that each device is protected from vulnerabilities. The RemoteIoT IoT device management platform can be used in combination with IoT analysis software, IoT security software, and IoT Monitoring platform. It fills the gap between the device sensors and data networks and connects the data to the sensor system and gives insights using back-end applications to create a sense of the plenty of data developed by the many sensors.