Here we manipulated Fledge through a concrete use case: integrating the DHT11 sensor to collect, process, store, and transmit environmental data. This use case serves as a practical demonstration of Fledge’s capabilities across its different components.
South Service
To connect the DHT11 sensor to Fledge, the corresponding plugin must be installed. We then add the fledge-south-dht11 plugin, which enables the collection of temperature and humidity measurements. Once the plugin is installed, the administrator is required to properly complete the configuration form.
Smart Data Collection & Real-Time Monitoring
Initially, the sensor detected an ambient room temperature of around 21°C. However, once a heat source was placed near the sensor, the temperature readings increased rapidly to 33°C. This sudden variation was instantly captured and displayed within the Asset & Reading section of Fledge, creating a clear spike in the monitoring dashboard.
Data Storage
Collected data can persist for as long as required by a specific use case. However, it is common that after a certain period—whether just a few seconds, minutes, or even days or months—the data is no longer needed in Fledge.
For this reason, the storage plugin is designed to automatically delete data from the database. This deletion can be configured based on time duration or storage space used, giving users full control over how long data should be retained.
Backup and Restore
The Backup and Restore section allows you to perform a complete backup of both the collected data and the Fledge configuration. The interface provides a list of all system backups, including their creation date and time.
Each backup can then be restored, deleted, or downloaded with a simple click on the corresponding action button.
Interconnecting Fledge Instances
One of the key uses of Fledge is to establish a communication link between different Fledge instances at the Edge layer, enabling data processing directly within the same layer.
To achieve this, the South-HTTP service of the Laptop instance is connected to the North-HTTP service of the NVIDIA Jetson Xavier NX instance. This setup ensures seamless data flow and efficient processing across both devices.
Data Transmission to the Cloud
The collected, filtered, and stored data can be sent outside of Fledge, meaning it can leave the Edge layer and move to the Cloud layer for more advanced analytics.
In our case study, the data is transmitted to Kafka, a distributed streaming platform designed to publish, store, process, and subscribe to real-time event streams. Kafka is built to handle data flows from multiple sources and deliver them reliably to multiple consumers.
To enable this communication with the Cloud, the Kafka-Python plugin is configured to launch the streaming service, ensuring seamless and scalable data integration.
Dashboard Overview
The Dashboard provides a comprehensive view of Fledge operations, with the ability to customize both the displayed information and the time ranges.
It offers a complete overview of all Fledge activities, presented through a variety of intuitive graphs and visualizations, making it easier to monitor performance and analyze trends in real time.
Conclusion
Fledge stands out as a robust Edge computing framework, delivering complete capabilities for data collection, processing, storage, and seamless integration with the Cloud. From capturing sensor measurements and displaying them through intuitive dashboards, to managing backups and storage policies, it ensures that businesses maintain full control and visibility over their industrial IoT data.
Its ability to connect multiple Edge instances allows for smooth communication and localized processing, while its Cloud connectivity enables deeper analytics and AI-driven insights. With flexible backup, restore, and retention features, Fledge guarantees reliability, scalability, and efficiency in data-driven operations.
In essence, Fledge bridges the gap between Edge and Cloud, empowering organizations to make smarter decisions, react faster, and maximize the value of their data.
