Real-Time Sensor Data Analytics and Visualization in Cloud-Based Systems for Forest Environment Monitoring

Abstract

Forest environment monitoring is essential for natural resource management. The development of sensors using across forests enables for the collection massive volumes of data due to technological improvements in the sensor network. Raspberry Pi, a flexible and inexpensive single-board computer, is at the main of the system, connecting and interfacing with the many sensors spread throughout the system. Sensors such as this can collect crucial information about the forest's environment, such as the weather, humidity, and temperature. Data from various sensors can be acquired and processed in real-time due to Raspberry Pi's role as a data collection device. The system uses cloud-based services to overcome the limitations of onpremises data processing and storage. A fusion technique on the cloud platform combines and analyzes data from various sensors after receiving transmissions from Raspberry Pi. The cloud service provides a location for live monitoring and other visualization which greatly help data in real-time. These visuals can be accessed remotely, allowing users to access the forest from any location. Improved comprehension and control of forest environments are possible because of the combination of various technologies for collecting, analyzing, and evaluating sensor data.