Web-enabled Intelligent System for Continuous Sensor Data Processing and Visualization
This addresses the problem of real-time spatial data understanding and decision-making for stakeholders in building management and aquaponics, though it is incremental as it combines existing methods for specific applications.
The researchers developed a prototype system for near real-time, continuous 3D visualization of sensor data using X3D, applied to thermal monitoring in buildings and nitrogen cycle monitoring in aquaponics, by approximating data distribution across volumes with Finite Differences Method and Neural Networks.
A large number of sensors deployed in recent years in various setups and their data is readily available in dedicated databases or in the cloud. Of particular interest is real-time data processing and 3D visualization in web-based user interfaces that facilitate spatial information understanding and sharing, hence helping the decision making process for all the parties involved. In this research, we provide a prototype system for near real-time, continuous X3D-based visualization of processed sensor data for two significant applications: thermal monitoring for residential/commercial buildings and nitrogen cycle monitoring in water beds for aquaponics systems. As sensors are sparsely placed, in each application, where they collect data for large periods (of up to one year), we employ a Finite Differences Method and a Neural Networks model to approximate data distribution in the entire volume.