iVayu

iVayu facilitates visualization and quantitative analysis of sensor-derived time-series data to support air quality and environmental monitoring at high spatial-temporal resolution.

Key Features:

• Robust data analysis: Provides data conversion, interpolation, aggregation, and prediction functions for sensor time-series.
• Visualization capabilities: Generates visual representations of spatial-temporal patterns in large sensor datasets.
• Statistical analysis tools: Performs statistical analyses to extract insights from sensor-derived time-series data.
• Scalability for large sensor datasets: Handles high-volume time-series data produced by low-cost and low-power sensors.
• Sensor data support: Targets air quality sensor data and other environmental time-series, including crowd-sourced sensor networks.

Scientific Applications:

• Air quality research: Supplements traditional monitoring networks with high-resolution, crowd-sourced sensor data to analyze pollution patterns at finer spatial-temporal scales.
• Environmental time-series analysis: Applies to other domains requiring analysis of sensor-derived time-series for environmental monitoring and research.

Methodology:

Computational methods explicitly include data conversion, interpolation, aggregation, prediction, visualization, and statistical analysis of sensor time-series.