Internet of the Environment (IoE) and Eddy Covariance-based Ecosystem Fluxes

The Internet of the Environment (IoE) represents a subset of the Internet of Things (IoT) where connected environmental monitoring sensors, that utilize edge computing and embedded power and communications, report on the state of the environment to improve scientific understanding via large-scale monitoring. 

The IoE approach offers several notable advantages compared to traditional methods:

• It facilitates measurements in almost any location, including large-scale deployments and remote, hard-to-reach areas.
• It supports consistent measurement techniques that are scalable from field to landscape to continental levels, all while reducing operational costs.
• It leads to cost savings and minimizes data loss through enhanced operations, utilizing predictive maintenance powered by machine learning.
• It integrates various external datasets into a unified cloud platform, enabling automated post-processing and advanced data analytics.

This presentation covers the integration of an eddy covariance (EC) sensor with an IoE Module, transforming it into a node within the IoE system. Other sensors, measuring different environmental parameters, can serve as additional nodes.

Once the data from these nodes is transmitted to the cloud, it can be utilized for automated quality assurance/quality control, gap filling, forecasting, accumulation, and spatial extrapolation, leveraging external datasets and statistical/machine learning tools.

This integration enables users to construct dynamic virtual networks of real measurements from various research sites and nodes, facilitating scientific research and fostering collaboration between institutions and groups.

An illustrative example of this approach is presented through a network of actual evapotranspiration EC sensors, which collect flux data across diverse irrigated and rain-fed agricultural landscapes for immediate societal applications.