Programmable automated low-cost IoT water sampler.

Area of Science:

• Environmental Science
• Agricultural Engineering
• Water Resource Management

Background:

• Water quality management faces challenges from agricultural pollutants like nitrogen and phosphorus, degrading global waterways.
• Current monitoring relies on manual sampling (labor-intensive, single data points) or expensive, complex automated samplers.
• Effective water resource management requires accessible and reliable water quality monitoring tools.

Purpose of the Study:

• To develop and evaluate a low-cost, automated water sampler (LCS) using Internet of Things (IoT) technology.
• To provide near-real-time, edge-of-field water monitoring capabilities for agricultural settings.
• To offer an affordable and simple alternative to traditional water quality monitoring methods.

Main Methods:

• Development of a low-cost automated water sampler (LCS) integrating IoT technology.
• Deployment of the LCS for edge-of-field water monitoring in agricultural areas.
• Comparison of water quality and quantity data collected by the LCS with traditional methods.

Main Results:

• The LCS provides near-real-time water quality monitoring with notable affordability and simplicity.
• Data from the LCS shows promising agreement with traditional methods for water quality and quantity.
• The device demonstrates potential as a practical substitute for established water monitoring techniques.

Conclusions:

• The developed LCS offers a viable, cost-effective solution for agricultural water quality management.
• IoT integration enables accessible, real-time water monitoring, enhancing environmental pollutant mitigation efforts.
• The LCS empowers water resource managers with practical tools for improved water quality surveillance.