This breakthrough offers an efficient, scalable solution for addressing long-standing issues in hydrological monitoring. This solution has been tested in two regions in Spain, utilizing dense sensor networks to measure both soil moisture and water levels. The main goal was to develop an efficient, low-cost monitoring solution for challenging environments, providing real-time data on hydrological processes. By integrating NB-IoT with the Thinger.io cloud platform, the system overcame traditional issues like low connectivity and high energy consumption.

Study

What Does It Solve?

Traditional hydrological monitoring struggles with sparse data collection, low spatial resolution, and connectivity issues in remote areas. This new system, developed in collaboration with University Polytechnic of Madrid and University Carlos III of Madrid, along with Thinger.io cloud integration, provides a comprehensive and real-time solution to these challenges. It enables timely tracking of hydrological events, thus optimizing water management and aiding in flood prevention and agricultural planning.

Research Utility

Real-time hydrological monitoring has become essential for addressing challenges across various sectors. Precise data on soil moisture and water levels improve water resource management, thus helping to optimize agricultural irrigation, prevent floods, and create more sustainable urban plans. By constantly tracking these processes, authorities can implement effective strategies to mitigate climate change impacts, such as droughts and extreme weather events.

• Climate Science 🌍 : Early warning systems for extreme weather events.
• Water Management 💧: Efficient irrigation systems to reduce water waste.
• Agricultural Monitoring 🌾: Smart farming technologies to optimize irrigation.
• Flood Prevention 🌊: Infrastructure for flood prevention in vulnerable areas.
• Urban Planning 🏙️ : Sustainable water management for smart cities.
• Drought Mitigation: ☀️ Efficient water use during droughts to prevent waste.

Key Results

The system demonstrated excellent performance in field trials, with sensors providing reliable data transmission and optimized battery life through Thinger.io. Key findings include:

• High spatial and temporal data accuracy 📏
• Successful operation in remote areas with low connectivity 🌐
• Extended battery life with efficient energy consumption management, optimized via Thinger.io. 🔋
• Real-time data accessible via Thinger.io’s cloud platform for immediate analysis. 📊

NB-IoT Hardware

The core of the devices is an IoT development toolkit manufactured by Thinger.io, as a result, providing flexibility for creating hardware prototypes tailored to specific project requirements. The toolkit is built around an ESP-32 System-on-Chip (SoC) processor, which combines Wi-Fi and Bluetooth capabilities, and also integrates a modem with NB-IoT capability from Quectel. The processor manages data acquisition via general-purpose ports with 12-bit SAR ADC functionality in order to collect data from soil moisture and water level probes.

• 🌱 Soil moisture sensors: Equipped with two independent probes wired through a Resistor-Capacitor (RC) circuit, allowing for reading calibration and analog noise reduction.
• 🌊 Water level sensors: Use an A02YYUW ultrasonic sensor operating at 40 kHz, therefore providing sufficient accuracy to measure distances between 25 and 30 cm.

The units are powered by 3.7V, 3400mAh rechargeable lithium batteries. Solar panels were not used to allow more flexibility in field deployment.

Here’s how Thinger.io is used

Thinger.io played a crucial role in managing the data collection and transmission from the sensor network. The platform is used to:

• Sensor auto-provision ⚙️: Each connected sensor is automatically provisioned, streamlining device deployment, data storage and device management.
• Configurable sleep times 💤: The platform enabled remote management of sensor sleep cycles to optimize battery life.
• Data transmission and visualization 📡: The soil moisture and water level sensors transmitted data directly to Thinger.io, thus enabling real-time visualization and storage on the platform.
• Dashboards and monitoring 📈: Custom dashboards showcased sensor data, including battery voltage and readings, enabling continuous monitoring and analysis.
• Error handling and optimization 🛠️: The platform monitored and managed connectivity issues as well as data transmission, ensuring efficient sensor operation even in remote areas.

Conclusions

The study demonstrated the effectiveness of the custom-designed hydrological monitoring system using Thinger.io. By combining NB-IoT connectivity, cloud infrastructure, and efficient sensor design, the system delivered accurate, real-time data on soil moisture and water levels, thus improving data reliability. As a result, it improved monitoring efficiency. Remote management of sensors enhanced battery performance while ensuring continuous data transmission, even in remote areas.

This monitoring system offers a scalable and low-cost solution for hydrological studies, enabling better water resource management and environmental monitoring. Future improvements could enhance sensor durability and additionally incorporate automated calibration routines to further optimize data accuracy and long-term operation.

Read the full publication here.