In traditional agriculture, farmers mainly rely on experience to determine if farmland needs water: looking at the color of the soil, squeezing to feel its dryness or wetness, and observing if crop leaves are wilting. While this method is direct, it is inaccurate. Experience cannot be quantified, and different people have different judgment standards, which can easily lead to insufficient or excessive irrigation. Modern agriculture pursues precision and intelligence. When to irrigate and how much water to use need to be based on accurate data rather than vague experience. This is crucial for water conservation, energy efficiency, and yield increase.
Therefore, many farmlands have introduced Soil Moisture Monitors. This is an intelligent system integrating sensor technology, data acquisition and transmission technology, cloud computing, and IoT technology. It can real-time, automatically, and continuously monitor soil moisture conditions and other related environmental parameters, and intuitively present the data to users, providing scientific basis for precision irrigation and agricultural management.
You can understand it as a "smart stethoscope" that continuously monitors the land 24/7.
A complete Soil Moisture Monitor consists of three parts:
① Sensors
The most important is the soil moisture sensor. Common ones are sensors based on Frequency Domain Reflectometry (FDR) principle, which indirectly, quickly, and accurately calculate volumetric water content by measuring the dielectric constant of the soil. This is currently the most mainstream technology.
There are other sensors, such as soil temperature sensors, soil electrical conductivity (EC) sensors (reflecting salt content), and meteorological sensors (such as air temperature and humidity, rainfall, wind speed and direction, light intensity, etc.).
② Data communication network
Responsible for sending data from the field to the cloud. According to the network coverage and power consumption requirements of the monitoring points, wireless transmission can be selected, such as 4G/5G, LoRa, NB-IoT, etc. LoRa and NB-IoT are widely used in field farmland scenarios due to their low power consumption and wide coverage characteristics. Or wired transmission can be used in nearby locations with conditions.
③ Cloud data center and software platform
Responsible for data processing, storage, analysis, and display. Through computer webpages or mobile apps, real-time data from various monitoring points is displayed in the form of charts, curves, maps, etc. Users can set thresholds (such as soil moisture content below 10%), and the system will automatically issue alerts via SMS, app notifications, etc. Advanced systems can also combine historical data, crop growth models, and weather forecasts to provide scientific irrigation recommendations (when and how much to water).
Application scenarios:
Large-field precision agriculture: Water and fertilizer management for crops such as wheat, corn, and cotton.
Orchards and tea gardens: High-value cash crops are more sensitive to water requirements.
Protected agriculture: Precise environmental control in greenhouses.
Landscaping: Water-saving irrigation for golf courses and urban parks.
Scientific research and meteorological hydrological monitoring: Providing long-term positioning observation data for ecological, hydrological, and meteorological research.
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