Smart Agriculture Greenhouse: How Can the Industrial Gateway Link Environmental Sensors with Irrigation Systems? Precision Planting Area Planning Ushers in a New Era of Efficient Agriculture
In the Smart Seedling Industrial Park in Shouguang, Shandong, tomato seedlings thrive under the precise regulation of an intelligent greenhouse. Inside the greenhouse, temperature and humidity sensors upload data every 30 seconds, light sensors capture real-time changes in light intensity, and soil moisture sensors synchronize humidity information from the root zone to the cloud. When the soil moisture falls below the set threshold, the industrial gateway USR-M300 immediately activates the irrigation system, controlling water flow through solenoid valves while adjusting the concentration ratio of the fertilization pump to achieve precise water-fertilizer integration. Behind this scenario lies the core role of the industrial gateway as the "central nervous system of smart agriculture"—it not only connects sensors with actuating devices but also constructs a closed-loop control system of "perception-decision-execution" through data fusion and edge computing.
Environmental monitoring in smart greenhouses needs to cover more than ten parameters, including temperature, humidity, light, carbon dioxide concentration, and soil EC value (electrical conductivity). In traditional solutions, sensors from different manufacturers often use heterogeneous protocols such as Modbus RTU, RS485, and 4-20mA analog signals, leading to prominent data silo issues. The USR-M300 industrial gateway supports over 20 industrial protocols, including Modbus TCP/RTU, OPC UA, and BACnet, enabling seamless integration of multi-brand sensors. For example, at a large vegetable base in Jiangsu, the USR-M300 simultaneously connects a temperature and humidity sensor from Germany's Sensirion, a soil nutrient sensor from the United States' Spectrum, and a flowmeter from China's Juying Electronics, converting the data into a unified JSON format for upload to the cloud through protocol conversion.
Greenhouse environmental regulation has strong time-sensitivity requirements. Take light control as an example: when the light intensity exceeds the crop's light saturation point, the sunshade needs to be activated within 10 seconds; if the soil moisture falls below the wilting coefficient, the irrigation system needs to respond within 5 minutes. The USR-M300 is equipped with a 1.2GHz quad-core processor and supports localized edge computing, enabling the running of lightweight AI models. At a flower plantation in Zhejiang, the gateway deployed an LSTM neural network model to predict soil moisture changes in the next two hours based on historical data, adjusting irrigation plans in advance and improving water resource utilization by 40%.
Smart greenhouses require coordinated control of multiple devices. For example, in a high-temperature and high-humidity environment, the gateway needs to simultaneously activate exhaust fans, open roof windows, regulate wet curtains, and reduce CO₂ concentration. The USR-M300 supports graphical programming, allowing users to define interaction rules by dragging and dropping logic blocks. At a tomato greenhouse in the Netherlands, the administrator configured a "nighttime low-temperature protection" scenario through the gateway: when the temperature falls below 12℃, ventilation windows automatically close, heaters start, and an SMS alert notifies the on-duty personnel.
Traditional greenhouse planting area planning relies on manual measurement, making it difficult to consider dynamic factors such as equipment layout and crop growth cycles. The USR-M300 supports GNSS positioning and LiDAR scanning, enabling the generation of three-dimensional point cloud models of greenhouses. In a smart agriculture project in Shandong, the gateway constructed a digital twin of the greenhouse using SLAM algorithms and optimized the layout of planting racks by combining canopy height data, resulting in an 18% increase in yield per unit area.
Different crops have significantly different requirements for environmental parameters. For example, lettuce prefers a growth temperature of 15-20℃, while peppers prefer 25-30℃. The USR-M300 has a built-in crop knowledge base that can recommend suitable varieties based on planting area and environmental conditions. At a pepper planting base in Sichuan, the gateway analyzed historical yield data and climate models and suggested switching some areas to the cold-tolerant variety "Chuanla 19," reducing losses during frost periods by 65%.
Planting area planning needs to dynamically match market demand. The USR-M300 can access agricultural commodity futures market data and predict production gaps for the next three months based on current planting area and growth cycles. At a vegetable cooperative in Hebei, the gateway analyzed price fluctuations at the Beijing Xinfadi Wholesale Market and suggested switching 10% of the cucumber planting area to the in-demand fruit cucumbers, increasing single-season revenue by 220,000 yuan.
Challenge: The base covers an area of 50 acres, and the original irrigation system relied on manual judgment, leading to severe water waste and inconsistent strawberry quality.
Solution: Deploy the USR-M300 industrial gateway to connect 200 soil moisture sensors, 30 weather stations, and 50 sets of solenoid valves. The gateway achieved zoned irrigation control through edge computing, dynamically adjusting irrigation strategies according to different growth stages of strawberries (seedling, flowering, and fruiting).
Effect: Water savings of 35%, a 1.2° increase in strawberry sugar content, and an improvement in the excellent fruit rate from 68% to 89%.
Challenge: The greenhouse has a span of 120 meters, and traditional wired sensor wiring is costly, with a rising equipment failure rate due to low winter temperatures.
Solution: Use the LoRa wireless expansion module of the USR-M300 to deploy 50 wireless temperature and humidity sensors and 10 sets of heating equipment. The gateway enables remote operation and maintenance through a VPN tunnel and is configured with an automatic low-temperature protection mechanism.
Effect: A 70% reduction in wiring costs, a 90% decrease in equipment failure rate, and a shortening of the seedling period by 5 days.
Challenge: The base needs to simultaneously meet the EU's GAP certification and the United States' MPS certification standards, with extremely high requirements for the completeness and traceability of environmental records.
Solution: The USR-M300 integrates a blockchain module to store sensor data, equipment operation records, and personnel permission information on the blockchain. Customers can scan a QR code to view the full lifecycle environmental data of the flowers.
Effect: A 100% increase in certification pass rates and a tripling of export orders.
To help agricultural enterprises quickly implement smart greenhouse projects, we offer the following free services:
Service: Planting Area Assessment and Planning Report
Submission Content: Click the button to fill in the enterprise name, contact person, contact information, greenhouse type (glass greenhouse/multi-span greenhouse/solar greenhouse), current planting area, and main crop type.
Output Results: Provide an "Optimized Planting Area Report" within three working days, including:
The core of smart agriculture lies in achieving optimal allocation of production factors through data-driven approaches. The USR-M300 industrial gateway, as a bridge connecting the physical and digital worlds, not only solves technical challenges such as sensor heterogeneity, device interaction, and real-time decision-making but also helps agricultural enterprises construct a full-chain closed-loop management system of "environment-crop-market" through data services such as planting area planning, crop adaptation, and production capacity forecasting.
