3D Soil Moisture Sensor Network for Vineyard Irrigation
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Solution Overview
Problem
Current agricultural technologies lack the ability to effectively manage water resources in vineyards under drought conditions, failing to integrate high-resolution sensor data with physical models and translate it into actionable decisions for grape producers, leading to inefficiencies in irrigation and crop management.
Innovation Solution
A system and method utilizing a network of temperature and moisture sensors to provide a three-dimensional assessment of water movement through the soil, determining volumetric water content, spatial and temporal variability, and plant available water levels, allowing for real-time adjustments in irrigation and providing predictive insights for harvest dates and grape composition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution sensor networks are deployed to track soil moisture and temperature, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system divides the vineyard into multiple monitoring zones with sensors deployed at different locations and depths. Each sensor node independently measures local soil conditions, and the computer integrates these segmented measurements to create a comprehensive three-dimensional assessment of water movement across the entire field.
Solution Approach 2:
The system transitions from traditional two-dimensional surface monitoring to three-dimensional subsurface monitoring by deploying sensors at multiple depths within the soil profile. This dimensional expansion enables tracking of water movement through vertical soil layers and root zones, providing comprehensive spatial assessment.
2Productivity
If three-dimensional assessment of water movement is implemented, then productivity is improved through better irrigation decisions, but loss of information increases due to the complexity of processing and integrating multiple data sources
Solution Approach 1:
The system merges multiple data sources including soil moisture sensors, temperature sensors, weather data, and plant physiology models into a unified three-dimensional assessment framework. The computer integrates these diverse information streams to produce coherent irrigation recommendations, preventing information loss through systematic data fusion.
Solution Approach 2:
The computer acts as an intermediary that processes raw sensor data and model outputs, translating them into actionable irrigation decisions. This intermediary processing layer organizes complex information from multiple sources into synthesized assessments of water availability and movement, making the data usable for productivity improvement.
3Reliability
If real-time monitoring of spatial and temporal variability is performed, then reliability of irrigation decisions is improved, but use of energy increases due to continuous data collection and processing
Solution Approach 1:
The system implements periodic monitoring at strategically selected locations and depths rather than continuous monitoring across the entire field. Sensors collect data at regular intervals, and the computer processes this periodic information to assess spatial and temporal variability, maintaining decision reliability while reducing energy consumption compared to continuous full-field monitoring.
Data Source
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AI summary
Disclosed herein are a system and method that integrate vineyard sensor data into an environment that enables analysis, historical trend analytics, spatio-temporal analytics, and weather model fusion for improved decision making from vineyard management to wine production. The integration of new sensor data from multiple soil depths with surface measurements, combined with production flow process and historical information enables new decision making capabilities. A wireless network of sensor/transmitters can be distributed to provide a 3-dimensional assessment of water movement both across the grower's field and as it moves from the surface through the root zone. The soil monitoring data stream feeds into a visualization interface that will be incorporated in software based decision aid and crop management tool that helps agricultural producers reduce costs, minimize water and nutrient applications, and better protect the environment by reducing agricultural production inputs.