Irrigation Efficiency Modeling for Zone-Specific Watering Control
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Solution Overview
Problem
Current irrigation systems face challenges in uniformly watering lawns due to varying soil moisture retention and sunlight exposure across different areas, leading to over or under watering, and lack of efficient monitoring and control solutions that consider weather forecasts and cumulative water usage.
Innovation Solution
A computer-based system that uses moisture sensors to collect data, generates an efficiency model of the lawn based on water application and soil response, and schedules water application based on this model, weather forecasts, and cumulative usage, ensuring optimal watering while monitoring and controlling water distribution devices remotely.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If uniform watering is applied across the entire lawn, then all areas receive the same amount of water, but some areas become overwatered while others become underwatered due to varying soil moisture retention and sunlight exposure
Solution Approach 1:
The lawn is divided into multiple zones based on soil moisture retention characteristics, sunlight exposure, and drainage properties. Each zone is equipped with independent moisture sensors and controlled by separate irrigation valves, allowing differentiated watering strategies for each segment to achieve precise moisture distribution while maintaining operational simplicity through automated zone-based control.
Solution Approach 2:
The system implements location-specific irrigation parameters by measuring actual moisture levels at each sensor location and adjusting watering duration and intensity accordingly. Areas with poor moisture retention receive longer watering periods, while areas with good retention receive shorter periods, ensuring each location receives precisely the water it needs rather than uniform treatment.
2Extent of automation
If automatic sprinkler systems are used to water the lawn, then watering can be performed without manual intervention, but the system cannot account for weather forecasts and may water unnecessarily when precipitation is expected
Solution Approach 1:
The system continuously monitors actual soil moisture levels via sensors and compares them against target moisture thresholds. This feedback loop allows the automated system to adjust watering operations in real-time based on actual conditions rather than following fixed schedules, enabling adaptation to varying weather patterns and preventing unnecessary watering when soil moisture is sufficient or precipitation is expected.
Solution Approach 2:
The system checks weather forecasts and current soil moisture levels before initiating watering operations. By performing preliminary assessments of expected precipitation and current moisture status, the system can preemptively avoid scheduling water applications when natural rainfall is predicted or when soil moisture thresholds are already met, optimizing water usage while maintaining full automation.
3Manufacturing precision
If manual monitoring and adjustment of irrigation is performed, then watering can be precisely controlled for each area, but significant user presence and attention are required to place and activate sprinklers
Solution Approach 1:
The system performs self-monitoring and self-adjustment of irrigation operations. Moisture sensors automatically detect soil moisture levels, the controller compares readings against target thresholds, and valves are automatically activated or deactivated without user intervention. The system places and manages its own control elements through automated decision-making, achieving precise irrigation control while eliminating the need for continuous user presence or manual adjustments.
4Device complexity
If traditional irrigation systems are used without monitoring, then simple operation is maintained, but water usage efficiency cannot be tracked or optimized
Solution Approach 1:
The system integrates multiple functions into a single platform: moisture sensing, data transmission, weather forecasting, efficiency modeling, and automated control. This multi-functional approach allows the system to simultaneously maintain operational simplicity for the user while incorporating advanced monitoring and optimization capabilities that track and improve water usage efficiency through centralized intelligent control.
Solution Approach 2:
An efficiency model acts as an intermediary between raw sensor data and irrigation control decisions. The model processes moisture measurements, weather forecasts, and historical data to generate optimized watering schedules, translating complex monitoring information into simple automated actions. This intermediary layer enables efficient water usage tracking and optimization while maintaining system simplicity for end users.
Data Source
AI summary
Technologies disclosed herein are provided for irrigation monitoring and controlling based on water usage monitoring and control using an efficiency model for a defined geographic region. The technology includes receiving a first and a second set of moisture sensor measurements from a set of moisture sensors located in a defined geographic region, and determining an amount of water that is applied to the defined geographic region at a time period between the first and the second set of moisture measurements. An efficiency model representing efficiencies of locations in the defined geographic region is obtained based on the first and second set of moisture measurements and the amount of water applied. Schedule information is generated based on the efficiency model that indicates time periods at which areas in the defined geographic region are to be watered.