Agricultural Sensor Placement for Fault-Tolerant Irrigation Networks

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Solution Overview

Problem

Agricultural irrigation systems face inefficiencies due to manual scheduling and inadequate sensor placement, leading to excessive water use and communication faults in wireless sensor networks, which are not optimized for terrain, soil type, or crop characteristics.

Innovation Solution

A system using a genetic algorithm to determine optimal sensor placement in a field, incorporating soil moisture sensors with a central controller for fault detection, and implementing a fitness metric to ensure reliable communication and data inference, reducing sensor costs while maximizing data quality and fault tolerance.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Area of stationary object

If sensors are placed uniformly across the field, then coverage area is maximized, but communication reliability deteriorates due to terrain and soil variations

Engineering Contradiction:

Improvesensor coverage areaVSAvoidcommunication reliability

Core Design Contradiction:

Area of stationary objectVSReliability

Solution Approach 1:

The patent applies local quality by dividing the field into multiple zones based on terrain, soil type, and crop characteristics, then placing sensors at optimized locations within each zone rather than uniform distribution. This allows the sensor placement strategy to adapt to local conditions, improving communication reliability while maintaining comprehensive coverage.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The patent performs preliminary action by using a genetic algorithm to pre-optimize sensor placement locations before deployment. The system evaluates multiple potential configurations and selects the optimal placement that maximizes both coverage and communication reliability, avoiding the need for trial-and-error deployment.

Inventive Principle:

Principle #10Preliminary action

2Measurement precision

If more sensors are deployed to improve data quality, then measurement precision increases, but system cost and complexity increase

Engineering Contradiction:

Improvedata qualityVSAvoidsystem complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent applies partial action by deploying sensors at optimized locations rather than comprehensive coverage. The genetic algorithm determines the minimum number of sensors needed to achieve sufficient data quality for irrigation decisions, avoiding unnecessary sensors that would increase complexity and cost.

Inventive Principle:

Principle #16Partial or excessive action

Solution Approach 2:

The patent segments the field into zones and places sensors strategically within each zone rather than distributing sensors uniformly throughout the entire field. This segmentation approach maintains measurement precision while reducing the total number of sensors required.

Inventive Principle:

Principle #1Segmentation

3Device complexity

If manual irrigation scheduling is used, then system simplicity is maintained, but water use efficiency deteriorates

Engineering Contradiction:

Improvesystem simplicityVSAvoidwater use efficiency

Core Design Contradiction:

Device complexityVSLoss of energy

Solution Approach 1:

The patent implements feedback by using sensor data from optimized placement locations to inform irrigation scheduling decisions. The system continuously monitors soil moisture, terrain conditions, and crop needs, then adjusts irrigation accordingly, significantly improving water use efficiency while maintaining manageable system complexity.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The patent enables self-service by allowing the irrigation system to automatically adjust based on sensor feedback from strategically placed sensors. The optimized sensor placement provides sufficient data for the system to make intelligent irrigation decisions without requiring complex infrastructure or continuous manual intervention.

Inventive Principle:

Principle #25Self-service

4Reliability

If sensors are placed to optimize communication, then communication reliability improves, but coverage of critical regions deteriorates

Engineering Contradiction:

Improvecommunication reliabilityVSAvoidfield coverage

Core Design Contradiction:

ReliabilityVSArea of stationary object

Solution Approach 1:

The patent applies local quality by treating different field regions with different placement strategies. Critical regions such as slope boundaries, soil type transitions, and crop variation zones receive priority sensor placement, while other areas use sensors positioned for optimal communication. The genetic algorithm evaluates both coverage and communication metrics for each potential placement location.

Inventive Principle:

Principle #3Local quality

Data Source

PatentUS11520647B2Agricultural sensor placement and fault detection in wireless sensor networks

Publication Date: 2022.12.06 TEXAS A&M UNIVERSITY

AI summary

Disclosed are various embodiments for optimized sensor deployment and fault detection in the context of agricultural irrigation and similar applications. For instance, a computing device may execute a genetic algorithm (GA) routine to determine an optimal sensor deployment scheme such that a mean-time-to-failure (MTTF) for the system is maximized, thereby improving communication of sensor measurements. Moreover, in various embodiments, a centralized fault detection scheme may be employed and a soil moisture of a field can be determined by statistically inferring soil moistures at locations of faulty nodes using spatial and temporal correlations.