Autonomous Crop Sensor Fusion for Soil and Canopy Correlation
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Solution Overview
Problem
Current farm management systems lack an efficient and autonomous method to collect and correlate data on both above and below ground conditions for optimal crop management, relying on general advice and reactive decision-making rather than data-driven insights.
Innovation Solution
An autonomous sensor system that combines in-soil sensors with imaging devices to gather and correlate data on soil parameters and crop growth, providing a comprehensive data set for informed decision-making and optimization of agricultural practices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional soil testing and general advice are used, then farmers can obtain basic soil information, but the data is not specific enough to optimize crop management for individual land conditions
Solution Approach 1:
The patent combines multiple sensing capabilities (soil sensors for pH, moisture, temperature; imaging devices for crop health; weather stations) into an integrated monitoring system. This merging allows simultaneous collection of diverse data types at the same location, providing comprehensive and specific soil-crop condition information without requiring multiple separate systems
Solution Approach 2:
The patent introduces a processing hub as an intermediary that collects data from various sensors, correlates it with imaging data, and generates actionable insights. This intermediary component synthesizes raw data into meaningful information about soil-crop relationships, making the complex data manageable and useful for farmers
2Productivity
If farmers manually collect and analyze soil samples, then they can obtain test results, but the process is time-consuming and reactive rather than proactive
Solution Approach 1:
The patent implements continuous monitoring through permanently installed sensors that automatically and continuously measure soil parameters (pH, moisture, temperature) and crop conditions. This eliminates the intermittent, periodic nature of manual sampling and provides real-time data streams, enabling proactive rather than reactive farm management
Solution Approach 2:
The system performs self-measurement and self-analysis through automated sensors and on-board processing. The sensors automatically collect data, the hub correlates it with imaging data, and the system generates insights without requiring farmer intervention for sampling or initial analysis, freeing farmers from time-consuming manual tasks
3Adaptability or versatility
If general agricultural advice based on trials on different land is followed, then farmers can obtain management guidance, but the advice does not account for specific local soil and crop conditions
Solution Approach 1:
The patent implements localized monitoring by deploying sensors and imaging devices at specific field locations to capture unique soil and crop conditions. Each monitoring point provides data specific to its local environment, allowing management advice to be tailored to local conditions rather than applying general recommendations across diverse landscapes
Solution Approach 2:
The system continuously feeds back local condition data (soil parameters, crop health images, weather conditions) to the processing hub, which correlates this information and generates location-specific management recommendations. This feedback loop ensures advice is constantly updated based on actual local conditions rather than relying on generalized trial data from different locations
4Reliability
If multiple separate tools are used to test soil and monitor crops, then comprehensive data can be collected, but the system becomes complex and difficult to operate
Solution Approach 1:
The processing hub serves multiple functions: it collects data from various sensors (soil moisture, pH, temperature), receives and processes imaging data from cameras, correlates all these different data types, and generates comprehensive insights. This multi-functional hub simplifies operation by providing a single point of control and data integration rather than requiring farmers to manage multiple separate tools and data sources
Data Source
AI summary
The present application is directed to an autonomous system for managing crops, the system being configured to record and utilises data indicative of both above and below ground conditions at the same location to provide an output that incorporates data derived from soil conditions and land use activity. The system combines data reflective of each of above and below ground parameters as measured concurrently from in-soil sensors, imaging devices and activity trackers, and analyses the data to provide data outputs based on accurate and consistent soil and crop management measurement parameters.