Crop Information Mapping with Adjustable Field Regions
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Solution Overview
Problem
Existing agricultural mapping technologies, such as using a normalized difference vegetation index (NDVI) map, fail to determine the timing and extent of various agricultural works like sowing, flower thinning, pollination, fertilization, and disease control, as they do not account for crop-specific variations and requirements.
Innovation Solution
An information processing device that adjusts the target region for information acquisition, acquires crop data at a desired resolution, and generates comprehensive field information by integrating data from multiple regions, using a server to construct a database and adjust regions based on user input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a single index map (NDVI) is used for field mapping, then the mapping process is simple and quick, but the ability to determine timing and extent of various agricultural works is insufficient
Solution Approach 1:
The patent segments the field mapping into multiple index layers (NDVI, NDRE, NDWI, etc.) instead of using a single NDVI map. Each index captures different crop characteristics, and the system segments agricultural work determination into multiple categories (sowing, flowering, pollination, fertilization, disease control) based on different index combinations
Solution Approach 2:
The system creates a universal mapping framework that can determine multiple types of agricultural work (sowing, flowering, pollination, fertilization, disease control) using the same multi-index mapping system. The mapping technology becomes multi-functional, serving various agricultural management purposes simultaneously
2Measurement precision
If crop-specific variations are accounted for in mapping, then the precision of agricultural work determination is improved, but the complexity of the mapping system increases
Solution Approach 1:
The patent applies local quality by selecting different index combinations for different crop types and agricultural work stages. For example, NDVI is used for general green vegetation assessment, while NDRE is specifically used for nitrogen status assessment in certain crops. Each region or crop type receives customized index selection based on its specific characteristics
Solution Approach 2:
The system changes parameters by using multiple spectral indices with different formulations (NDVI, NDRE, NDWI) instead of relying on a single parameter. This allows the mapping system to capture different aspects of crop health and adjust to various crop types and growth stages by selecting appropriate index parameters
3Adaptability or versatility
If multiple indices are used to capture various agricultural aspects, then the comprehensiveness of field management is improved, but the data processing complexity increases
Solution Approach 1:
The patent segments the agricultural work determination into distinct categories (sowing, flowering, pollination, fertilization, disease control), each associated with specific index combinations. This segmentation allows the system to handle complex multi-index data by processing each agricultural work type separately with its relevant indices, reducing overall processing complexity
Solution Approach 2:
The system adds a temporal dimension to the multi-index mapping by determining not only the extent but also the timing of agricultural works. This dimensional approach organizes the complex data by when activities occur in the agricultural cycle, making the data more manageable and interpretable
Data Source
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AI summary
An information processing device including an adjustment unit configured to adjust a target region for acquisition of information on a crop; an acquisition unit configured to acquire the information on the crop in the target region; and a generation unit configured to generate the information on the crop in an entire field or part of the field based on the information on the crop in one or more regions.