Market Context — Why This Technology, Why Now

The global agricultural sector is undergoing a profound transformation, driven by increasing pressure to enhance food production sustainably while minimizing environmental impact. Regulatory bodies are pushing for reduced fertilizer and water usage, creating a strong market pull for technologies that enable precise resource management. This patent aligns perfectly with the rise of smart farming, where data-driven decisions are crucial for competitive advantage and meeting consumer demand for eco-friendly produce.

Key Competitive Advantages
01

Achieves high-precision fertilizer application and growth prediction, overcoming limitations of conventional remote sensing data through situational correction.

02

Enables real-time optimization by continuously deriving optimal crop-related values, accounting for weather and environmental changes during observation.

03

Optimizes resource allocation, such as fertilizers and water, based on accurate, corrected data, potentially reducing waste by up to 15%.

Market Opportunity
Smart Agriculture Solutions
$1B globally (AI est.)
Rapidly expanding demand for precision agriculture utilizing IoT sensors and AI makes high-precision data analysis a core technology driving market growth.
Smart farming platform providers Agricultural software developers IoT sensor manufacturers for agriculture
Agricultural Machinery and Material Manufacturers
$1.5B globally (AI est.)
This technology could enhance product value and differentiation by integrating with high-performance agricultural machinery to automate optimal fertilization and spraying.
Major agricultural equipment OEMs Fertilizer and chemical producers Precision seeding and spraying system developers
Environmental and Sustainability Services
$3.5B globally (AI est.)
Reducing environmental impact through optimized fertilizer use directly supports corporate sustainability goals and contributes to ESG management initiatives.
Environmental consulting firms ESG reporting and compliance providers Carbon credit verification services for agriculture
IP Defensibility — Why Competitors Can't Replicate This
What This Patent Covers

This patent represents a robust and stable right, having been granted after extensive examination against numerous prior art references and multiple office actions, including a pre-appeal examination. With 18 claims, it broadly covers the technology for deriving crop-related values by correcting remote observation data based on environmental conditions, offering strong protection against invalidation.

Competitive White Space

This patent primarily covers data correction and derivation. Licensees could develop complementary IP in novel remote sensing hardware, advanced crop disease detection algorithms, or fully autonomous robotic farming systems.

Economic Impact
This technology could generate ~$10K/year (AI est.) in economic benefits for a medium-sized farm, with potential for over ~$50K/year (AI est.) at larger scales (est.).
estimated ROI · USD · AI analysis
ROI Calculation Logic

For a medium-sized farm (10ha, annual fertilizer cost ~$50K (AI est.)), optimizing fertilizer application with this technology could reduce fertilizer costs by 15%, leading to ~$5K/year (AI est.) in direct savings. Additionally, a 5% increase in yield could boost revenue by ~$5K/year (AI est.) (e.g., 5% of ~$135K (AI est.) revenue). Combined with a 5% reduction in labor costs from operational efficiency (~$0.5K/year (AI est.) from ~$20K/year (AI est.) labor), the total economic impact is estimated at ~$10K/year (AI est.). Scaling up could achieve over ~$50K/year (AI est.) in economic benefits.

Speed to Market
5× faster than in-house development
This technology leverages established basic algorithms for remote sensing data correction. The components described in the claims can be implemented using general-purpose sensors and data processing techniques. Existing research can form the basis for crop growth models and fertilization calculation formulas, significantly shortening foundational development time. This allows licensees to reduce R&D time and costs, aiming for rapid commercialization.
Competitive Positioning

X: Data Accuracy and Reliability
Y: Resource Efficiency Contribution

Business Models & Applications
☁️ SaaS Data Analytics Service
Offer a cloud-based data analytics platform powered by this technology. Farmers could subscribe monthly to access high-precision fertilizer application and growth prediction data.
🤝 Technology Licensing
License the algorithms and system architecture of this technology to existing agricultural machinery manufacturers and smart agriculture solution providers.
📈 Consulting and Implementation Support
Provide comprehensive consulting services, from planning to operation, for large-scale farms and agricultural corporations implementing precision agriculture systems using this technology.
Adjacent Application Opportunities
🏞️ 環境モニタリング
Forest and Water Resource Health Assessment
This system could apply environmental correction to satellite or drone data of forests and water bodies, accurately deriving vegetation indices and water quality metrics. This has the potential to aid in early detection of environmental changes and improve resource management efficiency by up to 20%.
🏗️ 建設・インフラ管理
Infrastructure Degradation Prediction and Inspection
By correcting remote sensor data on infrastructure conditions for environmental factors (temperature, humidity, wind), this technology could more accurately predict degradation progress and optimal repair times. This could reduce inspection costs by an estimated 15-20%.
災害対策・防災
Disaster Risk Assessment and Damage Prediction
This technology could enhance the accuracy of disaster risk assessment by correcting geographical data for high-risk areas with real-time weather data, precisely analyzing soil moisture and ground stability. This could improve early warning system accuracy by 10-15% for floods and landslides.
Integration Roadmap — Estimated 12-Month Deployment
Requirements Definition and Data Integration Design
Duration: 3 months
Define integration methods with the licensee's existing systems and observation data, and design customizations for the correction algorithm.
System Development and Pilot Testing
Duration: 6 months
Develop the system based on the design and conduct small-scale pilot tests in actual fields to verify data correction accuracy and the effectiveness of crop-related value derivation.
Full-Scale Operation and Impact Verification
Duration: 3 months
Optimize the system based on pilot results and commence full-scale operation. Evaluate and improve business contribution through continuous data collection and impact measurement.
Technical Feasibility
This technology is designed to integrate with existing general-purpose remote sensing infrastructure, including drones, satellite imagery, field sensors, and weather data. The patent claims define functional blocks such as data acquisition, correction, and derivation units, which are structured for easy integration as software modules into existing agricultural management systems or cloud platforms. This indicates high technical feasibility for deployment, requiring minimal new hardware investment and allowing for implementation similar to a software update.
Success Scenario
Implementing this technology could potentially reduce fertilizer waste by up to 15%, leading to tens of thousands of dollars in annual cost savings and reduced environmental impact. Furthermore, maximizing yields based on highly accurate growth predictions could enable more strategic production and sales planning, potentially increasing agricultural business profitability by over 10%.
Patent Record
APPLICATION NO.
特願2022-015143
REGISTRATION NO.
7688915
FILING DATE
2022/02/02
GRANT DATE
2025/05/28
EXPIRATION DATE
2042/02/02
PATENT HOLDER
国立研究開発法人農業・食品産業技術総合研究機構
Examination History
2024年02月08日
出願審査請求書
2024年02月08日
手続補正書（自発・内容）
2024年11月12日
拒絶理由通知書
2024年12月05日
意見書
2024年12月05日
手続補正書（自発・内容）
2025年03月05日
拒絶査定
2025年04月07日
手続補正書（自発・内容）
2025年04月25日
審査前置移管
2025年05月07日
審査前置移管通知
2025年05月13日
特許査定
2025年05月13日
審査前置登録