Market Context — Why This Technology, Why Now

The global smart agriculture market is experiencing rapid growth, projected at 10-15% CAGR, driven by increasing food demand, climate change impacts, and the need for sustainable practices. Farmers and agribusinesses are actively seeking advanced analytics and automation to optimize resource use, minimize waste, and improve crop resilience. This technology aligns perfectly with these trends, offering a critical tool for data-driven decision-making and enhancing operational efficiency across large-scale farming operations worldwide.

Key Competitive Advantages
01

Enables high-frequency, high-resolution crop monitoring by integrating low-frequency high-resolution images (drone/satellite) with high-frequency lower-resolution satellite constellation data.

02

Provides high-accuracy growth prediction by applying a plant growth model within a state transition model, estimating future growth from past image data to support optimal agricultural management decisions.

03

Automatically corrects estimated images using concurrent satellite constellation images, significantly enhancing the reliability of data-driven agricultural management decisions.

Market Opportunity
Large-Scale Agricultural Corporations
$1.5B–$6B globally (AI est.)
These entities have a high demand for reducing labor and material costs in managing vast farmlands, where precision agriculture offers significant efficiency gains.
Large-scale corporate farms Agribusiness conglomerates Food production companies with integrated farming operations
Agricultural Machinery & IT Vendors
$15B–$60B globally (AI est.)
Integrating this technology into smart agricultural machinery and farm management systems could enhance product and service value, providing a competitive differentiator.
Agricultural equipment manufacturers Farm management software providers Drone and satellite imaging service providers
Agricultural Consulting & Data Services
$150M–$600M globally (AI est.)
By offering precise growth data and predictions, these firms could develop new consulting services and data sales businesses.
Agricultural consulting firms Agronomic data analytics providers Crop insurance companies
IP Defensibility — Why Competitors Can't Replicate This
What This Patent Covers

This patent protects an information processing apparatus and method for generating high-frequency, high-resolution crop growth images by integrating various satellite and drone data with a plant growth model. It covers 18 claims, demonstrating robust patentability established through an accelerated examination process and successful responses to examiner objections.

Competitive White Space

This patent primarily covers software-based image processing and growth modeling. White space exists in developing novel sensor hardware for data acquisition, integrating outputs directly into autonomous farm machinery for automated intervention, or applying advanced genetic models for crop resilience.

Economic Impact
~$700K/year estimated agricultural cost reduction per facility (est.)
estimated ROI · USD · AI analysis
ROI Calculation Logic

For large-scale farms (e.g., 1,000ha), precise growth management using this technology could reduce pesticide and fertilizer costs by ~5%, saving ~$350K/year (AI est.). Early detection and control of pests and diseases could improve harvest yield by ~5%, increasing annual revenue by ~$350K (AI est.), assuming $6.5M annual harvest value. Additionally, labor costs for field patrols and growth diagnostics could be ~5% more efficient, saving ~$50K/year (AI est.), assuming $650K annual labor costs. This could result in an annual economic benefit exceeding ~$700K (AI est.), shortening the investment recovery period.

Speed to Market
6× faster than in-house development
This technology was developed by a national research institution, meaning core image processing algorithms and plant growth models are already established. This significantly reduces the R&D time and cost required for a licensee to develop equivalent technology from scratch. Integration into existing image analysis systems or agricultural management platforms primarily involves API linking and data format adjustments, enabling market entry in as little as 6 months.
Competitive Positioning

X: Cost Efficiency
Y: Real-time Capability & Accuracy

Business Models & Applications
☁️ SaaS Monitoring Service
Offer a cloud-based growth monitoring service built on this technology. Provide high-frequency, high-resolution growth data and predictions via monthly/annual subscriptions to support agricultural corporations' decision-making.
🔗 Agricultural Machinery & System Integration License
License this technology's algorithms and data processing modules to agricultural machinery manufacturers and farm management system vendors, enhancing their product and service value.
🤝 Region-Specific Solution Co-Development
Collaborate with local agricultural cooperatives and municipalities to jointly develop and provide precision agriculture solutions optimized for specific regional climates, crops, and field characteristics.
Adjacent Application Opportunities
🌲 Forestry & Forest Management
Forest Resource Monitoring
Integrate satellite and drone imagery to monitor tree growth, detect pests and diseases early, and identify illegal logging across wide areas at high frequency. This could enable accurate estimation of forest resources and enhance disaster risk management, potentially improving operational efficiency by 15-20%.
🏙️ Urban Greening & Infrastructure Management
Urban Tree Health Diagnostics
Regularly monitor the health of urban park trees and street trees. This could support early detection of diseases and the formulation of appropriate maintenance plans, contributing to urban landscape preservation and potentially reducing management costs by 10-15%.
♻️ Environmental Monitoring
Water Quality Anomaly Detection
Detect abnormal occurrences of phytoplankton and algae in water bodies using satellite and drone imagery. Applying growth models, this could serve as an early warning system for water pollution, potentially reducing response times by up to 30%.
Integration Roadmap — Estimated 18-Month Deployment
Phase 1: Proof of Concept & Data Linkage
Duration: 3 months
Conduct basic Proof of Concept (PoC) for this technology and establish integration with existing data collection infrastructure (satellite and drone imagery).
Phase 2: Prototype Development & Validation
Duration: 6 months
Develop a prototype system integrating the core algorithms and conduct field trials in specific areas to evaluate performance and make improvements.
Phase 3: Production Deployment & Optimization
Duration: 9 months
Deploy the system into a production environment based on validation results, and continuously collect data and feedback to enhance prediction model accuracy and optimize operations.
Technical Feasibility
This technology is structured as an information processing apparatus, method, and program, primarily enabling software-based implementation. It is expected to be relatively easy to integrate into existing cloud infrastructure, agricultural management systems, and image analysis platforms via API data linkage and algorithm embedding. Utilizing general-purpose satellite and drone image data eliminates the need for significant new hardware investment, indicating very high technical feasibility.
Success Scenario
Upon adoption, licensees could monitor crop growth across vast farmlands daily, rather than weekly, and at high resolution. This could optimize pesticide application and fertilization timing, potentially reducing material costs by up to 20%. Early detection of pests and diseases and timely intervention could also improve harvest yields by an average of 10%, significantly increasing annual production value.
Patent Record
APPLICATION NO.
特願2022-169847
REGISTRATION NO.
7316004
FILING DATE
2022/10/24
GRANT DATE
2023/07/19
EXPIRATION DATE
2042/10/24
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
2022年11月28日
早期審査に関する事情説明書
2022年11月28日
出願審査請求書
2022年12月23日
早期審査に関する通知書
2023年03月07日
拒絶理由通知書
2023年04月18日
手続補正書（自発・内容）
2023年04月18日
意見書
2023年06月27日
特許査定