Market Context — Why This Technology, Why Now

The global push for smart agriculture and AgriTech adoption is accelerating, driven by demographic shifts, climate change impacts, and demand for higher food production efficiency. Automation and AI are critical to overcoming labor shortages and optimizing resource-intensive operations. This technology aligns perfectly with these trends, enabling farms to maximize output with fewer resources and providing a competitive edge for equipment manufacturers and service providers in a rapidly digitizing sector.

Key Competitive Advantages
01

Achieves High-Precision Resource Optimization by accurately estimating task completion time based on operator skill and autonomous machine performance, automatically selecting optimal resources and eliminating waste.

02

Accelerates Agricultural Digital Transformation (DX) by providing optimal operational guidance for companies adopting remote and autonomous agricultural machinery, reducing adoption barriers and driving efficient, sustainable transitions.

03

Offers Long-Term Market Advantage by providing exclusive market advantage for products and services until ~2042, enabling licensees to establish a strong business foundation ahead of competitors.

Market Opportunity
Large Agricultural Corporations & Farms
$300M–$350M domestically (AI est.)
These entities face significant labor shortages and high demand for operational efficiency. They are eager to adopt advanced technologies for productivity gains. This technology's cost reduction and task optimization directly enhance their competitiveness.
Large-scale corporate farms Agribusiness conglomerates Agricultural cooperatives managing extensive operations
Agricultural Machinery Manufacturers
$50M–$100M domestically (AI est.)
This technology directly enhances the value of autonomous and remote-controlled machinery. Integrating this system allows for product differentiation and the offering of new solutions, establishing a competitive edge in the market.
Global agricultural equipment OEMs Drone and robotics manufacturers for agriculture Smart farming solution providers
Agricultural Support Service Providers
$50M–$100M domestically (AI est.)
For farm work outsourcing and smart agriculture consulting firms, this technology dramatically improves service quality and efficiency. It enhances value propositions for clients and contributes to business expansion.
Farm management software companies Agricultural consulting firms Remote sensing and data analytics providers for agriculture
IP Defensibility — Why Competitors Can't Replicate This
What This Patent Covers

This patent protects a selection device, program, and method for optimizing agricultural work by matching tasks with the most suitable remote operators or autonomous machinery based on skill and performance. Its strong claims and successful grant without office actions, following examination against nine prior art documents, indicate high stability and a clear scope of protection.

Competitive White Space

Potential white space exists in advanced sensor integration for real-time environmental adaptation, predictive maintenance systems for agricultural machinery, and the development of novel autonomous execution modules for specific farm tasks not covered by this resource selection patent.

Economic Impact
~$100K/year estimated agricultural cost reduction per large corporation (est.)
estimated ROI · USD · AI analysis
ROI Calculation Logic

Large agricultural corporations could achieve a 5% reduction in annual farm operating costs, estimated at ~$2.0M per company (AI est.). This translates to an annual saving of ~$100K per company (AI est.).

Speed to Market
4× faster than in-house development
This technology's core algorithm, which evaluates operator skill and autonomous machine performance to estimate task completion times, is already patented and fully developed. This significantly reduces the need for licensees to develop systems from scratch. By focusing on API integration and data synchronization with existing agricultural support systems or IoT platforms, rapid market entry and service deployment are achievable.
Competitive Positioning

X: Cost Efficiency
Y: Resource Optimization Precision

Business Models & Applications
☁️ SaaS Platform Provision
Offer a SaaS platform that matches agricultural task requesters with operators and machinery. Revenue streams include monthly subscription fees and transaction commissions.
🤝 Technology Licensing
License this technology's algorithms and system modules to agricultural machinery manufacturers and smart farming system developers. This promotes integration into their products and services.
📈 Agricultural DX Consulting
Provide implementation support for agricultural optimization solutions, centered on this technology, and data-driven operational improvement consulting for large agricultural corporations.
Adjacent Application Opportunities
🏗️ Construction & Civil Engineering
Optimized Deployment of Heavy Equipment Operators & Autonomous Machinery
Deploy optimal resources in real-time for construction tasks, based on heavy equipment operator skill and autonomous machinery performance data. This could shorten project timelines by up to 15%, reduce operational costs, and enhance site safety.
📦 Logistics & Warehousing
Task Optimization for Autonomous Mobile Robots & Warehouse Personnel
Optimize inventory movement and sorting tasks by considering the performance of autonomous mobile robots (AMRs) and the proficiency of picking personnel. This could maximize logistics efficiency by 20% and significantly reduce lead times.
🧹 Facility Management
Optimized Patrols & Tasks for Cleaning & Security Robots
Plan optimal patrol routes and tasks for cleaning and security robots or assigned personnel based on their performance and skills in commercial facilities or factories. This could lead to a 25% improvement in cleaning quality and maximized security efficiency.
Integration Roadmap — Estimated 17-Month Deployment
Phase 1: Requirements & Design
Duration: 4 months
Analyze the licensee's existing systems and agricultural workflows to define specific requirements for implementing this technology. Subsequently, develop the system integration architecture and customization plan.
Phase 2: Prototype Development & Validation
Duration: 9 months
Based on the design, develop a prototype of the core algorithm tailored to the licensee's environment. Conduct functional and performance validation in a small-scale test environment to identify and resolve issues.
Phase 3: Production Deployment & Optimization
Duration: 4 months
Deploy the validated system into the production environment and commence real-world agricultural operations. Based on operational data, fine-tune algorithm parameters and implement functional improvements for continuous optimization.
Technical Feasibility
This technology primarily consists of software algorithms for data-driven selection of agricultural task resources. It could be integrated relatively easily into existing agricultural support systems or IoT platforms via API linkage or module addition. As it does not require extensive new hardware and can leverage existing infrastructure, the technical adoption barrier is estimated to be low.
Success Scenario
Upon adoption, large agricultural corporations could automatically assign optimal operators and machinery based on fluctuating task requirements, weather conditions, and equipment status. This could reduce task planning time by up to 30% and decrease machine idle time by 20%. Consequently, an estimated 15% annual productivity improvement and maximized profitability are anticipated.
Patent Record
APPLICATION NO.
特願2021-117320
REGISTRATION NO.
7635984
FILING DATE
2021/07/15
GRANT DATE
2025/02/17
EXPIRATION DATE
2041/07/15
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04月12日
出願審査請求書
2025年01月28日
特許査定