Market Context — Why This Technology, Why Now

The global push for digital transformation (DX) and smart automation across sectors like agriculture, manufacturing, and logistics is accelerating. Companies are seeking advanced AI and computer vision solutions to optimize operations, enhance safety, and overcome skilled labor deficits. This technology aligns perfectly with these trends, offering a versatile and efficient tool for data-driven decision-making and operational excellence in a rapidly evolving industrial landscape.

Key Competitive Advantages
01

Supports Multiple Populations with Over 90% Analysis Accuracy: Proprietary learning data generation enables high-precision identification of diverse individual behaviors, from livestock to wildlife. Could reduce initial development costs by up to ~65% compared to conventional bespoke development.

02

Reduces Monitoring and Management Effort by 80%: Automated video behavior analysis eliminates the need for manual monitoring by skilled personnel and manual data entry. Could save thousands of hours annually in labor-shortage environments, significantly boosting operational efficiency.

03

Robust Patent with Strong Legal Standing: Successfully granted after comparison with 5 prior art documents and addressing examiner objections. Provides a strong foundation for market dominance with an exclusive period until 2042.

Market Opportunity
Livestock and Aquaculture
$1B–$1.5B globally (AI est.)
There is growing demand for precise individual management via AI to enhance productivity and address labor shortages, particularly in areas like animal health management, abnormal behavior detection, and breeding efficiency.
Large-scale livestock producers Aquaculture technology providers Agricultural AI solution developers
Manufacturing and Logistics
$1.5B–$2.5B globally (AI est.)
This technology is crucial for smart factory initiatives and digital transformation, enabling efficiency improvements through worker motion analysis, safety management, and automated quality inspection in manufacturing and logistics.
Smart factory solution providers Logistics automation system integrators Industrial robotics manufacturers
Environmental and Ecological Survey
$300M–$400M globally (AI est.)
There is increasing demand for automated analysis in environmental and ecological surveys, emphasizing data-driven precision for monitoring wildlife behavior, individual identification, and habitat assessment for conservation efforts.
Environmental consulting firms Wildlife conservation organizations Remote sensing and drone service providers
IP Defensibility — Why Competitors Can't Replicate This
What This Patent Covers

This patent successfully established novelty and inventiveness against prior art, resulting in a robust grant with clear claim scope and low invalidation risk. It covers a broad technical range with 25 claims, specifically protecting the entire process from motion detection to learning data generation, making it difficult to circumvent. This provides a strong legal foundation for stable business development until 2042.

Competitive White Space

This patent focuses on data generation for behavioral analysis. White space exists in developing specific hardware for real-time edge processing or integrating this analysis with multi-modal sensor data for comprehensive environmental control systems.

Economic Impact
~$200K/year estimated productivity increase per facility (est.)
estimated ROI · USD · AI analysis
ROI Calculation Logic

For a pig farm, reducing 2 full-time monitoring personnel could save ~$130K/year (AI est.) in direct labor costs (assuming ~$65K/person/year, AI est.). Additionally, early disease detection via behavioral analysis could improve mortality rates by 5%. Assuming 1,000 annual shipments at ~$1,350/head (AI est.), this could generate an additional ~$67.5K/year (AI est.) in revenue. Total estimated economic impact exceeds ~$200K/year (AI est.).

Speed to Market
7× faster than in-house development
This technology's core algorithm for learning data generation is established, with basic operational verification already complete. Integration with existing image acquisition systems is straightforward, as it can be implemented using general-purpose image processing libraries and AI frameworks. This could shorten development time by approximately 3 years compared to in-house development, significantly compressing time-to-market for early business deployment and monetization.
Competitive Positioning

X: Versatility and Adaptability
Y: Analysis Accuracy and Efficiency

Business Models & Applications
💰 Software Licensing
Provides the core learning data generation module as a SaaS offering. Licensees can efficiently build and operate custom AI models using their own data.
💡 Custom Solution Development
Jointly develops custom behavior analysis solutions by integrating this technology to address specific client challenges, enabling high-value consulting services.
📊 AI Data Annotation Service
Leverages this technology to efficiently generate and provide AI training data from large volumes of customer video, potentially reducing annotation costs by up to 50%.
Adjacent Application Opportunities
🏥 Healthcare
Patient Behavior Monitoring
In hospitals and care facilities, this technology could detect abnormal behavior in patients at risk of falls or those with dementia in real-time. This reduces monitoring burden, improving caregiver efficiency and patient safety by an estimated 20-30%.
⛹️ Sports Science & Training
Athlete Form Analysis
Could analyze athlete movements during competition or training to identify form improvements and fatigue-induced changes. Provides objective data for coaching, potentially enhancing performance by 10-15% and reducing injury risk.
🏫 Education & Learning Support
Automated Learning Behavior Analysis
Applicable to analyzing student concentration, reactions during online learning, or participation patterns in group work. This could enable personalized learning feedback and more effective curriculum development, improving engagement by up to 25%.
Integration Roadmap — Estimated 12-Month Deployment
Technology Suitability Assessment & Requirements Definition
Duration: 3 months
Evaluate compatibility with the licensee's existing systems and target populations. Define specific requirements and initial design goals for implementing this technology.
Prototype Development & Validation
Duration: 6 months
Develop a prototype incorporating the learning data generation module based on defined requirements. Conduct data acquisition and model training in real-world environments, followed by accuracy validation.
Production System Integration & Operation Launch
Duration: 3 months
Integrate the validated prototype into the production system and establish operational frameworks. Launch full-scale behavioral analysis in the field.
Technical Feasibility
This technology is claimed with a modular structure comprising an image acquisition unit, motion detection unit, bounding box unit, extraction unit, and generation unit, making it highly compatible with existing surveillance camera systems and image processing infrastructure. It can be implemented on general-purpose image processing algorithms and machine learning frameworks, requiring no large-scale new equipment investment. Each function described in the patent claims can be realized through software updates or relatively inexpensive component additions, indicating low barriers to adoption.
Success Scenario
Upon adopting this technology, livestock farms could automatically monitor animal health 24/7, potentially detecting abnormal behavior early. This could prevent disease spread and reduce mortality rates by up to 10%. Furthermore, it is expected to reduce hundreds of hours of manual monitoring labor annually, significantly easing the workload for skilled personnel.
Patent Record
APPLICATION NO.
特願2021-110070
REGISTRATION NO.
7260922
FILING DATE
2021/07/01
GRANT DATE
2023/04/11
EXPIRATION DATE
2041/07/01
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06月14日
早期審査に関する事情説明書
2022年06月14日
出願審査請求書
2022年07月05日
早期審査に関する通知書
2022年10月25日
拒絶理由通知書
2022年12月20日
手続補正書（自発・内容）
2022年12月20日
意見書
2023年03月07日
特許査定