Market Context — Why This Technology, Why Now

The global manufacturing and automotive sectors are undergoing a profound shift towards Industry 4.0, demanding advanced automation, AI-driven analytics, and predictive capabilities. Regulatory pressures for product quality and safety are intensifying, while the cost of human error and unplanned downtime continues to rise. This technology aligns perfectly with these trends, offering a scalable solution to enhance operational resilience and meet stringent quality standards across complex production environments.

Key Competitive Advantages
01

Detect subtle changes and complex conditions accurately, significantly reducing false detection rates by combining object depth information and similarity.

02

Accelerate inspection processes by ~50%, replacing manual visual checks by skilled workers, reducing labor costs and increasing production throughput.

03

Enable predictive maintenance by forecasting future parameters from similarity data, detecting failure precursors early and reducing unplanned downtime risk by up to 30%.

Market Opportunity
Automotive and Vehicle Inspection
$1.5B–$10B globally (AI est.)
The evolution of autonomous driving technologies is driving a surge in demand for high-precision inspection and diagnostics of complex vehicle components and systems. This technology could contribute to detecting minute anomalies and predicting wear in parts.
Automotive Tier 1 suppliers Autonomous vehicle component manufacturers Vehicle inspection equipment providers Automotive diagnostic software developers
Manufacturing Quality Control
$25B–$30B globally (AI est.)
Industrial advancement and labor shortages are accelerating the adoption of AI-driven automated inspection and predictive maintenance. This technology could enhance inspection efficiency and product quality across diverse manufacturing sectors.
Industrial automation solution providers Quality assurance equipment manufacturers Smart factory technology developers Large-scale discrete manufacturing companies
IP Defensibility — Why Competitors Can't Replicate This
What This Patent Covers

This patent protects an information processing system that predicts parameters of a first moving object by acquiring depth information from its image, determining its similarity to a second moving object, and using the second object's parameters and the similarity. The claims are robust and broad, having overcome three prior art references during examination, indicating strong originality and patentability.

Competitive White Space

While this patent covers core object similarity and depth-based parameter prediction, white space exists in integrating this technology with specific robotic manipulation systems or developing novel sensor fusion techniques beyond standard cameras and depth sensors. Further IP could also be built around specialized data compression for real-time edge deployment in highly constrained environments.

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

In manufacturing quality inspection, this technology could reduce annual labor costs by $75K (AI est.) by improving efficiency by 50% for 3 skilled operators (assuming ~$50K/operator/year). Additionally, if unplanned downtime causes $10K (AI est.) in production loss per month, predictive maintenance could reduce stops by 20%, avoiding ~$20K/year (AI est.) in losses. Total direct savings could exceed $95K/year (AI est.). Considering indirect benefits like reduced defect waste and recall risks from lower false detection rates, the overall economic impact could exceed $200K/year (AI est.).

Speed to Market
6× faster than in-house development
The core algorithm for this technology is established, and the main information processing flow is clear from the patent claims. It can easily integrate with general-purpose hardware like existing cameras and depth sensors, minimizing the need for extensive new development. Key technical elements for proof-of-concept are already available in the market, allowing licensees to significantly shorten development cycles and accelerate market entry.
Competitive Positioning

X: Prediction Accuracy and Stability
Y: Implementation Flexibility and Cost-Effectiveness

Business Models & Applications
👨‍🏭 Inspection and Predictive Maintenance System Provider
Offer automated inspection equipment and predictive maintenance software incorporating this technology to manufacturers, enhancing equipment uptime and reducing maintenance costs.
📊 Data Diagnostics Service
Provide data analysis services offering anomaly diagnostics and deterioration prediction reports for client equipment and products, based on acquired object depth and similarity data.
💡 Intellectual Property Licensing
License the intellectual property rights of this technology in specific industries or product sectors, enabling partner companies to accelerate their product development and service expansion.
Adjacent Application Opportunities
🚗 Autonomous Driving & Mobility
Traffic Infrastructure Monitoring and Diagnostics
Diagnose the deterioration of transportation infrastructure like roads, bridges, and railways using depth information and similarity from images captured by patrol vehicles or drones. Early anomaly detection enables proactive repairs, potentially extending infrastructure lifespan and reducing maintenance costs by up to 25%.
🚀 Aerospace Industry
Aerospace Component Manufacturing Quality Inspection
Implement this technology in aerospace component and satellite equipment manufacturing to automatically detect minute defects and dimensional deviations with high precision. This could dramatically streamline quality assurance processes for complex-shaped parts and multi-connection assemblies, potentially reducing inspection time by 40%.
Integration Roadmap — Estimated 12-Month Deployment
Proof of Concept and Requirements
Duration: 3 months
Validate the technology's effectiveness using existing licensee data or simulation environments, then define specific implementation goals and system requirements.
System Development and Testing
Duration: 6 months
Based on PoC results, develop a prototype system incorporating this technology, design integration with existing systems, and conduct real-world testing and adjustments.
Production Deployment and Optimization
Duration: 3 months
Deploy the developed system into the production environment, monitor performance using actual operational data, and drive continuous improvement and optimization for full adoption.
Technical Feasibility
This technology utilizes an architecture based on existing digital cameras, depth sensors, and general-purpose information processing units, potentially eliminating the need for extensive capital investment by licensees. The information processing flow described in the patent claims—acquiring depth information from images, determining similarity, and predicting parameters—is well-suited for software implementation as an add-on to existing systems. Integration with current production management systems or inspection equipment is also deemed relatively straightforward via APIs.
Success Scenario
Implementing this technology could significantly reduce human error in manufacturing inspection processes, potentially cutting false detection rates by over 50%. This is estimated to improve product shipment quality by an average of 15%, enhancing customer trust and brand value. Furthermore, predictive maintenance could reduce production stoppages due to equipment failure by 20% annually, potentially increasing operational uptime by up to 5%.
Patent Record
APPLICATION NO.
特願2021-163903
REGISTRATION NO.
7779507
FILING DATE
2021年10月05日
GRANT DATE
2025年11月25日
EXPIRATION DATE
2041年10月05日
PATENT HOLDER
国立大学法人　東京大学
Examination History
2024年08月06日
出願審査請求書
2025年06月24日
拒絶理由通知書
2025年08月12日
意見書
2025年08月12日
手続補正書（自発・内容）
2025年10月28日
特許査定