Market Context — Why This Technology, Why Now

The digital transformation of the food sector is accelerating, driven by consumer expectations for personalized nutrition, seamless online ordering, and transparent ingredient sourcing. Regulatory bodies are also increasing scrutiny on food labeling and allergen information, demanding higher data accuracy. Companies that can efficiently process and validate vast amounts of food data will lead in customer trust and operational efficiency, gaining a critical competitive advantage in this data-intensive environment.

Key Competitive Advantages
01

Generates highly reliable food data by removing noise from web sources using AI and a unique two-stage validation logic.

02

Establishes market first-mover advantage due to only 2 prior art documents, indicating high uniqueness and technical superiority.

03

Ensures robust patent protection, having overcome rejection notices during examination, indicating low invalidation risk from competitors.

Market Opportunity
Food Delivery & E-commerce Platforms
$120B–$140B globally (AI est.)
Driven by evolving consumer needs and technological advancements, providing highly accurate information is a key differentiator, fueling market growth.
Major food delivery services Online grocery retailers E-commerce solution providers
Restaurant & Retail Chains
$2.5T–$3.0T globally (AI est.)
Addressing labor shortages, enhancing efficiency through data utilization, and strengthening customer engagement are urgent priorities, accelerating DX investments.
Large restaurant groups Supermarket chains Food service management companies
Health & Nutrition Management Services
$13.5B–$15.0B globally (AI est.)
Growing individual health consciousness and increasing demand for personalized nutrition guidance leveraging AI are anticipated.
Digital health app developers Corporate wellness providers Personalized diet plan services
IP Defensibility — Why Competitors Can't Replicate This
What This Patent Covers

The patent's history of overcoming a rejection notice through precise amendments and arguments confirms its robustness and validity, indicating a strong right unlikely to be invalidated by competitors. With only two prior art documents, this patent covers a broad range of processes from information collection to high-reliability data generation, demonstrating high originality.

Competitive White Space

This patent primarily covers the software logic for reliable food data generation. White space exists in developing specialized hardware for food image acquisition in diverse environments or integrating this data with advanced supply chain optimization algorithms.

Economic Impact
~$1.0M/year estimated cost reduction per facility (est.)
estimated ROI · USD · AI analysis
ROI Calculation Logic

Assuming a company processes 1 million food information items annually for e-commerce or food delivery, a 3% current error rate from manual input and visual checks could result in a ~$3.50 (AI est.) loss per item. By reducing the error rate to 0.5% with this technology, annual losses could decrease by ~$850K (AI est.). Additionally, a 20% reduction in manual data entry could save ~$150K (AI est.) in labor costs annually, totaling an estimated ~$1.0M/year in economic benefits.

Speed to Market
6× faster than in-house development
This technology could reduce the typical 2.5-year development period for building a neural network model and two-stage reliability logic from scratch to approximately 0.5 years. The basic AI model architecture is already established and patented, allowing licensees to focus on API integration and data consolidation with existing systems, free from IP infringement risks. This significantly shortens time-to-market, establishing a competitive advantage.
Competitive Positioning

X: Data Reliability
Y: Operational Efficiency

Business Models & Applications
🍽️ 🍽️ Data Provision Service
A SaaS model providing highly reliable food information via API, enabling food delivery and e-commerce platforms to integrate it into their services, enhancing customer satisfaction and operational efficiency.
💻 💻 System Licensing
Licensing for restaurant chains and food manufacturers to integrate this technology into their internal menu development, quality control, and marketing strategies, fostering data-driven decision-making.
📈 📈 Collaborative Solution Development
Promising co-development model with health management app or smart appliance manufacturers to create new customer experiences, such as automatic calorie calculation or recipe suggestions based on food recognition.
Adjacent Application Opportunities
🍳 Smart Kitchen
AI-Powered Smart Cooking Appliances
Develop smart ovens or refrigerators with integrated food recognition AI. This could automatically identify dishes during cooking, suggest optimal cooking modes, or manage ingredient inventory, revolutionizing the user's cooking experience by ~30% efficiency gain.
🏭 Food Manufacturing & Quality Control
AI Quality Inspection for Production Lines
Integrate this technology into food factories to analyze food images in real-time on production lines. This could automatically detect foreign objects or defective products, significantly improving quality inspection accuracy and speed by over 50%.
🌍 Tourism & Inbound Services
Multilingual Menu Information System
Build a system that automatically recognizes restaurant menu images and displays dish names, allergen information, and ingredients in multiple languages. This could enhance the dining experience for international tourists by improving information accessibility by ~80%.
Integration Roadmap — Estimated 15-Month Deployment
Phase 1: Technical Validation & Data Integration Design
Duration: 3 months
Design API integration between the core technology modules and existing systems, and verify recognition accuracy with initial datasets.
Phase 2: Model Adaptation & System Construction
Duration: 6 months
Retrain and optimize the AI model for specific licensee needs, build the information processing system, and conduct internal testing.
Phase 3: Pilot Program & Production Deployment
Duration: 6 months
Evaluate performance through pilot programs in limited environments, incorporate feedback, then gradually proceed with production environment deployment.
Technical Feasibility
This technology is designed for easy integration into existing cloud infrastructure or on-premise environments as a program. The information collection unit, estimation unit, and two-stage validation logic described in the patent claims are expected to integrate smoothly via API with existing databases and image processing systems. As it relies on general telecommunication networks for information acquisition, no large-scale new equipment investment is required, allowing for deployment akin to a software update.
Success Scenario
Upon adoption, this technology could reduce manual effort for updating online menus and product catalog data by approximately 70% annually. This is estimated to shorten new product market launch cycles by 20%, enabling services that consistently reflect the latest trends. Furthermore, it could significantly reduce the workload for handling customer inquiries related to food information, optimizing operational costs while enhancing customer satisfaction.
Patent Record
APPLICATION NO.
特願2021-052299
REGISTRATION NO.
7635976
FILING DATE
2021/03/25
GRANT DATE
2025/02/17
EXPIRATION DATE
2041/03/25
PATENT HOLDER
学校法人東京電機大学
Examination History
2024年03月14日
出願審査請求書
2024年11月19日
拒絶理由通知書
2024年12月13日
意見書
2024年12月13日
手続補正書（自発・内容）
2025年01月07日
特許査定