Market Context — Why This Technology, Why Now

The accelerating adoption of Industry 4.0 initiatives, coupled with increasing regulatory pressures for workplace safety and efficiency, underscores the critical need for advanced indoor positioning. Traditional GPS is insufficient for complex indoor environments, creating a significant market gap. This technology provides a robust solution for precise asset tracking, autonomous robot navigation, and personnel monitoring, essential for optimizing supply chains and enhancing operational resilience across diverse industries globally.

Key Competitive Advantages
01

Achieves 1.5× higher positioning accuracy while reducing data aggregation time by 66% compared to conventional methods.

02

Ensures stable, high-accuracy positioning in GPS-denied or high-interference environments, leveraging existing infrastructure.

03

Provides robust patent protection, validated against 6 prior art documents, securing long-term market differentiation.

Market Opportunity
Smart Factories
$5B–$10B globally (AI est.)
Manufacturing sites are seeing a surge in demand for automation, production efficiency, and real-time tracking of parts and tools. This technology could contribute to precise control of AGVs and safety management through worker location tracking.
Industrial automation solution providers Robotics manufacturers Large-scale factory operators
Logistics and Warehousing
$5B–$10B globally (AI est.)
The expansion of e-commerce and labor shortages necessitate the adoption of automated guided vehicles (AGVs) and precise inventory location management within warehouses. This technology could support efficient picking operations.
Warehouse automation system integrators E-commerce logistics providers Automated material handling equipment suppliers
Healthcare and Elderly Care
$3B–$6B globally (AI est.)
There is growing demand in hospitals and care facilities for improving operational efficiency, enabling rapid response in emergencies, and monitoring patients and medical equipment through accurate location tracking.
Hospital management system developers Medical device tracking solution providers Elderly care technology companies
Smart Retail
$2B–$4B globally (AI est.)
This technology could enhance the shopping experience and optimize store operations by analyzing customer flow, optimizing shelf layouts, and assisting with product searches. It also enables personalized service delivery.
Retail analytics platform providers In-store navigation system developers Large retail chains
IP Defensibility — Why Competitors Can't Replicate This
What This Patent Covers

This patent protects a position estimation system and method, specifically covering the combination of position fingerprinting and PhyC-SN for high-accuracy, rapid data aggregation. Its robust claims, refined through a rigorous examination process against prior art, provide a strong, defensible intellectual property foundation.

Competitive White Space

This patent primarily covers the algorithmic combination for position estimation. White space exists in developing novel sensor hardware integrations, advanced predictive analytics for movement patterns, or specialized AI for environmental adaptation beyond the core estimation method.

Economic Impact
~$100K/year estimated operational cost savings per facility (est.).
estimated ROI · USD · AI analysis
ROI Calculation Logic

Implementing this technology could reduce asset search time and misplacement losses in large warehouses or factories. Specifically, a 10% reduction in asset search time for 20 workers (assuming an annual labor cost of $40,000/worker (AI est.)) could save $80,000 (AI est.). A 5% reduction in misplacement losses for $666,667 (AI est.) of annual inventory could save an additional $33,333 (AI est.). This totals over $113,000/year in estimated cost savings (AI est.), achieved through improved worker productivity and optimized asset management.

Speed to Market
8× faster than in-house development
This technology is based on established algorithms like position fingerprinting and PhyC-SN, with a clearly defined system architecture within the patent. The detailed processes for both learning and estimation phases eliminate the need for complex fundamental research or algorithm development. This enables early implementation from the PoC phase for licensees, potentially shortening time-to-market by approximately 3.5 years compared to in-house development.
Competitive Positioning

X: Positioning Accuracy & Stability
Y: Implementation Cost Efficiency

Business Models & Applications
🤝 Licensing Model
This model involves licensing the intellectual property of this technology to adopting companies, enabling its integration into existing products and services. It supports rapid market entry and the acquisition of a technological advantage.
🔗 Solution Integration Model
This model allows for the integration of this technology with a licensee's existing IoT platforms or operational management systems, enabling new solution offerings leveraging high-accuracy location data.
📊 Data Service Model
This model involves anonymizing and aggregating high-accuracy location data obtained through this technology, then offering it as analytical data for specific industries or regions. It contributes to the creation of new data-driven businesses.
Adjacent Application Opportunities
🏭 Smart Factory
Precision Control for Autonomous Robots
Integrating this technology into AGVs and AMRs in factories could enable precise position control within ± centimeters, even in environments with radio interference or complex layouts. This has the potential to fully automate inter-line material transport and operations in hazardous areas, maximizing production efficiency.
🚚 Logistics & Warehousing
Real-time Inventory and Asset Tracking
Tracking forklifts, pallets, and high-value goods in large warehouses with this technology could provide real-time inventory status and accurate location management. This is expected to dramatically reduce search times, minimize mis-shipments, and automate inventory processes, leading to significant reductions in logistics costs.
🏥 Healthcare & Elderly Care
Patient and Medical Device Monitoring
In hospitals and care facilities, precisely locating patients and elderly individuals with dementia could prevent wandering and enable rapid response in emergencies. Real-time management of expensive medical equipment could reduce search times and improve utilization rates, contributing to digital transformation in healthcare.
Integration Roadmap — Estimated 19-Month Deployment
Requirements Definition & PoC
Duration: 5 months
Analyze specific challenges and existing infrastructure of the licensee to define implementation requirements. Conduct a Proof of Concept (PoC) in a small-scale environment to verify technical suitability and effectiveness.
System Development & Testing
Duration: 9 months
Based on PoC results, proceed with integration design and development for existing systems. This includes building the fusion center, optimizing observation sensor placement, implementing data linkage modules, and conducting comprehensive testing.
Production Deployment & Optimization
Duration: 5 months
Deploy the developed and tested system into the production environment and commence operations. Analyze data from initial operations to adjust parameters and optimize algorithms, aiming for continuous performance improvement and maximum effectiveness.
Technical Feasibility
This technology features a software-centric architecture that aggregates and processes parameter information detected by general-purpose observation sensors in a fusion center. It can leverage existing infrastructure like Wi-Fi or Bluetooth as observation sensors, allowing integration into existing systems much like a software update, without significant capital investment. The technical hurdles for adoption are considered low.
Success Scenario
Implementing this technology could reduce asset search time in factories and warehouses by up to 20%. This may enhance worker productivity and potentially lead to annual labor cost reductions of several hundred thousand dollars (AI est.). Furthermore, optimizing AGV routes could improve transport efficiency by 15%, contributing to shorter production lead times and increased equipment utilization.
Patent Record
APPLICATION NO.
特願2021-166252
REGISTRATION NO.
7748705
FILING DATE
2021/10/08
GRANT DATE
2025/09/25
EXPIRATION DATE
2041/10/08
PATENT HOLDER
国立大学法人信州大学
Examination History
2024年07月12日
出願審査請求書
2025年05月07日
拒絶理由通知書
2025年06月25日
意見書
2025年06月25日
手続補正書（自発・内容）
2025年09月02日
特許査定