Market Context — Why This Technology, Why Now

The global push for industrial automation and smart infrastructure is accelerating, driven by rising labor costs, demographic shifts, and the need for enhanced security. Industries worldwide are seeking AI-powered solutions to improve quality control, reduce human error, and enable 24/7 monitoring. This technology directly supports these trends by offering a highly accurate, versatile motion detection system that can be integrated into existing platforms, enabling companies to meet stringent quality standards and operational demands while optimizing workforce allocation.

Key Competitive Advantages
01

Achieves superior motion detection accuracy by combining neural networks with unique filter generation technology.

02

Offers high versatility for diverse applications, integrating flexibly into various video analysis systems as a software program.

03

Demonstrates clear superiority over prior art, with patentability confirmed against five existing technologies.

Market Opportunity
🏭 Manufacturing (Quality Control & Monitoring)
$300M–$400M globally (AI est.)
This technology could enable early detection of abnormal operations on production lines and automate/enhance precision in product quality inspection, leading to reduced defect rates and improved production efficiency.
Industrial automation solution providers Quality control system integrators Factory equipment OEMs
🚨 Security & Surveillance
$150M–$250M globally (AI est.)
It could contribute to building advanced, human-independent security systems by automatically detecting suspicious intruders or abnormal behavior, and continuously monitoring critical infrastructure.
Security system integrators Smart city technology providers Critical infrastructure operators
🏃 Sports & Healthcare
$100M–$150M globally (AI est.)
This technology could support athlete performance improvement through form analysis and automate motion evaluation in rehabilitation, serving as a valuable tool for specialists.
Sports analytics software developers Medical device manufacturers Telehealth and remote monitoring platforms
IP Defensibility — Why Competitors Can't Replicate This
What This Patent Covers

This patent protects a core AI algorithm for high-precision motion segment detection, combining neural network-based feature extraction with unique filter generation and RoI Pooling. Its patentability was confirmed after successfully differentiating it from five prior art references, indicating strong, stable protection.

Competitive White Space

White space exists in integrating this core algorithm with novel sensor modalities beyond standard video, such as thermal or lidar data, or in developing predictive analytics for motion-based anomaly forecasting.

Economic Impact
~$1M/year estimated operational cost reduction per facility (est.)
estimated ROI · USD · AI analysis
ROI Calculation Logic

Automating 20% of tasks for 10 inspectors in manufacturing quality control or facility monitoring, each with an annual labor cost of ~$50K (AI est.), could yield ~$100K/year (AI est.) in labor savings. Additionally, reducing false detection rates, defects, and production line downtime could generate an estimated ~$850K/year (AI est.) in further savings.

Speed to Market
6× faster than in-house development
The core algorithm for motion segment detection is established and provided as software. This could reduce development time by approximately 2.5 years compared to in-house development. Designed for integration into existing video analysis platforms, leveraging general-purpose hardware resources for rapid deployment and market entry.
Competitive Positioning

X: Detection Accuracy & Reliability
Y: Ease of Implementation & ROI

Business Models & Applications
📝 Licensing Model
License the program to integrate high-precision motion detection capabilities into existing products or services.
☁️ SaaS Integration Model
Embed the technology into cloud-based video analysis platforms or surveillance systems, offering services via API for subscription-based revenue.
⚙️ Embedded Solution Model
Provide the technology as a dedicated embedded solution within specific industrial machinery or IoT devices, selling it as a high-value product.
Adjacent Application Opportunities
🏥 Medical & Elder Care
Patient & Elder Anomaly Detection System
In care facilities and hospitals, this system could detect fall-risk movements or insufficient posture changes from prolonged bed rest in real-time, providing alerts to staff and automated record-keeping. It could reduce monitoring workload and prevent accidents, potentially cutting incident rates by 20-30%.
🏗️ Construction & Infrastructure
Worker Safety & Hazard Detection
On construction sites and in factories, this technology could automatically detect safety violations such as unhelmeted workers, entry into hazardous zones, or improper heavy machinery operation, preventing accidents. This could reduce safety incidents by 15-25% and improve overall site safety compliance.
🛍️ Retail & Marketing
Customer Behavior Analytics for Store Optimization
In retail stores, it could analyze customer movement patterns, product interaction (e.g., picking up items), and dwell times to optimize store layouts and enhance customer experience. This data-driven approach could lead to a 5-10% increase in sales through improved merchandising and store flow.
Integration Roadmap — Estimated 12-Month Deployment
Phase 1: Requirements Definition & PoC
Duration: 2 months
Clearly define the licensee's specific challenges and goals, then validate the technology's impact using existing video data. Establish hypotheses for technical suitability and business impact.
Phase 2: System Development & Prototype Implementation
Duration: 4 months
Based on PoC results, develop and integrate the technology into the licensee's system environment. Build a small-scale prototype for testing and adjustments in a real operational setting.
Phase 3: Full Deployment & Operations Optimization
Duration: 6 months
Following prototype validation, proceed with full deployment into the production environment. Continuously optimize the technology's performance through post-deployment data collection and analysis to maximize its effectiveness.
Technical Feasibility
This technology is provided as a program, allowing for easy integration as a software update into existing video surveillance and industrial camera systems. The patent claims specify a combination of neural network-based feature extraction, filtering, and RoI Pooling, which can be implemented with minimal new dedicated hardware investment by utilizing general-purpose GPU resources and existing image processing libraries.
Success Scenario
Implementing this technology in manufacturing line inspection processes could automate complex assembly motion verification and anomaly detection previously reliant on human operators. This is estimated to reduce inspector workload by up to 30% and establish a 24/7 high-precision quality control system. Consequently, it is expected to reduce the risk of defective product outflow by 50% and improve annual production efficiency by 15%.
Patent Record
APPLICATION NO.
JP2021-184623
REGISTRATION NO.
7765252
FILING DATE
2021/11/12
GRANT DATE
2025/10/28
EXPIRATION DATE
2041/11/12
PATENT HOLDER
日本放送協会
Examination History
2024-10-03
Request for Examination
2025-06-17
Office Action
2025-07-09
Amendment (Voluntary)
2025-07-09
Applicant's Response
2025-09-30
Decision to Grant