Market Context — Why This Technology, Why Now

Global industries face increasing pressure from climate change, driving demand for robust disaster resilience and business continuity solutions. Governments and regulatory bodies are mandating improved risk assessment and mitigation strategies, particularly for critical infrastructure and supply chains. This technology offers a competitive edge by enabling proactive measures against extreme rainfall, reducing potential economic losses and ensuring operational stability in a volatile climate landscape. Early adoption could position companies as leaders in sustainable risk management.

Key Competitive Advantages
01

Integrates nowcast, numerical, and observational data to predict maximum accumulated rainfall during heavy downpours with over 15% higher accuracy than conventional methods.

02

Provides near real-time predictions even under complex meteorological conditions, enabling rapid decisions for disaster prevention and business continuity plans.

03

Specializes in heavy rainfall caused by multiple cumulonimbus clouds, enabling localized risk assessment previously difficult with conventional wide-area forecasts.

Market Opportunity
Disaster Preparedness & Mitigation
$300M–$400M (AI est.)
Heavy rainfall damage is intensifying, making high-precision precipitation forecasting essential for optimizing evacuation orders and infrastructure protection.
Government agencies for disaster management Emergency services providers Urban planning and resilience consultants
Infrastructure Management
$500M–$600M (AI est.)
There is a growing need to detect disaster risks in advance and respond early for the maintenance and management of roads, railways, rivers, and power grids.
Public utility companies (power, water, telecom) Transportation authorities (rail, road) Civil engineering and construction firms
Agriculture & Fisheries
$150M–$250M (AI est.)
These weather-dependent industries require accurate precipitation forecasts for crop management, harvest planning, and improving safety in fishing operations.
Agribusiness technology providers Large-scale farming operations Aquaculture and fisheries management companies
Logistics & Supply Chain
$200M–$300M (AI est.)
High-precision weather forecasts are needed to mitigate transport delays and supply chain disruption risks caused by adverse weather.
Global logistics and shipping companies Supply chain software providers Major manufacturing and retail corporations
IP Defensibility — Why Competitors Can't Replicate This
What This Patent Covers

This patent protects a precipitation prediction device and method, specifically detailing the integration of nowcast, numerical, and observational data through unique filtering and synthesis. The claims clearly define the system's components and their interaction for high-precision forecasting, having successfully overcome examiner objections to establish a robust and clearly defined scope of protection.

Competitive White Space

This patent primarily covers the core prediction algorithm and system architecture. White space exists in developing specific hardware integrations, advanced visualization tools for diverse end-users, or integrating this prediction into broader climate risk modeling platforms.

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

Assuming an average annual economic loss of ~$350M (AI est.) from heavy rainfall, this technology could mitigate 3% of that, or ~$1.0M (AI est.) annually. This includes reducing infrastructure damage, supply chain disruptions, and agricultural losses, thereby enhancing business continuity.

Speed to Market
4× faster than in-house development
This technology's fundamental research and algorithms have been established by a national research institute and have received patent approval, indicating that the technical demonstration phase is complete. This could shorten development time by approximately 3 years compared to developing a similar prediction system from scratch, enabling faster market entry and service integration. Integration with existing meteorological data acquisition systems is also estimated to be relatively straightforward.
Competitive Positioning

X: Prediction Accuracy (Heavy Rainfall Response)
Y: Contribution to Early Decision-Making

Business Models & Applications
☁️ Prediction Data Provision Service
A subscription-based model could provide high-precision accumulated rainfall prediction data generated by this technology to local governments and businesses via API integration.
🚨 Disaster Risk Management Solution
An integrated solution could leverage prediction data for specific regional disaster risk assessment, evacuation planning support, and linkage with infrastructure monitoring systems.
🌾 Agricultural Digital Transformation Support
This service could integrate with soil moisture sensors and irrigation systems on farmlands to automate optimal water management and crop protection based on precipitation forecasts.
Adjacent Application Opportunities
🚧 Construction & Civil Engineering
Construction Site Disaster Risk Prediction System
For large-scale civil engineering sites and high-altitude work, this technology could provide high-precision advance prediction of landslide and lightning risks from heavy rainfall. This has the potential to optimize work schedules and enhance worker safety, potentially reducing weather-related project delays by 10-15%.
🚢 Maritime Transport & Port Management
Vessel Route & Port Hazard Avoidance Support
This technology could predict localized severe weather or heavy rainfall for vessel route selection and port cargo handling operations. It has the potential to support safer operational planning and decisions to suspend work, potentially reducing weather-related shipping delays by 5-10%.
⚡️ Energy Infrastructure
Renewable Energy Plant Operations Optimization
For solar and hydroelectric power plants, this technology could forecast precipitation to anticipate fluctuations in power generation and disaster risks. This has the potential to contribute to stable power supply planning, potentially improving grid stability by 5% during extreme weather events.
Integration Roadmap — Estimated 12-Month Deployment
Requirements Definition & Data Linkage Validation
Duration: 3 months
Define requirements for integration with existing meteorological observation data and infrastructure management systems, and validate the compatibility of data acquisition and processing interfaces.
System Development & Prediction Model Tuning
Duration: 6 months
Integrate the technology's algorithms into existing platforms, and perform parameter tuning and accuracy validation for prediction models tailored to specific target regions and applications.
Pilot Operation & Impact Measurement
Duration: 3 months
Initiate pilot operation of the system in a limited environment, measure prediction accuracy and economic impact, and make final adjustments based on feedback.
Technical Feasibility
This technology is designed to utilize existing meteorological observation data and numerical prediction model outputs, eliminating the need for new large-scale sensor networks or observation equipment. The claimed nowcast prediction unit, numerical prediction unit, filter application unit, and synthesis unit can be implemented as software data processing modules, making integration into existing cloud infrastructure or on-premise environments relatively straightforward.
Success Scenario
Implementing this technology could potentially reduce the risk of infrastructure damage from heavy rainfall, previously difficult to predict, by approximately 20%. This could enable companies to take proactive measures earlier, mitigating losses from business interruptions by ~$50K–$100K annually (AI est.). Additionally, local governments could improve the accuracy of evacuation orders, thereby more reliably ensuring resident safety.
Patent Record
APPLICATION NO.
特願2020-052014
REGISTRATION NO.
7286165
FILING DATE
2020/03/24
GRANT DATE
2023/05/26
EXPIRATION DATE
2040/03/24
PATENT HOLDER
国立研究開発法人防災科学技術研究所
Examination History
2022年06月14日
出願審査請求書
2023年03月29日
拒絶理由通知書
2023年04月07日
手続補正書（自発・内容）
2023年04月07日
意見書
2023年05月10日
特許査定