Globally, aging infrastructure necessitates cost-effective, continuous monitoring to prevent failures and ensure public safety. Environmental regulations are tightening worldwide, demanding broader and more precise surveillance of pollutants and natural resources. Furthermore, the push for Industry 4.0 and smart cities emphasizes optimized sensor networks for data-driven decision-making. This technology offers a critical solution to meet these evolving demands by maximizing monitoring efficiency with fewer resources and lower operational expenses.
Dramatically reduces required sensor count by optimizing observation points compared to conventional random or comprehensive placements.
Maximizes inverse estimation success rate to reliably identify targets with fewer observation points, achieving high-precision monitoring efficiently.
Offers high technical originality with few prior art references, indicating strong competitive advantage and broad applicability beyond the nuclear sector.
This patent protects a broad scope covering observation point determination devices, methods, and programs, with 7 claims. Its strong technical originality is evidenced by few cited prior art documents, providing a robust and stable foundation for licensees to build upon.
This patent focuses on optimal observation point determination. Licensees could develop complementary IP in advanced sensor hardware, real-time data transmission protocols, or AI-driven predictive analytics for the collected data.
Optimizing observation points could reduce equipment-related costs (sensor procurement, installation, maintenance) by 10%–20% annually. Additionally, labor savings from streamlined observation tasks could cut annual personnel costs by 10%–15%, leading to a total annual cost reduction of 20%–30%. For example, a facility with $650K (AI est.) in annual observation-related expenses could see savings of $150K–$200K (AI est.) per year.
X: Cost Efficiency
Y: Data Reliability