MUMBAI, India, Sept. 28 -- Intellectual Property India has published a patent application (202641111012 A) filed by Dr B Nagaraj; Shahithya B; Banu Priya C K; Dharsika B K; Deepika R; and Pooja Sri S on September 16, 2026, for System And Harware Architecture For Trust-Impact-Based Execution Control In Data-Driven Decision Systems.
Inventors include Shahithya B; Banu Priya C K; Dharsika B K; Deepika R; and Pooja Sri S.
The application for the patent was published on September 25, 2026, under issue no. 39/2026.
Abstract: The present invention relates to a system and hardware architecture for trust–impact based execution control in data-driven decision-making environments. The system is designed to evaluate incoming data and regulate automated actions by computing a composite trust score using multiple parameters including source reliability, data consistency, freshness, anomaly detection, and historical accuracy. In parallel, the system determines a decision impact level based on the criticality, risk, and potential consequences of the intended operation. The computed trust score and decision impact level are integrated through a trust–impact fusion mechanism, which dynamically determines whether a decision should be executed, blocked, or escalated for review. This adaptive decision logic ensures that only sufficiently reliable and context-appropriate data triggers system execution. A dedicated hardware component, referred to as the Data Trust Processing Unit (DTPU), is implemented to enable real-time enforcement of trust-based control. The DTPU comprises parallel trust evaluation circuits, an impact assessment unit, a threshold comparator module, execution gating logic, and a memory unit for storing historical decision outcomes. This hardware-level architecture ensures low-latency processing, reduced computational overhead, and enhanced system efficiency compared to conventional software-only approaches. The system further incorporates an adaptive feedback learning mechanism that continuously updates trust weights and threshold parameters based on prior execution outcomes, enabling progressive improvement in decision accuracy and reliability. Overall, the invention enhances safety, robustness, and efficiency in automated and autonomous systems by ensuring that only trustworthy and context-validated data is permitted to influence critical system decisions across various application domain.
Disclaimer: Curated by HT Syndication.
