MUMBAI, India, May 1 -- Intellectual Property India has published a patent application (202641051708 A) filed by Kotcherla Murali Krishna, Nellore, Andhra Pradesh, on April 23, for 'system and method for environment-aware autonomous orchestration of data center workloads and infrastructure.'

Inventor(s) include Kotcherla Murali Krishna.

The application for the patent was published on May 1, under issue no. 18/2026.

According to the abstract released by the Intellectual Property India: "The present invention discloses a system and method for environment-aware autonomous orchestration of data center workloads and thermal infrastructure, with particular applicability to multi-region cloud providers requiring data sovereignty compliance. The system integrates a multi-horizon forecasting engine with confidence intervals and disaster prediction, a dynamic risk scoring module with adaptive model optimization, a thermal-weather coupling analyzer using physics-based or data-driven thermal modeling, and a preemptive workload migration controller that generates hardware-level control signals to industrial control systems and hypervisors. A confidence-aware scheduling engine modulates migration aggressiveness based on forecast uncertainty, while a model-based temporal risk propagation module uses a time-weighted aggregation model as part of model-based temporal risk propagation across future time windows. Gradient-limited thermal actuation via industrial protocols prevents mechanical stress. The closed-loop control architecture, executing continuous feedback-driven actuation loops across thermal and compute infrastructure, produces quantifiable technical effects through hardware-integrated actuation, including reduced cooling energy consumption, fewer thermal excursions, and lower inlet temperature variance, resulting in reduced control latency and improved actuation stability. An operator interface enables human-in-the-loop policy adjustment with explainability outputs and command feedback, while data sovereignty-aware geographical redistribution balances workload placement across regions via hardware-encrypted sovereignty table lookup, and carbon-aware scheduling aligns compute distribution with grid conditions without compromising thermal stability."

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