Data Center Occupant-Aware Environmental Modulation Control
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Solution Overview
Problem
Data centers face challenges in maintaining optimal working conditions for individuals while balancing operational efficiency, sustainability, and regulatory compliance due to varying workload volumes affecting ambient temperature, contact temperature, and noise levels.
Innovation Solution
An automated system that identifies the location of individuals in a data center using sensors and adjusts environmental parameters such as temperature and noise levels by modifying computing device operations, including fan speeds and workload redistribution, to ensure optimal conditions are met without excessive energy use.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If data centers run warmer and at higher utilization rates to maximize output and reduce cooling costs, then energy efficiency and productivity improve, but the environmental parameters (ambient temperature, contact temperature, noise level) deteriorate negatively impacting working conditions
Solution Approach 1:
The system implements location-specific environmental monitoring and control, where sensors detect individual positions and computing devices adjust cooling and operational parameters locally rather than uniformly across the entire data center. This allows warmer operating conditions in areas without individuals while maintaining comfortable temperatures in occupied zones, resolving the contradiction between energy efficiency and working conditions.
Solution Approach 2:
The system dynamically adjusts data center operational parameters based on real-time detection of individual locations and environmental conditions. Computing devices modify their operation, fan speeds, and workload distribution dynamically rather than statically, enabling the system to maximize energy efficiency when no individuals are present while automatically adjusting to protect individual comfort when occupants are detected, thus resolving the contradiction between cooling costs and ambient temperature.
2Productivity
If data centers run warmer and at higher utilization rates to maximize output and reduce cooling costs, then energy efficiency and productivity improve, but contact temperature of components increases creating safety hazards
Solution Approach 1:
The system performs preliminary detection of individual locations using sensors before individuals can be exposed to harmful contact temperatures. When individuals are detected or predicted to be in proximity to computing devices, the system proactively adjusts operational parameters and workload distribution to prevent excessive contact temperatures, thereby maintaining high productivity while preemptively eliminating safety hazards.
Solution Approach 2:
The system continuously monitors environmental parameters including contact temperature and individual locations, using this feedback to dynamically adjust computing device operations. This closed-loop control ensures that productivity is maximized while contact temperature remains within safe limits by automatically responding to real-time conditions rather than operating at fixed high-utilization settings.
3Loss of energy
If data centers run warmer and at higher utilization rates to maximize output and reduce cooling costs, then energy efficiency and productivity improve, but noise level increases negatively impacting working conditions
Solution Approach 1:
The system implements location-specific noise control by detecting individual positions and adjusting fan speeds and operational parameters of computing devices locally rather than uniformly. This allows the data center to operate at high utilization rates with reduced cooling costs while maintaining acceptable noise levels in occupied zones through targeted adjustments rather than system-wide noise reduction.
Solution Approach 2:
The system dynamically adjusts fan speeds and operational parameters based on real-time detection of individual locations and noise level measurements. When individuals are present, the system automatically modifies operations to reduce noise while maintaining productivity, and when no individuals are detected, it can operate at higher utilization rates with minimal cooling costs, thus dynamically resolving the contradiction between energy efficiency and noise level.
4Object-affected harmful factors
If automated systems modify computing device operations to maintain optimal environmental parameters for individuals, then working conditions improve, but energy consumption increases
Solution Approach 1:
The system applies environmental modulation selectively and partially rather than excessively, adjusting computing device operations only to the extent necessary to maintain optimal environmental parameters in occupied zones. By using sensor-based location detection and targeted local adjustments rather than system-wide modifications, the system improves working conditions while minimizing the additional energy consumption required for automation.
Data Source
AI summary
Automated on-demand occupant environment modulation in a data center, including: identifying, by a computing device operatively coupled to one or more computing devices in a data center, based on data from one or more sensors, a location of an individual in the data center; and modifying, by the computing device, one or more environmental parameters at the location, including modifying operation of the one or more computing devices in the data center based on the location of the individual in the data center relative to the one or more computing devices.