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  6. Cloud-based Noise Level Measurement System for Data Centers

Cloud-based Noise Level Measurement System for Data Centers

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M2MSTREAM

last updated:Mar 04, 2026

グリッドリンク IoTプラットフォーム事業部
グリッドリンク IoTプラットフォーム事業部
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Visualizing the noise around data centers to enhance environmental consideration and resident engagement.

In data centers, many facilities such as air conditioning systems, cooling units, and emergency generators operate 24 hours a day. The noise generated by these facilities can affect not only the operational environment within the facility but also the surrounding environment. To balance stable facility operations with consideration for the local environment, it is important to continuously monitor and appropriately manage noise levels. Additionally, changes in noise levels can indicate abnormalities or deterioration in equipment, and utilizing this as part of operational monitoring can help in the early detection of equipment issues and preventive maintenance. The cloud-based noise monitoring system measures noise levels in real-time using sound level meters installed both inside and outside the data center, managing the data centrally in the cloud. It allows for remote monitoring and historical data review, enabling operators to immediately grasp the overall noise situation of the facility. Furthermore, it automatically sends alert notifications when set thresholds are exceeded, supporting prompt responses. By analyzing the accumulated data, it also contributes to the optimization of equipment operations and the enhancement of environmental management. As a monitoring foundation that supports the stable operation of data centers and environmental considerations, it aids in improving the reliability of facility operations.

    Data LoggerNoise Inspection
P_騒音レベル計測.png

Cloud-based Noise Level Measurement System for Data Centers

P_騒音レベル計測.png
P_騒音レベル計測.png
  • Special site - Product/service details - https://pr.mono.ipros.com/m2mstream/product/

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basic information

【Features】 - Real-time monitoring of noise levels from remote locations - Detailed data measurement including maximum, minimum, and equivalent noise levels - Automatic calculation of time-weighted noise levels (LA95, LA50, LA05) - Notifications via email or alarm system when thresholds are exceeded - Graphical data representation and download in CSV file format

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Applications/Examples of results

【Usage Scenarios】 - Noise monitoring within data center facilities - Environmental monitoring in server rooms and rack areas - Monitoring of air conditioning and cooling equipment areas - Noise monitoring during the operation of emergency generator equipment - Environmental noise monitoring around the facility perimeter 【Benefits of Implementation】 - Understanding operational conditions through real-time visualization of noise levels - Strengthening preventive maintenance through early detection of equipment anomalies and unusual sounds - Rapid response through alert notifications when thresholds are exceeded - Optimization of equipment operation through recording and analysis of noise data - Consideration for the surrounding environment and strengthening of environmental management systems

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Cloud-based Noise and Vibration Level Measurement System for On-site Environment IoT

Cloud-based Noise and Vibration Level Measurement System for On-site Environment IoT

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グリッドリンク

グリッドリンク IoTプラットフォーム事業部

IT/Telecommunications

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We provide the IoT/AI network infrastructure "M2MSTREAM," which seamlessly integrates sensing technology, artificial intelligence (AI), communication technology, information technology, and application technology, all of which are essential for realizing a highly automated, unmanned, and remote society. "M2MSTREAM" connects edge devices and the cloud seamlessly, enabling high-speed automated processing through real-time data collection and analysis. It has standard IoT functions necessary for collecting real-world data and remote operation of devices, allowing for the rapid construction of IoT/AI systems by customizing and adding AI functions. We contribute to the realization of a highly automated, unmanned, and remote society through "M2MSTREAM."

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