The demand for artificial intelligence (AI) continues to surge, and concerns about the environmental impact of data centers are escalating. Of particular concern is their substantial energy and water usage. Indeed, ensuring the sustainability of data centers, which house the advanced data processing technology essential for AI operations, is receiving unprecedented attention.
After calibrating over 100,000+ sensors in live data centers, Standard Calibrations, Inc. (SCI) issued a white paper with alarming audit findings: One in four sensors monitoring essential functions such as heating, cooling, humidity control, and other operations were found to be inaccurate. Furthermore, installation deficiencies were identified in new data centers more than 15% of the time. SCI attributes these inaccuracies to various root causes, including evolving technology demands and oversights in sensor design, selection, and installation.
Standard Calibrations, Inc. (SCI) of Chesapeake, VA warns that overlooking sensor inaccuracy can lead to costly downtime and operational inefficiencies for data centers. (Photo courtesy of SCI)
“The potential financial repercussions of inaccurate building sensors can be severe,” said SCI President Mike Meyer. “In a recent case, a global SCI customer had initiated a $3M project to upgrade critical supply fans believed to be underperforming based on inaccurate sensor data. If we had not intervened by verifying sensor installation and setup during our preliminary health checks and then recalibrating out-of-tolerance sensors, the customer would have proceeded with this unnecessary multi-million dollar upgrade. For data center owners and operators, this reality begs the question: Can I truly trust the integrity of my building sensor data?”
Meyer emphasizes that accurate sensors alone will not guarantee precise measurements of heat, humidity, cooling capacity, and other essential building measurements: “Ensuring sensor accuracy within the building after installation and at regular intervals is vital to maintaining system performance and preventing unplanned and unnecessary risk and costs.”
Artificial intelligence will either add to the burden on an already-strained electrical grid or it can help pave the way to a secure energy future, says ACEEE. Read more…
Safeguarding Data Center Performance
Accurate building sensor data is the cornerstone of maintaining system performance and achieving sustainability targets for data center owners and operators. However, drifting, inaccurate, or failing sensors can have severe consequences. Underperforming HVAC systems, increased energy consumption, and unnecessary equipment wear can significantly impact risk and cost.
Ensuring the accuracy and reliability of building sensors is a strategic imperative for business executives seeking to safeguard data center investments and maintain a competitive edge. With that in mind, SCI has launched SensorProQ™, a no-cost sensor health check service for building management systems (BMS). The health check is performed onsite at data centers to uncover potential sensor and monitoring issues affecting building system performance. It provides actionable recommendations to address identified problems proactively.
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Artificial intelligence will either add to the burden on an already-strained electrical grid or it can help pave the way to a secure energy future, says ACEEE. Read more…
