Skip to main content

Monitoring Building and HVAC Infrastructure

Keith Bromley

Monitoring of heating, ventilation and air conditioning (HVAC) infrastructures has become a key concern over the last several years. Modern versions of these systems need continual monitoring to stay energy efficient and deliver satisfactory comfort to building occupants. This is because there are a large number of environmental sensors and motorized control systems within HVAC systems. Proper monitoring helps maintain a consistent temperature to reduce energy and maintenance costs for this type of infrastructure.

By deploying Ethernet-based taps, building personnel and network managers have easy access to data from HVAC systems. After taps are installed, a network packet broker (NPB) is used to aggregate data from the various taps. The NPB will capture, filter, and regenerate specific pieces of data as needed and forward that data on to individual application performance monitoring (APM) tools that can be used to examine the data.

The NPB also provides the internal ability to load balance data to multiple APM tools. This allows IT personnel the ability to deploy n+1 survivability. The traffic load is divided up evenly across the number of allocated tools. Should one or more of the tools fail, the data is still split evenly across the remaining number of tools. If the number of tools is dimensioned correctly, there will be no loss of data.

The solution ends up looking like the following:


The monitoring solution described here provides the following benefits:

■ Reuse of the existing Ethernet infrastructure

■ 24 x 7 remote access to the HVAC data and system controls

■ Cost reduction due to faster alerting of system problems

■ Deployment of n+1 survivability for HVAC monitoring tools

Hot Topics

The Latest

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

Monitoring Building and HVAC Infrastructure

Keith Bromley

Monitoring of heating, ventilation and air conditioning (HVAC) infrastructures has become a key concern over the last several years. Modern versions of these systems need continual monitoring to stay energy efficient and deliver satisfactory comfort to building occupants. This is because there are a large number of environmental sensors and motorized control systems within HVAC systems. Proper monitoring helps maintain a consistent temperature to reduce energy and maintenance costs for this type of infrastructure.

By deploying Ethernet-based taps, building personnel and network managers have easy access to data from HVAC systems. After taps are installed, a network packet broker (NPB) is used to aggregate data from the various taps. The NPB will capture, filter, and regenerate specific pieces of data as needed and forward that data on to individual application performance monitoring (APM) tools that can be used to examine the data.

The NPB also provides the internal ability to load balance data to multiple APM tools. This allows IT personnel the ability to deploy n+1 survivability. The traffic load is divided up evenly across the number of allocated tools. Should one or more of the tools fail, the data is still split evenly across the remaining number of tools. If the number of tools is dimensioned correctly, there will be no loss of data.

The solution ends up looking like the following:


The monitoring solution described here provides the following benefits:

■ Reuse of the existing Ethernet infrastructure

■ 24 x 7 remote access to the HVAC data and system controls

■ Cost reduction due to faster alerting of system problems

■ Deployment of n+1 survivability for HVAC monitoring tools

Hot Topics

The Latest

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...