Leveraging Advanced Analytics to Improve Thermal Comfort and Energy Consumption
Today, there is a lot of talk in the commercial building industry about advanced analytics. As new...
When it comes to utilizing big data for optimizing energy consumption in commercial buildings, property owners and service contractors often find it challenging to commit to a framework or platform. Whether due to a lack of knowledge of complex machine learning algorithms or the difficulty understanding the capabilities of a particular building data analytics platform, it can be hard to see the potential benefits of one platform over another and how those benefits affect return on investment (ROI). To better understand the potential of building analytics platforms without getting bogged down in technical jargon, we take a closer look at two analytics systems: Niagara Analytics and onPoint.
Niagara Analytics and onPoint are analytics platforms with unique advantages for building owners and facilities managers. Both platforms are designed for monitoring, management, and maintenance of building systems. However, there are substantial differences between the two and it helps to know what you’re looking for. A good place to start is by examining the benefits and costs of each.
Optimal energy management is only possible when you monitor energy usage and associated costs at the building, component, and system levels. Though the Niagara Analytics platform provides aggregated information about different interconnected systems to better support facility management, onPoint offers the ability to objectively track facilities based on comfort, cost, and compliance through comprehensive reports. These reports can include customized formulas that track energy usage intensity, energy cost intensity, and other parameters.
Without robust fault detection and diagnostic capabilities, false/nuisance alarms can be major problems. In an interconnected network of building equipment, if one equipment malfunctions, multiple alarms from other related units can be triggered. In basic alarm consoles, those faults may render as only small blips, and the fact that multiple alarms are related to the malfunctioning of one piece of equipment will likely not be recognized at all. onPoint communicates multiple, related alarms in a way that projects their severity to the end user instead of just throwing another issue on the board for someone to track down blindly.
The Niagara Analytics framework cannot combine several similar faults or equipment into one alert, leaving it unable to relieve the strain of alarm fatigue on building operators. . The inability to consolidate multiple alerts also greatly impairs the troubleshooting process and delays the solution, sometimes indefinitely.
In comparison, onPoint Analytics has a set of point-level fault detection rules to ensure the integrity of data gathered from a network. These analytic rules include minimum duration requirements, which means a small blip in data does not create an unintended insight. Active suppression avoids cascading alarms, which is particularly helpful when multiple pieces of equipment are connected (e.g. an air handler unit (AHU) and its associated variable air volume (VAV) systems).
onPoint’s sophisticated algorithms result in more accurate recommendations for corrective actions. Additionally, detailed insights related to particular equipment are displayed on custom dashboards that give stakeholders the information they need to make thoughtful decisions.
Due to the specialized programming knowledge required to work with the Niagara Analytics platform, it is not easy to install and use. In contrast, onPoint requires no programming. It is built to deploy with little effort and can show results in as little as one week. The user interface comes standard with configurable dashboards, KPI widgets and a navigation structure that is intuitive.
Since there has been little adoption of the specialized programming required for Niagara Analytics, it is often difficult to find a programmer or integrator with the experience necessary to write rules and set up a Niagara Analytics system. The onPoint system is built on SkySpark and is therefore open to additional configurations should clients have programmers on staff. The open SkySpark back-end also makes it possible for clients to retain ownership of their data and take advantage of the extensive network of service providers should they want additional support.
Breaking down the cost structure of building analytics platforms is one of the most critical yet complicated steps of choosing the right service. After all, this is key to understanding the ROI potential of each platform and when your organization may start to really realize energy savings.
The cost structure of these platforms typically includes a license fee, SaaS fee, equipment fee, and setup fee. The deployment cost, calculated annually, is usually dependent on the size of your building as a proxy for how much equipment it will likely have, and the customized features you want to include in the package.
Typical software licenses in the building automation industry are based on points. For most, this is a nebulous term that makes it difficult to estimate costs, which as explained above, is a crucial factor in the decision-making process. Broadly, a point is a metric that identifies something a user wants data about. The Niagara Analytics pricing model follows the Niagara Framework pricing structure in that it’s based on points and can be purchased in packs ranging from 10 to 50,000. The per-point price goes down the larger the point package.
onPoint, on the other hand, is priced per square foot, a much more familiar concept to the buildings and commercial real estate industry. By using square footage, it is easier to conceptualize the total cost of a potential project and discuss ROI strategies with team members throughout the procurement process.
Compared to onPoint, the Niagara Analytics pricing model can be difficult to calculate and will often increase very quickly.
Understanding these benefits and costs is critical to selecting the platform that can optimize operations, reduce energy usage, and offer significant return on investment.
For those with existing Niagara systems, it may seem like a straightforward choice to add Niagara Analytics. Your Niagara system is already generating alarms, so why not just apply an analytic rule set to those alarms and be on your way?
Turns out, it’s not an either/or choice. onPoint integrates directly with Niagara, which means it collects and organizes Niagara Alarms as well as SkySpark Sparks. Unlike Niagara Analytics, the onPoint rule library can be applied to Niagara Alarms without any programming on your part. The ease with which onPoint can be deployed means you’re taking advantage of machine learning algorithms and tailored rule sets after completing a single page onboarding document.
Whether you’re a service contractor with lots of different Niagara buildings, or you’re a building operator with just one Niagara system, onPoint is made to make your building management life easier. From truly helpful troubleshooting messaging to automated monthly reports and continuous platform updates,
onPoint can transform your building management and open up new opportunities for improved efficiency and greater occupant comfort.
Jon Schoenfeld, PE is Buildings IOT's Director of Energy & Analytics. He's been developing advanced algorithms for building automation applications for more than a decade and he applies his tremendous building expertise as he oversees the team of building scientists creating the onPoint platform.