This case study accurately illustrates the possible practical benefits of machine learning for HVAC operation. Thanks to ET, a significant potential for energy savings was found and fully exploited during subsequent modifications of the building management system resulting in successful savings in energy consumption and building operation costs.
This case study is a good example of how AI can improve our work. In this case, AI does not replace an expert; it just makes their work more efficient. AI performs the repetitive and dull part of the job – such as comparing all measured data and detecting anomalies. The expert then spends precious time only with the events that matter and are worth investigating.
During the pandemic, buildings were exposed to nonstandard regimes (reduced number of occupants, nonstop ventilation, total lockdown, etc.). Valuable data
were measured by Building Management Systems.
Analysis of these data provide valuable knowledge about the effectiveness of setback regimes.
This case study demonstrates the potential of energy-saving measures to achieve significant cost savings and reduction of energy consumption, even in challenging market environments. Immediate impact evaluation tools, such as Energy Twin Interactive and SkySpark, can enhance the efficiency of implementing such measures. These tools provide prompt feedback for fine-tuning and adjusting measures, while automating mundane tasks, thus reducing the workload of energy experts.
Introduction Every journey into AI begins with a crucial first step: understanding your data. Many clients approach us eager to jump straight into machine learning
This tutorial is focused on visualization of a model in the app ET Views once it has been identified.
This tutorial is focused on visualization of a model in the app ET Views once it has been identified.
This tutorial is focused on visualization of a model in the app ET Views once it has been identified.
This video demonstrates how to identify a model in the ET Admin app using Energy Twin Analytics.
In the fast-paced environment of fast food restaurants, maintaining the right temperature in freezers and coolers is critical. Any deviation from the optimal temperature range
