In a previous post, I wrote about how the Edge and edge devices are contributing to a significant shift in the way we are acquiring information, interacting with it, and making decisions.
Continuing this theme, this evolution has been enabled, in large part, by rapid advances in lower-cost controllers, open source software, powerful processors -and the world of IoT. This combination is also changing our BAS landscape to support a decentralized architecture where analytic processing can be done at the edge. This evolution is also changing the execution of analytics and machine learning's location.
With more devices functioning at the edge comes more data that has the potential to provide enhanced insights into how we manage and operate facilities. At the same time, it also presents a new challenge for how to analyze it all. Collecting and compiling this data benefits no one unless there is a way to understand it all. Making sense of huge amounts of data is a perfect application for learned actions and AI.
By applying analytics with AI to data at the edge, we can identify and understand patterns, make more informed decisions and initiate action. This leads to a variety of benefits for building operators and system integrators such as proactive intervention, intelligent automation and highly personalized experiences. It also enables us to find ways for these devices to work better together, make building automation systems easier to use, extend the lifetime value of the equipment within these systems and deliver a more personalized environment for occupants.
Analytics and AI can enable autonomous improvements to operations within a facility — including heating, cooling and lighting. For example, we can identify and automatically act upon usage patterns in a building space such as recognizing specific patterns ranging from people in the room, room temperatures to controlling lights on and off when someone enters or leaves.
Integrating analytics and machine learning at the edge level is beginning to become a prerequisite for today’s IoT-enabled buildings. Although we are in the very early stages of AI when it comes to the edge, it is beginning to gain traction. James McHale, Managing Director at Memoori said it best, “ It has long been clear that AI technology represents the future in building automation and beyond, but in the present, building performance software is helping humans improve automation while also nurturing its eventual successor – AI”.