FogHorn's Chris Penrose
Things are looking a little different this back-to-school season than in previous years due to COVID-19. As many schools and businesses make the transition to hybrid or fully online learning and working, smart building managers and operators must also make the transition to accommodate for sudden occupancy fluctuations—varying from full classrooms and offices one day, to a completely empty campus and building the next, if an outbreak occurs.
Pre-COVID, organizations typically had a routine schedule that building-management systems are programmed to follow for lights and HVAC—for example, everything is on from 7 a.m. to 5 p.m. However, with the varying levels of occupancy on a day-to-day basis as a result of rotating office and class schedules, smart building managers are tasked with the challenge of accommodating irregular schedules and activity. These tasks include ad-hoc schedule enforcement and setting room temperatures and lighting.
Enhance your building-management system with Edge AI
Edge AI can be applied to an existing building-management system (BMS) or building-automation system (BAS) to reduce energy consumption, provide increased occupant comfort, boost safety, and better utilize building assets and services of critical systems such as elevators, fire alarms and sprinklers.
A smart edge AI-enabled BMS or BAS system can help implement real-time adjustments to schedule variations, and prime HVAC systems based on changing conditions (including building occupancy, weather and energy demands). Rather than replacing a current BMS or BAS and implementing entirely new hardware and software, edge AI can provide intelligence to sit on top of and enhance existing systems. As a result, building managers are able to amplify their BMS capabilities in a cost-effective manner.
Improving building energy efficiencies through edge AI platforms
By leveraging an edge AI platform we can collect data from a multitude of sensors and external sources, for temperature and occupancy sensors, weather forecasts, and even time-of-day energy rates. The collected data can be correlated, processed and analyzed with sophisticated machine-learning models and AI to automatically determine the optimal start/stop times, heating and cooling profiles, and lighting for each zone, room, building or campus. This approach enables smart building managers to capitalize on the most efficient use of energy while ensuring occupancy comfort.
During this process, edge AI platforms utilize real-time data to react to any changing conditions and make system adjustments immediately as they happen. This approach results in tremendous savings and improves overall system efficiencies and results in significant reductions in consumption and cost over time. Other types of devices include vibration sensors, flow meters and temperature probes to ensure optimal performance and energy usage of equipment such as the HVAC systems. Managers and operators of such smart buildings can use these insights to gain better visibility into their system functions and improve operational efficiencies across their facilities.
Learnings from smart energy in a COVID world
Building-management systems are fairly sophisticated human-centric interconnected systems and subsystems. An edge AI-enabled system facilitates an intelligent interplay of such systems that can evolve from smart buildings to smart cities, which is especially critical as our routines and “norms” continue to change on a day-to-day basis. In general, such adaptive systems enable an intelligent conservation of energy, which, in addition to the financial advantages, is good for the planet we live in.
Using an edge AI-enabled BMS, a building operator can monitor and manage the behavioral patterns of the system without having to physically go into the building and rely on the edge-AI intelligence to orchestrate the BMS functions to automate and optimize energy usage.
COVID-19 has encouraged many building managers to discover the benefits of an edge AI-powered BMS, creating more agile and efficient smart-building ecosystems. The benefits are multifold. A smart BMS can identify what the contributing factors are for one area of a building using more energy than other areas, which can help formulate appropriate remedial measures, many of which are AI-powered, all without the need for human involvement. And these learnings from one system can be applied to other building spaces to help maximize efficiency.
Chris Penrose is COO with FogHorn
