The AI-driven, multi-site EMS / BMS is coming to a building near you!
Artificial Intelligence is transforming Energy and Building Management Systems. What key information do you need, and which considerations should be top of mind when you're considering this new progression in facility management?
As we know, Energy and Building Management Systems (EMS/BMS) play a central and vital role in controlling, monitoring, and optimizing multiple different functions within a building (or buildings). The EMS/BMS oversees systems including HVAC (Heating, Ventilation, and Air Conditioning), lighting, security, energy usage, signage, and others.
Building Management Systems are evolving rapidly, mainly due to new integrations with Artificial Intelligence (AI). AI is the key driver behind the current movement towards intelligent buildings that are notably efficient and better tailored to the needs of occupants.
The integration of AI for EMS/BMS has been gradual but has accelerated in the last year or so. The roots of AI in these systems go back to older rule-based automation technologies; however, it's only lately that they've started incorporating sophisticated machine learning and deep learning algorithms. Initially, EMS/BMS depended on relatively straightforward algorithms and rule sets for their operational control.
With the emergence of AI, EMS/BMS systems now have the capability to process large datasets instantaneously, identify patterns through learning, and autonomously make decisions aimed at enhancing building efficiency.
Applications of AI in EMS/BMS:
So why the shift? It’s not difficult to identify the specific areas of EMS/BMS to which AI can contribute to significant performance improvement. Here are some examples:
- When AI algorithms are used to analyze data from sensors and equipment, they can predict potential failures before they occur, leading to proactive maintenance and minimizing downtime. This equates to the benefit of predictive maintenance.
- AI can deliver enhanced or improved energy cost management by optimizing usage through analyzing occupancy patterns, weather forecasts, and historical data, then adjusting HVAC and lighting systems dynamically.
- Used to analyze occupancy data, the AI-driven EMS/BMS optimizes space allocation, improves efficiency, and reduces costs.
Of course, there are other benefits we could list. AI models can simulate airflow patterns to optimize ventilation systems in a building for better air quality while minimizing energy consumption. And AI can predict energy demand and price fluctuations, which means building can participate in demand response programs and reduce utility costs. In summary, you can quickly see the big step forward the AI-driven EMS/BMS delivers.
Benefits of AI in EMS/BMS:
From the above and other applications of AI, significant benefits can be accrued. We’ve already touched on some - upgraded energy efficiency, lowered operational costs, improved comfort, and increased security, but there’s more.
Access to data driven insights is perhaps the most important benefit. AI analytics are now becoming the key source of intelligence into building performance, harnessing data collected from a variety of sensors, systems, and other sources. Normalized and processed, this data can be used to enable more informed decision-making and continuous improvement in a building’s performance. That’s “smart”!
Additionally, the AI-powered EMS/BMS can scale to manage complex building portfolios efficiently, adapting to changing requirements and environments as geography may dictate. For the multi-site environment, this enables performance to be managed centrally, to one corporate standard when required. The “piecemeal” approach to meeting such challenges – one building at a time – is becoming a thing of the past.
Challenges and Considerations:
Inevitably, with the arrival of the AI-driven EMS/BMS comes a new set of challenges for property managers to consider. Among these are:
- AI models rely on high-quality data to make accurate predictions and decisions, so data accuracy, integrity, and availability is a vital consideration.
- Integration with existing building systems and IoT devices must be considered as interoperability challenges, requiring standardized protocols and interfaces, may sometimes arise.
- Collecting and analyzing occupant data raises issues of privacy, which means transparent policies and robust security measures will need to be put in place when AI is harnessed.
Plus, given data privacy regulations and the need to meet building codes, AI deployment in EMS/BMS isn’t as simple as counting the benefits. Careful adherence to legal requirements will also need to be considered.
Future Prospects:
Despite the challenges, the trend towards the AI-driven, multi-site EMS/BMS is now established and advances in AI Technology are likely to see its value increase in both the short and longer term. Continually improving AI algorithms, such as reinforcement learning and natural language processing, will only further increase EMS/BMS capabilities. There a few things worth keeping an eye on with this in mind.
Edge AI, a subset of the wider field of edge computing, facilitates instantaneous processing and decision-making directly on the devices, consequently reducing delays and boosting reactivity within EMS/BMS environments. Currently, AI-empowered EMS/BMS are set to merge more seamlessly with intelligent electrical grids, affording facilities the ability to engage in demand response programs, participate in energy trading, and contribute to grid stability services — opening new avenues for financial optimization.
The general direction of travel for both the AI-driven EMS/BMS and the industry in general is towards autonomous buildings. These facilities can adapt to changing conditions and optimize operations without human intervention. Collaborative ecosystems where buildings, utilities, and smart cities interact intelligently to optimize resource usage and enhance sustainability will in time likely become a feature of this landscape.
In summary, the bottom line is straightforward. It’s safe to say that AI is unlocking never before seen levels of efficiency, comfort, and sustainability in multi-site buildings management. Challenges to implementation remain but the potential benefits of AI in EMS/BMS easily outweigh them. An era of smarter more resilient buildings of the future seems inevitable.
About NexRev
At NexRev, we’ve been unlocking the power of facility and energy management data with over a million connected devices across North America. Our team of experts is focused on helping you deliver more with your budgets, infrastructure, and assets to create sustainable savings in operations and energy, reducing your risk and increasing operational confidence.
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