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A Building Automation System (BAS) is like the "brain" of a building. It uses software and hardware to control and monitor various systems inside a building, such as heating, ventilation, air conditioning (HVAC), lighting, security, and increasingly more IOT systems. The goal of a BAS is to improve the comfort of occupants, increase the efficiency of a building, and reduce operational costs through automating the control of these systems. A BAS uses open or closed communication protocols. A closed BAS relies on proprietary systems where manufacturers have unique communication protocols to create a cohesive, well-integrated ecosystem. While closed protocols can simplify support when needed, they can also make integration cumbersome and often lock facility managers into a specific brand for all their automation needs.  In contrast, an open BAS uses standardized communication languages, or protocols, to allow various devices and systems within a building to interact seamlessly. This ensures interoperability among different devices and systems, regardless of the manufacturer. 

the global smart building market is expected to grow to $109.5 billion USD by 2026, thanks in large part to the increasing adoption of the latest building management system (BMS) technologies.  The commercial real estate marketplace has undergone disruptive changes due to the COVID-19 pandemic and building owners are currently looking for new ways to attract tenants. Since many corporate employees are currently working out of their homes, many building owners are seizing the opportunity to launch major renovations and modernizations to their buildings.

Buildings of the Future need next-generation Building Management Systems. To meet these challenges, buildings must become more sustainable, resilient, hyper-efficient, and people-centric. A building management system (BMS) is central

Open protocols remove the “lock-in” effect associated with specific vendors or manufacturers. This fosters a more competitive market, preventing unfair pricing and providing consumers with more service options. 

One of the biggest questions that comes up for many building owners is knowing when the time is right to invest in a building management system upgrade.

In today’s marketplace, many large and medium-size building tenants pay specialized consultants to go in and closely investigate a property before they sign a lease. They want to know the detailed history of building infrastructure improvements. They are also interested in the status of the air conditioning, ventilation, and lighting systems. The building management system is a big part of this evaluation because they know it is a key indicator of tenant comfort, indoor air quality, temperature control, and energy consumption. Buildings with antiquated building management systems quickly drop from the list of tenant building prospects under consideration.

Newer building management system systems also make a building smarter and help the building to offer features that attract a younger workforce to a more modern digital workplace. Amenities such as optical recognition for entry into spaces and lights and shades that automatically dim to save energy and optimize lighting comfort help to drive demand. An updated building management system is key to smart building operation and can help landlords maintain a higher price per square foot.

Across many buildings today, an increased risk of failure of building management systems and the mechanical and power equipment they control is simply not acceptable.

When investing in a BMS upgrade, the brand of system selected can also make a big difference as to how long that system can provide reliable service. Consider that some brands will only support their installed controllers for a few years. Component and software reliability, innovation, and longevity all play an important role in helping building owners to decide on the right time to upgrade their BMS.

The pathway to energy-efficient buildings is driven by the maturation of digital technologies such as artificial intelligence (AI), machine learning, data analytics, and visualization, all built on the backbone of connected industrial internet of things (IIoT) platform. These digital solutions are vital to acceleration building decarbonization.

While each building is unique, its core network infrastructure and communications components are primarily consistent, encompassing wired broadband, wireless broadband, and IoT connectivity.

We are in the midst of a make-or-break decade for limiting global temperature rise to 1.5°C. Scientific predictions, like the recent report from the Intergovernmental Panel on Climate Change (IPCC), dramatically illustrate what is likely to happen to humankind and our ecosystems if we do not quickly and adequately address the causes of human-driven climate change and resource depletion. These dire consequences have created unique business conditions that make energy and sustainability monitoring and reporting software an imperative. This environment is characterized by complex energy markets, emissions trading schemes, evolving government environmental regulations, growing ESG-driven investment power, and new customer demands that view progress on sustainability initiatives as a key performance metric

These three communication layers should operate in highly converged, robust, and secure intelligent architectures in smart buildings. Besides improvements on existing networks, smart buildings also need to support several IoT devices. By integrating wireless IoT data with legacy automation networks and enterprise systems, new building efficiency and sustainability levels, alongside tenants’ comfort and experience, can be achieved.

The starting point for most companies is reducing wasted energy and lowering overall energy consumption. Here machine learning can play a crucial role with real-time monitoring and advanced data analytics.

When it comes to load balancing, AI-based energy models can automatically enable onsite-generated power when grid power is most expensive, reducing energy costs. It is the first step for a microgrid that can disconnect a building from the grid for a given period, thanks to local generation. To meet aggressive climate change goals, buildings can use AI to monitor emissions continuously and optimize energy settings to reduce them.

Over the last couple of decades, BAS have seen a significant transformation. In the early days of building automation, each manufacturer had its own proprietary systems. However, this shifted in the late 1980s and early 1990s when ASHRAE (American Society of Heating, Refrigerating, and Air-Conditioning Engineers) developed BACnet, a communication protocol that allowed devices from different manufacturers to talk to each other. Despite the understandable scepticism and resistance BACnet faced from major manufacturers, its emergence really changed the game because finally there was a standardized method for exchanging information between building automation devices, opening the door for greater interoperability and flexibility. 

Around the same time, another open protocol, Modbus, was gaining traction. Developed by Modicon (now Schneider Electric) in 1979, Modbus quickly became widely adopted due to its ease of implementation and reliability. The real revolution, however, came with the introduction of the Niagara Framework by Tridium in the late 1990s. Tridium's Niagara Framework took the concept of openness a step further by creating a universal software infrastructure that could integrate diverse systems and devices. This framework supported multiple protocols, including BACnet and Modbus, making it easier for facility managers to monitor and control various building systems from a single platform. 

Another significant development at this time was the emergence of LonWorks, a protocol developed by Echelon Corporation. LonWorks was designed for networking devices over various media such as twisted pair, power lines, fiber optics, and wireless. This was just another step that made building automation systems more open and interoperable. 

In the last decade, driven by the Niagara Framework, manufacturers have started adopting truly open protocols, including APIs that facilitate data exchange. This shift was largely driven by customer demand for genuine interoperability. Many manufacturers are now recognizing the value of data and are increasingly supporting APIs and other cloud integrations to accommodate new technologies. As a result, the industry is beginning to embrace this openness.  This may take some time as many buildings still operate on legacy systems. However, we’re seeing a noticeable increase in the adoption of open protocols across the industry. Protocols like MQTT (Message Queuing Telemetry Transport) in particular are being explored for their ability to provide secure and efficient data transmission in IoT (Internet of Things) environments. This push towards open protocols has been largely driven by the demand for greater interoperability, reduced costs, and the need for future-proofing buildings.  

Energy use intensity (EUI) measures a building's energy efficiency, crucial for managing its carbon footprint. A building's major energy usage comes from HVAC systems (40-60%), lighting (20-30%), and water heating (10-15%).

Energy use intensity (EUI) is a metric that indicates how energy-efficient a building is. It's both a crucial indicator of a building’s energy performance and the key metric for determining your building’s carbon footprint and how to reduce it.

Essentially, the power grid is a complex system that delivers electricity from producers to consumers. It starts at power plants, where electricity is generated from various sources like coal, natural gas, nuclear, and – increasingly - renewables like wind and solar.

From there, electricity travels over high-voltage transmission lines, which are like the highways of the grid, carrying large amounts of power over long distances. This high-voltage electricity is then stepped down at substations to a lower voltage suitable for use in homes and businesses.

Finally, it reaches consumers through local distribution lines. Along the way, grid operators manage the flow of electricity to ensure that the supply meets demand in real-time, maintaining the balance and reliability of the grid. It’s a truly dynamic system, and it’s becoming even more complex as we integrate more renewable energy sources and adapt to new technologies. 

Renewable curtailment happens when there's more renewable energy available than the grid can use or demand at that moment. Renewable curtailment is a fascinating challenge. And it’s more common than most people think, especially in regions rich in renewables. This is where buildings can be proactive because, by shifting heating and cooling times to suit the fluctuations in renewable energy availability (otherwise known as “dynamic energy scheduling”), they can help mitigate curtailment.

The US and EU are cracking down on building emissions through new and revised building rules and regulations. ASHRAE's revised standards introduce ambitious targets for decarbonizing existing buildings.

The Energy Performance of Buildings Directive (EPBD) stands as a foundational policy in the EU’s strategy to reduce building emissions. The Directive, revised in 2023, sets out a range of measures that will help EU governments boost the energy performance of their most energy-inefficient buildings, with the goal to achieve a fully decarbonized building stock by 2050.  In a significant move by the US Department of Energy (DOE), four new appliance energy efficiency rules have recently been finalized. These rules, which impact commercial rooftop heating and cooling units, circulator pumps, and more, are projected to save almost $1.9 billion annually in utility bills across homes and businesses. 

Set to take effect starting in 2029, these regulations are expected to reduce energy consumption by about 10% compared to current products. The American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE) has recently revised its Standard 100-2024 to focus more on decarbonizing existing buildings. This update introduces new benchmarks for setting GHG targets and requires building owners to establish comprehensive energy management plans. The changes align with US city and state mandates that increasingly demand energy and emissions reductions in buildings, making ASHRAE's standards a critical component in the nation’s environmental policies.

US Green Building Council (USGBC) latest version emphasizes reducing operational emissions and improving the energy efficiency of buildings. The new rating system awards credits for efforts like electrification, peak thermal load reduction, and renewable energy use, reflecting a comprehensive approach to building decarbonization. It also emphasizes impact, alignment and interconnectedness to support initial and ongoing sustainability efforts throughout a building’s lifecycle, supported by more sustainable building operations, maintenance, design, and construction

Many buildings already use AI-driven systems to automate climate control, lighting, and energy consumption. The use of AI to streamline energy consumption is changing the facilities management game. That’s because it has the capacity to not just optimize energy use, but also significantly cut costs by dynamically adjusting to a building’s behaviour, utility data, occupancy rates, and environmental conditions. The result is a smarter, more sustainable approach to energy management that helps align with global sustainability goals. AI can turn data into predictive alerts, minimizing maintenance costs and drastically decreasing downtime. But its advantages here don’t just stop at prediction; it’s also capable of prescribing accurate and pre-emptive maintenance actions, optimizing the lifecycle of building systems before issues arise. In short, AI allows building operators to take a proactive stance on maintenance, saving both time and resources. AI systems can continuously monitor building operations, including HVAC, lighting, and energy use, adjusting these systems in real-time to optimize performance. By automating these adjustments, AI reduces the potential for human oversight or errors that can lead to inefficiencies or system failures. For instance, AI can automatically lower heating in unoccupied spaces, something that can be easily overlooked by human operators.

Alarm overload is a challenge for anyone in facilities management. The constant juggling of numerous alerts can lead to critical warnings being overlooked. The inclusion of alarms as a default feature in every Building Automation System (BAS) means that their deployment often lacks careful consideration – and an absence of strategic planning around the purpose of each alarm and whether it’s really needed could result in a whole lot of ineffective alarms. This in turn leads to overload, nuisance alarms, and alarm fatigue, making it difficult for operators to distinguish critical warnings from false positives and preventing them from prioritizing effectively. A good alarm system will ensure that alarms are relevant, unique (not duplicated), timely, prioritized, easy to understand and actionable. This underscores the critical need for adaptability and continuous reassessment. As buildings evolve and operational demands shift, the static nature of initial alarm protocols can become a liability rather than a safeguard. Recognizing this, the next step in the evolution of facility management is not merely the deployment of more alarms, but their strategic refinement and prioritization to ensure they remain relevant and actionable. This requires a nuanced approach that balances the original intentions of alarm systems with the dynamic realities of modern facility operations. artificial intelligence technology offers a promising solution. AI can rapidly sift through the immense volumes of data generated by Building Automation Systems (BAS), identifying patterns and anomalies humans might miss. What’s more, it can prioritize alarms based on severity and urgency. This approach streamlines alarm management, enabling faster responses to significant concerns and enhancing operational efficiency and decision-making. LLMs, or large language models (machine-learning tools like ChatGPT that recognize and recreate human language using deep neural networks) can take this a step further by identifying critical alarms and providing real-time contextual analysis and actionable insights. In fact, the integration of AI with LLMs is poised to revolutionize how FMs receive, respond to, and view alarms. 

At its core, a large language model is a machine-learning tool that recognizes and recreates human language using deep neural networks. Its main function is to make an educated guess as to which word will come next based on the preceding text.

As we know, traditional building management practices are full of challenges - from energy inefficiency and maintenance issues to operational bottlenecks.

Before the 19th century, building management was primarily manual, relying on clever architecture, natural resources, and manual efforts for lighting, ventilation, and heating. The invention of air conditioning in the early 20th century revolutionized building environments, finally making it possible to control indoor climates. The use of pneumatic controls marked the beginning of building automation. These systems used compressed air to control heating, ventilation, and air conditioning (HVAC) equipment. Thermostats would regulate air pressure to control dampers and valves, automating temperature and ventilation adjustments. The proliferation of electrical and electronic control systems enabled more sophisticated management of building functions. This included basic automation of heating, ventilation, and air conditioning (HVAC) systems, and the introduction of electric lighting control. The energy crisis of the 1970s spurred innovations in energy management and efficiency, leading to the development of more advanced HVAC control systems to save energy. The advent of computer technology led to the development of Building Management Systems (BMS), also known as Building Automation Systems (BAS). These systems integrated various building functions, including HVAC, lighting, and security, into a single, computer-controlled operation. The digital revolution introduced microproces