This paper is a technical overview of DeepMind and Google's recent work on reinforcement learning for controlling commercial cooling systems. Building on expertise that began with cooling Google's data centers more efficiently, we recently conducted live experiments on two real-world facilities in partnership with Trane Technologies, a building management system provider. These live experiments had a variety of challenges in areas such as evaluation, learning from offline data, and constraint satisfaction. Our paper describes these challenges in the hope that awareness of them will benefit future applied RL work. We also describe the way we adapted our RL system to deal with these challenges, resulting in energy savings of approximately 9% and 13% respectively at the two live experiment sites.

Artificial intelligence is becoming increasingly significant in facility management. In particular, predictive maintenance is a significant application of AI in this domain. Predictive maintenance is the process of using data to predict when equipment will fail and needs to be repaired or replaced. This is significant because it can help prevent equipment failures, which can lead to disruptions in service. With the pressure on organizations to do more with less, Facilities Management (FM) must challenge itself to be a strategic business enabler.

Tel Aviv, Israel-based Resonai aims to build the "digital square foot" and prepare the built world for its "mixed-reality" future. The company is looking to transform physical spaces into intelligent, digitally empowered environments. After successfully growing and steering the $60 million sale of Pebbles Interfaces to Meta's Oculus in 2014, Emil Alon founded Resonai in order to develop a new OS that would converge the physical, built world with emerging digital and web technologies. "Augmented reality is going to dramatically change the world we live in and the way we experience it today," he told VentureBeat. "It will require a new paradigm of ownership, accountability and privacy in a world where everything can be reshaped seamlessly for users at any given time."

Nearly all security cameras available today have some form of video analytics on board, according to Brian Baker, vice president, Americas, for Calipsa, a leading provider of deep learning-powered video analytics for false alarm reduction. But why is this the case? And what do facilities managers need to know about it? Video analytics powered by artificial intelligence promise smarter alerts that free your security staff from responding to false alarms, says Baker, a presenter at the 2020 GSX virtual tradeshow. But to find the right AI-backed analytics for your organization, it's first important to understand the basic concepts behind the technologies.

Here's why every business owner need to repurpose their business operations with Artificial Intelligence We all keep throwing around the term that we are in the fourth industrial revolution. But not all of us know what that actually means. The World Economic Forum identifies the 4th industrial revolution by the advent of cyber-physical systems. Cyber-physical systems are business tools and practices that include both the human and artificial intelligence intervention, working collaboratively to meet a common goal in an effective manner. For a business to run effectively, it has to leverage the implementation of artificial intelligence as much as possible.

For some, the term "building automation" may seem like a relatively new concept. In reality, building automation, as a working discipline, has been around for 30 years. The early 90's saw the advent of decentralized computers to provide digital monitoring and control of various elements within a building's environment. By the turn of the century many buildings were equipped with computers/controllers that could connect to the internet. These advances provided facility managers with the means to achieve greater control over many building parameters (temperature, lighting, access, security, etc.).

Virtual reality (VR), artificial intelligence (AI), and robot technologies are evolving quickly and impacting the facilities management industry. In this article, we take a look at the ways that effective facilities management teams can adopt these cutting edge technologies. Virtual reality is quickly becoming commonplace in our society, with new enterprise and consumer applications being developed at a feverish pace. Even tech giants like Facebook, Google and Samsung have entered the VR market with their own consumer grade devices. So far, the technology has centered around immersive experiences for entertainment like video games and movies, but we're now seeing VR used in healthcare, engineering, and other non-consumer based industries.

The subject of artificial intelligence (AI) in education often centers around edtech breakthroughs and the ongoing evolution of the learning spaces inside schools. But AI is also experiencing growth in other sectors that have a direct impact on schools, presenting more areas for the education community to study. Take, for instance, construction and green energy resources. As schools look to cut costs, they are also increasing the adoption of sustainability programs. New state-of-the-art energy efficiency technologies may offer cost savings while reducing a school's carbon footprint.

The future looks bright for data-driven building operations. These solutions can save time when operating a building and deliver better outcomes for occupants. One difficulty with understanding AI in buildings is the fact that it can be applied in a variety of ways. There is a range of realistic use cases. The breadth of the technology occasionally creates confusion about what AI actually can do.

In the era of machine learning, blockchain, and the "internet of things" (IoT), Greenprint remains focused on "small data"--monthly energy, water, and waste bills normalized by building and geographic attributes such as square footage, building type, vacancy rates, and heating and cooling degree days. Using Greenprint's shared-data benchmark drawn from these simple data (and managed in the cloud on ULI Greenprint's Measurabl platform), owners can identify which buildings in their portfolio are performing better or worse than the benchmark and spot opportunities for investments in cost-effective technology upgrades, training in best practices (learning from the leaders), and tenant engagement strategies to improve performance. The benchmark also encourages healthy competition among building managers and building portfolio owners, all looking to leverage data to reduce their operating expenses and improve their net operating income (NOI). The Greenprint benchmarking tools are by no means "big data," and this is the way that Greenprint members like it. Over the past nine years, Greenprint members have leveraged these benchmarking data and shared their best practices to cut energy consumption by more than 17 percent and greenhouse gas emissions by more than 20 percent, saving $36.4 million a year in annual energy, water, and waste expenses.