Smart Buildings

“If You Can’t Measure It, You Can’t Improve It”: The Path to Better Buildings

“Measurement is the first step that leads to control and eventually to improvement. If you can’t measure something, you can’t understand it. If you can’t understand it, you can’t control it. If you can’t control it, you can’t improve it,” said American businessman, author, and improvement guru, Dr. H. James Harrington. Harrington has more than 65 years in management and business process improvement, including 40 years revolutionizing approaches to performance improvement for IBM. His famous quote, above, may have originated decades ago, but it has never been so relevant as it is in today’s smart buildings and cities. Measurement Smart buildings and cities are often defined as spaces filled with sensors. Data can be collected on everything and anything; from the movement of people, to the performance of systems, energy consumption, even air quality and localized weather. “In one experiment, we put about 400 sensors into a small suburban office. Every sensor, every five seconds, […]

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“Measurement is the first step that leads to control and eventually to improvement. If you can’t measure something, you can’t understand it. If you can’t understand it, you can’t control it. If you can’t control it, you can’t improve it,” said American businessman, author, and improvement guru, Dr. H. James Harrington.

Harrington has more than 65 years in management and business process improvement, including 40 years revolutionizing approaches to performance improvement for IBM. His famous quote, above, may have originated decades ago, but it has never been so relevant as it is in today’s smart buildings and cities.

Measurement

Smart buildings and cities are often defined as spaces filled with sensors. Data can be collected on everything and anything; from the movement of people, to the performance of systems, energy consumption, even air quality and localized weather.

“In one experiment, we put about 400 sensors into a small suburban office. Every sensor, every five seconds, is sending data on the temperature, occupancy and so on. That creates terabytes of data over the course of a day and that’s just one office. Think about all the offices in all the buildings in downtown LA or San Francisco”, explained Srihar Potineni, CTO of applications and data at Jones Lang LaSalle (JLL) for Commercial Smart Buildings.

This data forms the foundation of all internet of things (IoT) and smart technology, but data collection alone is not enough. Data must be transferred to other systems for analysis in order to make it useful.

Understanding

To understand something it must be analyzed. The masses of data we are collecting from sensors in smart buildings and cities is fed into big data processors for analysis. With all this data from different streams coming together in one place, we can now get an accurate and holistic picture of what is going on in our smart spaces.

“We’d really like to know what happens every second of everyday, everywhere; big data is the key to making this a reality,” said Daniel Utges, Product Director at DEXMA during Memoori’s second webinar of 2017, sponsored by Project Haystack.

Big data is crucial to the “smart” developments in cities, buildings and the grid. A Memoori report on Big Data for Smart Buildings estimated that the market for Big Data and Cloud Based Software and Services in Smart Buildings alone, will grow from $7.9 Billion in 2015 to around $32 Billion by 2020. Only by connecting smart buildings with city scale IoT and the electricity grid will create a true Smart City.

Control

Only by understanding what is going on in a building or city can we hope to control those spaces, and the more we understand about those spaces the more we can control them. The majority of IoT systems not only sense their environment and send data back for analysis. They also have the ability to follow instructions in order to enact change in that environment.

Sensors in lighting fixtures collect data on ambient light and occupancy in an office, for example, and sends it to the centralized building management system (BMS) for analysis. The BMS cross-references the data against user preferences and other criteria, and then sends back instructions to alter light levels in order to optimize conditions for the user. This scenario is mimicked across the broad spectrum of smart systems in a building, creating a complex, self-optimizing, control system.

In the majority of smart building systems active today, humans still play a hands on role in setting the ideal criteria for optimization. Increasingly however, artificial intelligence (AI) is replacing human intelligence in this regard. AI continuously processes data to learn user preferences and unearth new routes to efficiency and optimization – creating control that needs no control.

Improvement

Smart buildings and cities, like any technological innovation, are designed to improve things. A smart building may apply technology to minimize energy consumption, enhance security, support health, increase comfort or raise productivity levels.

By improving all these elements, our smart buildings can truly have a significant and positive influence on our society as a whole and, as Harrington pointed out, all that improvement starts with measurement.

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