Middleware Needs Standardization to Hold Smart Buildings Together
In the physical world, hundreds of sensors are collecting data throughout every floor of smart buildings. In the digital world, building engineers and AI-power intelligence are analyzing and leveraging that data to produce actionable optimization. Bridging the gap between those two processes is proving to be one of the biggest challenges for smart buildings. The way that it is done is through a connective piece of software called middleware. In order to make sure the never-ending flow of data can get where it needs to go middleware standardization is needed.
Raw data is practically useless. Without qualifiers and context, raw data can’t be understood. To be useful, data must be sorted, arranged, meta tagged, and often presented visually. Decision-makers, whether an automated system or on-site engineer, must be able to understand the data for it to be useful. Smart buildings continue to fill with all manner of sensors, measuring occupancy, air quality, natural light, temperature, access, and more. Reading and routing the raw data coming off those sensors is the job of middleware. The better data can be routed and tagged, the better aggregation and intelligence functions at the application level. One of the things holding this important process back is that there is currently no data standardization to facilitate communication.
“There’s lots of talk about standardization in the industry, but it’s proving to be very difficult,” Daniel Russo, Chief Product Officer of Building Engines said. Russo is working to build a full-stack smart building management platform aimed at optimizing how buildings run. Doing that requires access to all sorts of data, making standardization a major challenge. One of the challenges to standardization is that currently there isn’t even an industry standard for how devices are named on a network, “how do you even name equipment in the system?” Russo said. “A lot of equipment just sends a 32 digit ID. Someone has to name it, put metadata around it. The industry is trying to normalize, to come up with naming equipment sensors, some sort of hierarchy so that when you pull data off a sensor it’s useful.”
Raw data is practically useless. Without qualifiers and context, raw data can’t be understood. To be useful, data must be sorted, arranged, meta tagged, and often presented visually. Decision-makers, whether an automated system or on-site engineer, must be able to understand the data for it to be useful. Smart buildings continue to fill with all manner of sensors, measuring occupancy, air quality, natural light, temperature, access, and more. Reading and routing the raw data coming off those sensors is the job of middleware. The better data can be routed and tagged, the better aggregation and intelligence functions at the application level. One of the things holding this important process back is that there is currently no data standardization to facilitate communication.
“There’s lots of talk about standardization in the industry, but it’s proving to be very difficult,” Daniel Russo, Chief Product Officer of Building Engines said. Russo is working to build a full-stack smart building management platform aimed at optimizing how buildings run. Doing that requires access to all sorts of data, making standardization a major challenge. One of the challenges to standardization is that currently there isn’t even an industry standard for how devices are named on a network, “how do you even name equipment in the system?” Russo said. “A lot of equipment just sends a 32 digit ID. Someone has to name it, put metadata around it. The industry is trying to normalize, to come up with naming equipment sensors, some sort of hierarchy so that when you pull data off a sensor it’s useful.”
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