Scaleup Enerbrain Builds on AWS to Develop Smart Building Energy Management System

Italian proptech scaleup Enerbrain decided to develop a cloud-native architecture on AWS from day one. It uses Amazon Lambda and Amazon Athena as key elements of its non-proprietary IoT energy optimization solution to handle huge volumes of sensor data generated by clients’ building management systems (BMS). Enerbrain’s key differentiator is machine learning use. It uses Amazon SageMaker to train its algorithms and provide the best strategy to reduce energy consumption and carbon emissions, as well as feed into ESG reporting—essential for data transparency across large-scale businesses. 

Climate change sits as a key priority for governments and businesses worldwide, with energy efficiency a key target in both the public and private sector. Increasingly, it is the most enlightened businesses implementing their own environmental, social, and corporate governance (ESG) measures that are leading the way.

With one of the biggest contributors to carbon emissions being from building use, Enerbrain, a scaleup based in Italy, saw a way forward to help ESG-aware businesses improve energy efficiency and meet their carbon reduction goals. Its vision was to devise a digital solution to harness the huge volumes of data generated by building management systems (BMSs) to create benchmarks to reduce energy use, improve internal comfort levels, and feed into ESG reporting. 

In 2015, while still a startup, Enerbrain wanted to ensure it could keep up with changes in technology. So it chose to use a cloud-native platform from the beginning rather than invest in on-premises IT equipment. Deploying a serverless cloud architecture meant that the company could focus on business development, rather than invest its time in managing its own data center. 

Enerbrain decided to build its system using Amazon Web Services (AWS) to benefit from the wide array of managed services and keep operational costs to a minimum. “Working with AWS would allow us to grow more quickly as a business,” says Marco Martellacci, CTO and co-founder, Enerbrain. “It’s essential for us to scale easily so we can quickly manage more buildings. Since developing our platform on AWS, we’ve been easily able to increase that number from 10 to 450 in a relatively short time.” 

It was important for the company to be able to handle and analyze large volumes of data generated by numerous devices, such as environmental sensors and actuators that Enerbrain retrofits at customer sites. It also needed to be able to create different models for different vertical markets including schools, airports, shopping malls, and offices as well as large industrial buildings. 

The company began by building its architecture on Amazon Aurora, because its ability to scale as needed was vital for the initial proof-of-concept stage, using the Enerbrain WebApp system to develop optimal energy use criteria at the start of a contract. The company is also using Amazon Athena together with Amazon Simple Storage Service (Amazon S3) for fast data analysis.

To create the Enerbrain System, the company’s overall IoT solution, it is using Amazon Lambda to provide the compute element along with Amazon SageMaker, which uses machine learning to help the company train its algorithms to deliver the best energy use strategy for each customer. Using this combination has helped its customers reduce their energy costs by up to 30 percent and has drastically cut CO2 by 9,600 tons over the buildings it manages in a single year—the equivalent of the annual carbon emissions of 1,894 passenger vehicles. 

“Machine learning is our key differentiator,” says Martellacci. “Using AWS services means we can easily learn from the data we collect from customers to provide high levels of energy efficiency as well as optimal comfort levels—down to specific areas within a given building.” 

Thanks to AWS, Enerbrain’s building and facility manager, customers can easily monitor and manage energy consumption via dashboards, allowing them to make essential day-to-day decisions. The dashboards are constantly updated using real-time data to track any kind of issue with a building’s heating, ventilation, and air conditioning (HVAC) system. 

“Our system is designed to control and regulate, so it’s important that it’s constantly monitoring an HVAC system to easily spot any red flags such as a system failure or to make quick adjustments to items like temperature on the go,” says Martellacci. “Because we can rely on AWS to guarantee uptime and availability, this has become an easy task.” 

Given the relative shortage of skilled IT staff in Italy, building on the AWS cloud means that Enerbrain does not have to increase its number of employees and can focus on ensuring its existing personnel keeps up to date with AWS services. 

“Since AWS’s cloud-based services are constantly evolving, we are able to continually enhance our models,” adds Martellacci. “The AWS team has given us amazing support every step of the way to develop and optimize our system, and they have helped us keep costs to a minimum.”

With a highly positive experience of cloud technology so far, Enerbrain plans to use AWS even more. “The cloud is the future,” concludes Martellacci. “Since we can spin up compute power when we need it, we can rapidly train neural networks over time, allowing us to provide ever smarter solutions for our customers—that’s a huge advantage.”