Use of Artificial Intelligence in Building Optimization Growing, Reports Frost & Sullivan
A new report from market research and consulting firm Frost & Sullivan shows that home and building technology companies are increasingly utilizing artificial intelligence and machine learning algorithms to stay ahead of competition. The technologies used are expected to assist with building optimization, which is a key differentiator between companies, according to the report.
“Vertically-integrated building automation solutions, edge intelligence in commercial building automation applications and energy disaggregation in commercial buildings will be distinct features in building management in 2019,” said Anirudh Bhaskaran, senior industry analyst at Frost & Sullivan. “Leading building automation participants will be looking to integrate cognitive abilities in buildings by way of partnerships with technology companies. Analyzing huge volumes of data is critical for cognitive buildings.”
The report, Global Homes and Buildings Industry Outlook 2019, details opportunities and key markets for the systems of lighting, energy management, automation, facility management, smart homes, fire safety and security. It also examines technologies that are changing the market as well as companies to watch in 2019.
The $1.2 billion home and building technology industry is expected to reach $1.3 billion in 2019, according to the report.
“To make homes truly connected and energy efficient, home and building companies need to establish partnerships with utilities, energy consultants, and retailers,” said Bhaskaran. “Meanwhile, Software-as-a-Solution (SaaS) developers need to develop a vendor-agnostic software platform to make solutions compatible with third-party hardware.”
Other highlighted growth opportunities for home and building technology companies include:
• Incorporating machine learning algorithms to provide personalized services to building occupants.
• Leveraging data generated in properties to provide insights with nearly zero human intervention.
• Developing products that control multiple building services, mainly HVAC and lighting, to reduce capital expenditure for building managers.
• Building a centralized data repository in the cloud for customers to access energy consumption data for independent data analytical applications.
• Adopting flexible business models that cover both hardware and software.
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