Smart Building Market Size, Share, Growth Analysis, By Component(Solution and Services (Consulting, Implementation and Support & Maintenance)), By Solution(Safety & Security Management (Access control system, Video surveillance system and Fire and life safety system), Energy Management (HVAC control system and Lighting management system), Building Infrastructure Management (Parking management system), By Building Type(Residential, Commercial and Industrial), By Region - Industry Forecast 2024-2031

Global Smart Buildings Market size was valued at USD 80.25 billion in 2022 and is poised to grow from USD 89.08 billion in 2023 to USD 205.3 billion by 2031, growing at a CAGR of 11% in the forecast period (2024-2031).

A complex control system manages building activities such as ventilation, air conditioning, heating, lighting, and other systems made up of sensors, actuators, and microchips in smart buildings. A smart building employs technology to simplify complex things to make it easier to maintain, more efficient, and safer. The growing trend of smart cities plays an important role in creating new chances for the smart building business. Because of advancements in digital technology, sensors, and telecommunications, buildings can now be monitored and controlled significantly more effectively than in the past. 

Smart buildings rely on a variety of IoT sensors and computer networks to automate solutions like lighting, heating, and elevator management, as well as fire detection, video surveillance, and badge access. Building Automation Systems (BAS) and these sensors collaborate to provide a wealth of informative and useful information on building safety and performance. BAS and IoT sensors, on the other hand, are vulnerable to intrusions because they usually lack essential cybersecurity skills.

Furthermore, buildings have increased chances to play a significant part in self-generation or grid-supplied energy, boosting the demand for non-carbon or low-carbon building energy management systems. Artificial Intelligence (AI) and Machine Learning (ML) may be used to analyse building data in order to improve the performance of various building activities as well as the building's income production capabilities. In today's fast-changing world driven by uncertainty, these systems can acquire the required data to translate it into meaningful information, and apply the new knowledge to the aims of companies.

According to the United States-China Economic and Security Review Commission, Chinese government investment in smart city programmes would top $38.92 billion by 2031. These developments also reflect a country's tendency to employ energy-saving technology. 

US Smart Building Market is poised to grow at a sustainable CAGR for the next forecast year.