The use of artificial intelligence (AI) is increasingly helping buildings to become more environmentally friendly. In 2022, buildings were responsible for approximately 26% of global energy-related greenhouse-gas emissions, according to the International Energy Agency. To achieve net-zero emissions by 2050, the agency advises that energy consumption per square meter needs to decrease by around 35% by 2030.
Over the past few decades, developers and construction companies have sought to enhance energy efficiency in buildings. LEED certifications, which recognize standards for energy, water, waste, and other environmental goals, are granted to buildings meeting these criteria. Furthermore, governments are implementing stricter energy codes for commercial spaces.
Despite these efforts, more than 80% of buildings still lack smart systems for effective energy management. JLL, a company responsible for managing vast commercial real estate properties worldwide, has been investing in AI systems to help businesses reduce their emissions. The reasoning behind this investment is that eco-friendly buildings can command higher rents and spend less time on the market.
Ramya Ravichandar, JLL Technologies’ vice president of technology platforms—smart and sustainable buildings, states a clear goal: to maximize the intelligence of all buildings. However, without adequate measurement of important data, meaningful changes cannot be made.
JLL’s investments include Turntide, a company that installs electric motors with small computers to learn from patterns and precisely control heating and cooling, and Envio Systems, a Berlin-based company that develops sensors to monitor a building’s usage, occupancy, and other factors for optimized energy-related activities.
The goal is to determine if lights need to be kept on or if air conditioning on certain floors can be turned off when the entire workforce is working from home. With relentless data processing, such a system provides crucial insights.
AI building systems typically analyze historical patterns and occupants’ daily habits to predict and manage power usage. Implementing software and hardware solutions that automate lighting, heating, and cooling can result in buildings reducing their yearly energy use by 20% or more. However, several challenges remain when it comes to installing AI systems, including the gathering of data from various sources in buildings, particularly sensors that often lack interconnectedness. Retrofitting existing buildings with such sensors and infrastructure can be resource-intensive and requires the assurance of consistent data quality.
Although AI has the potential to significantly reduce building emissions, its effectiveness relies heavily on the quality of data it learns from. Only 10% to 15% of buildings currently possess the necessary equipment or systems to gather the required data for supporting AI applications, according to Thomas Kiessling, chief technology officer of Siemens Smart Infrastructure. Without accurate data, scheduling, rule-setting, and more advanced use cases related to AI cannot be achieved. Therefore, data is a critical component for AI in buildings.
Siemens leverages AI by comparing a single building to a thousand similar ones to predict potential energy savings through the implementation of a smart-energy management system. Even with minimal information such as the building’s address, energy bill, and basic HVAC brand details, it is now possible to compile a building profile and estimate potential benefits. For companies lacking a sophisticated management system, lower-cost sensors for lighting and cooling can still contribute to energy conservation.
Fifth Wall, a venture-capital firm, dedicates a $500 million fund to decarbonizing buildings and allocates roughly one-third of its investments to startups offering AI solutions in both software and hardware. Additionally, the firm emphasizes the importance of using sustainable materials like concrete and steel produced with renewable energy sources.
AI can provide valuable assistance by quickly and cost-effectively identifying economically feasible building upgrades, navigating country-specific permits, generating design mock-ups, and developing sustainable chemistry. While AI alone cannot save the planet, it plays a significant role as part of a broader solution.
In conclusion, the use of artificial intelligence is increasingly being adopted to promote greener buildings. Efforts to improve energy efficiency have been made through LEED certifications and stringent energy codes introduced by governments. Despite these endeavors, the majority of buildings lack smart systems for effective energy management. JLL has invested heavily in AI systems as eco-friendly buildings yield higher rents and spend less time on the market. Factors such as sensors, historical patterns, and occupants’ habits are leveraged to optimize energy consumption.
However, challenges arise in gathering data from multiple sources within buildings and ensuring consistency and quality. Improved data collection is crucial for the success of AI applications in buildings. Siemens employs AI to compare buildings, Siemens also highlights the importance of sustainable materials to achieve environmental goals. Fifth Wall focuses on decarbonizing buildings and acknowledges the potential of AI in identifying viable building upgrades and streamlining processes. Ultimately, AI is a valuable tool in addressing the environmental impact of buildings.
For custom-tailored AI solutions and software, contact us here at Tanzanite AI. We work in a wide range of industries and provide renowned solutions globally.