Artificial intelligence: Powering IoT for real estate firms

July 25, 2018

A blog post by Surabhi Kejriwal, real estate research leader, Deloitte Support Services India Pvt. Ltd.

Using artificial intelligence (AI) to augment decision-making

Smart buildings appear to be the new normal. In a world that will be increasingly dominated by digital natives, an IoT-enabled building is the future. Recent research by MarketsandMarkets suggests a 33.7 percent compounded-annual-growth rate in the smart building market, to $31.7 billion, by 2022.¹ Further, IoT-enabled buildings are connecting with other sensor-enabled devices, such as mobile apps, wearable devices and so forth. The growth in connected devices continues to create a deluge of data. How can commercial real estate (CRE) owners and developers harness these structured and unstructured data to make more informed decisions?

Two years ago, Deloitte highlighted two strategies to optimally use this data in our report, Smart buildings: How IoT technology aims to add value for real estate companies. The strategies we named were, first, to develop advanced data aggregation and processing capabilities and second, to build a flexible platform to collect and exchange building data, as continuous evolution of data standards could render prior platforms obsolete.

Since then we realized that some CRE companies may not possess the requisite talent required to process this data. Professionals with the skills required to aggregate, analyze, and manage the data are scarce and the data sets are enormous. How then can these companies crunch the data and generate adequate returns on their investment in IoT technology?

AI could be a potential solution. CRE companies can harness the predictive capability of AI technologies such as machine learning to generate insights and power decision-making. Machine-learning technology “can automatically identify patterns and detect anomalies in the data that smart sensors and devices generate—information such as temperature, pressure, humidity, air quality, vibration, and sound.”² CRE companies can use AI in this way to drive operational efficiency and tenant satisfaction. For instance, Google’s AI-based predictive tool uses sensor information to forecast pressure and temperature at its data centers. The company has been able to optimize power consumption and reduce cooling costs by 40 percent.

A combination of sensor data and machine-learning solutions may also help improve real-time threat detection and response. As an example, the city of Las Vegas is using AI technology to detect and automate responses to cyber threats.³ Other AI technologies such as speech recognition and computer vision can extract insights from sensor data, which typically require human intervention.

Given the benefits of AI-powered IoT systems, many vendors are now evolving building management systems (BMS) to incorporate AI.⁵ According to the International Data Corp., AI will support “all effective” IoT efforts by 2019.⁶ It is also believed that IoT data will have “limited value” without the use of AI technology.⁷

In summary, CRE executives that are implementing IoT technology should consider AI-powered IoT systems. Owners of existing smart buildings should supplement their buildings with AI technology to mine the data.