Leveraging Machine Learning and Big Data for Smart Buildings: A Comprehensive Survey

TL;DR

This survey reviews how machine learning and big data analytics are transforming smart buildings by enabling enhanced services, efficiency, and resident comfort, while discussing current trends and challenges in the field.

Contribution

It provides a comprehensive overview of the role of machine learning and big data in smart building development, highlighting current trends and challenges.

Findings

Machine learning enables predictive maintenance and energy optimization.

Big data analytics facilitates real-time decision making in smart buildings.

Current challenges include data privacy and integration complexity.

Abstract

Future buildings will offer new convenience, comfort, and efficiency possibilities to their residents. Changes will occur to the way people live as technology involves into people's lives and information processing is fully integrated into their daily living activities and objects. The future expectation of smart buildings includes making the residents' experience as easy and comfortable as possible. The massive streaming data generated and captured by smart building appliances and devices contains valuable information that needs to be mined to facilitate timely actions and better decision making. Machine learning and big data analytics will undoubtedly play a critical role to enable the delivery of such smart services. In this paper, we survey the area of smart building with a special focus on the role of techniques from machine learning and big data analytics. This survey also reviews the current trends and challenges faced in the development of smart building services.