IoT-Driven Building Energy Management Systems (BEMS) for Net Zero Energy Buildings: Concept, Integration and Future Directions

TL;DR

This paper reviews IoT-enabled Building Energy Management Systems (BEMS), evaluates datasets for AI control, discusses integration challenges, and presents a case study on best practices for achieving Net Zero Energy Buildings.

Contribution

It provides a comprehensive review, dataset evaluation, and analysis of challenges, along with a case study, advancing understanding of IoT-driven BEMS for NZEBs.

Findings

IoT-enabled BEMS components and architectures are systematically reviewed.

Real-world datasets support AI-based predictive control in BEMS.

Integration challenges include interoperability and smart grid compatibility.

Abstract

Construction and operating of buildings is one of the major contributors to global greenhouse emissions. With the inefficient usage of energy due to human behavior and manual operation, the energy consumption of buildings is further increased. These challenges highlight the need for improved Building Energy Management Systems (BEMS) integrated with Internet of Things (IoT) and data driven intelligence to enhance energy-efficiency in a building and contribute to Net-Zero Energy Buildings (NZEB) targets. This paper offers four keys contributions: i) a systematic review of IoT enabled BEMS including components, network architecture and functional capabilities, ii) an evaluation of real-world BEMS datasets to support Artificial Intelligence (AI) based predictive control, iii) an analysis of integration challenges related to interoperability, smart grids and net-zero energy strategies, and iv) a case study highlighting global best practices, performances outcomes, and lesson learned for scaling advanced BEMS solutions.