Abstract
Highlights: What are the main findings? There is a lack of research on integrating Industry 4.0 into ventilation system maintenance planning. Existing reviews cover sensors, AI/ML, and big data in HVAC, but not integrated Maintenance 4.0. What are the implications of the main findings? Effective ventilation is crucial for indoor air quality, health, and energy efficiency. AI-driven analytics enable proactive, data-driven maintenance for optimized schedules, failure prediction, and improved performance. This article explores the integration of Maintenance 4.0 into HVAC (heating, ventilation, and air conditioning) systems, highlighting its essential role within the framework of Industry 4.0. Maintenance 4.0 utilizes advanced technologies such as artificial intelligence and IoT sensing technologies. It also incorporates sophisticated data management techniques to transform maintenance strategies into HVAC and indoor ventilation systems. These innovations work together to enhance energy efficiency, air quality, and overall system performance. The paper provides an overview of various Maintenance 4.0 frameworks, discussing the role of IoT sensors in real-time monitoring of environmental conditions, equipment health, and energy consumption. It highlights how AI-driven analytics, supported by IoT data, enable predictive maintenance and fault detection. Additionally, the paper identifies key research gaps and challenges that hinder the widespread implementation of Maintenance 4.0, including issues related to data quality, model interpretability, system integration, and scalability. This paper also proposes solutions to address these challenges, such as advanced data management techniques, explainable AI models, robust system integration strategies, and user-centered design approaches. By addressing these research gaps, this paper aims to accelerate the adoption of Maintenance 4.0 in HVAC systems, contributing to more sustainable, efficient, and intelligent built environments.
| Original language | English |
|---|---|
| Article number | 66 |
| Journal | Smart Cities |
| Volume | 8 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - Apr 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
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SDG 11 Sustainable Cities and Communities
Keywords
- indoor air quality (IAQ)
- internet of things (IoT)
- machine learning (ML)
- maintenance 4.0
- ventilation systems
ASJC Scopus subject areas
- Urban Studies
- Artificial Intelligence
- Electrical and Electronic Engineering
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