Academic literature on the topic 'IoT-enabled HVAC'

The convergence of Artificial Intelligence (AI), the Internet of Things (IoT), and cloud computing is transforming the HVAC industry, creating fully automated, efficient, and sustainable systems. This paper explores how IoT-enabled sensors, AI algorithms, and cloud-based platforms are redefining HVAC operations by enabling real-time monitoring, predictive maintenance, and energy optimization. It highlights the role of these technologies in advancing smart building concepts and discusses the challenges, including data security and integration costs, as well as the opportunities presented by their adoption. Emerging trends and future innovations in HVAC technologies are also examined, emphasizing their potential to drive sustainability and improve indoor environments.

This systematic review provides a comprehensive analysis of the advancements, challenges, and future directions of smart HVAC systems by examining 125 peer-reviewed articles following the PRISMA methodology. The study focuses on five critical areas: IoT-enabled HVAC systems, machine learning algorithms for predictive maintenance, renewable energy integration, data privacy and security concerns, and the economic feasibility of implementation. The findings highlight that IoT-enabled HVAC systems significantly enhance energy efficiency by leveraging real-time data from interconnected sensors, leading to energy savings between 20% and 40% through adaptive heating, cooling, and ventilation strategies. Additionally, machine learning algorithms in predictive maintenance play a crucial role in reducing system failures, cutting unscheduled maintenance costs by up to 40%, and improving energy efficiency by 15% to 25% through automated fault detection and optimized maintenance scheduling. Furthermore, renewable energy integration in HVAC systems, particularly hybrid solutions combining solar, geothermal, and wind energy, has demonstrated remarkable potential, with some systems achieving energy savings of up to 60%. However, challenges such as high upfront installation costs, the need for advanced energy storage solutions, and infrastructure limitations continue to hinder widespread adoption. The review also identifies data privacy and security vulnerabilities as a major concern in IoT and AI-powered HVAC systems. 20 reviewed articles highlight risks associated with data transmission, unauthorized access, and cyber threats, emphasizing the need for robust encryption techniques, blockchain-based security, and AI-driven authentication mechanisms to enhance protection and user trust. Moreover, the economic feasibility of smart HVAC solutions remains a key factor influencing adoption. While these systems require higher initial investments, findings from 15 reviewed studies indicate that the return on investment (ROI) typically falls within five to seven years, particularly for large-scale commercial applications where energy cost savings and predictive maintenance benefits accumulate more rapidly. Policy incentives, tax rebates, and government subsidies have also been recognized as crucial enablers for accelerating adoption, making smart HVAC technologies more accessible for residential and small business users. This review synthesizes existing knowledge, evaluates emerging trends, and identifies persistent barriers in smart HVAC technologies. The findings provide valuable insights for researchers, industry stakeholders, and policymakers to develop scalable, cost-effective, and energy-efficient HVAC solutions. Future research should focus on enhancing system interoperability, improving data security frameworks, and developing innovative financing models to facilitate the transition toward more sustainable and intelligent HVAC solutions in the built environment.

This study explores the integration of advanced sensing technologies into HVAC systems to improve efficiency and performance, with a focus on Northwest Indiana casinos. The project addresses challenges faced by traditional systems, such as inconsistent temperature control, high energy consumption, and poor air quality, which impact guest comfort and operational costs. Using a controlled testing environment and EnergyPlus simulation software, the research modeled casino-specific HVAC loads while incorporating IoT-enabled sensors, infrared thermal imaging, and AI-based optimization. Infrared cameras identified inefficiencies such as air leaks and duct blockages, while Schlieren imaging visualized airflow distribution to address zoning problems. Data was collected in 5-minute intervals across a 1-hour period to evaluate thermal comfort, airflow consistency, and energy use. Results demonstrate a 15% reduction in simulated energy consumption, enhanced airflow uniformity, and improved indoor air quality through better ventilation control. This research highlights the potential for intelligent HVAC technologies to enhance sustainability, reduce operational costs, and elevate guest experiences in high-occupancy environments.

Most of the appliances used in office buildings such as the room lights, fans and Air Conditioners (AC) are manually operated, where one has to switch ON and OFF these appliances. If one tends to forget to turn OFF these switches, it will impose a major challenge in building economic stimulus for their fiscal development. It can thereby increase the amount of energy consumed and thus increasing the electricity bills. Therefore, there is an urgent need for improvement and use of a smart lighting system. This paper introduces the energy- saving, easy-to-install, wireless and low cost IoT based smart office lighting system which is suitable for installation in the office or departmental company. It uses an infrared human motion sensor (PIR Sensor) working in coordination with other sensors. When no one is there in the space, all lights, fans and Air Conditioners (AC) are turned OFF; otherwise they are turned ON to save energy. The same can be controlled via IoT and the internet. The system can easily realize energy saving and easy control of LED lighting.

The evolvement of smart glass technology has gained a lot of interest through its energy-saving potential as one of the heating, ventilating, and airconditioning (HVAC) system. This paper focuses on polymer dispersed liquid crystal (PDLC) film, a smart glazing film that changes its opacity in response to an electrical impulse. The power consumption of the smart film is considerably small. However, improper handling of the smart film such as not turning off the film after usage can lead to energy wastage. Hence, connecting the smart film to an internet of things (IoT) controller would be one of the possible solutions to ensure that the film is maintained properly. The objective of the work here is to develop a smart, low cost and efficient IoT-enabled smart controller for PDLC films with energy-saving features. In pursuance of materializing this concept, this paper delineates the design of a smart controller for the PDLC films. The implementation of the IoT features, NodeMCU, and environmental sensors enabled the smart film to be capable of switching automatically. In addition, voice-command features were also incorporated into the controller. With the successful development of the IoT smart controller, the PDLC films can operate autonomously and wirelessly.

<p><span lang="EN-US">The evolvement of smart glass technology has gained a lot of interest through its energy-saving potential as one of the heating, ventilating, and air-conditioning (HVAC) system. This paper focuses on polymer dispersed liquid crystal (PDLC) film, a smart glazing film that changes its opacity in response to an electrical impulse. The power consumption of the smart film is considerably small. However, improper handling of the smart film such as not turning off the film after usage can lead to energy wastage. Hence, connecting the smart film to an internet of things (IoT) controller would be one of the possible solutions to ensure that the film is maintained properly. The objective of the work here is to develop a smart, low cost and efficient IoT-enabled smart controller for PDLC films with energy-saving features. In pursuance of materializing this concept, this paper delineates the design of a smart controller for the PDLC films. The implementation of the IoT features, NodeMCU, and environmental sensors enabled the smart film to be capable of switching automatically. In addition, voice-command features were also incorporated into the controller. With the successful development of the IoT smart controller, the PDLC films can operate autonomously and wirelessly.</span></p>

Efficient management of heating, ventilation, and air conditioning (HVAC) systems is paramount for mitigating energy consumption and enhancing climate resilience in modern infrastructure. This review explores the significance of leveraging project management tools to optimize energy efficiency within HVAC operations, thus fostering a pathway towards climate resilience. The integration of project management methodologies offers a systematic approach to address challenges associated with energy consumption in HVAC systems, thereby facilitating informed decision-making processes. Firstly, the review delves into the pressing need for energy conservation in HVAC operations amidst escalating concerns over climate change and its adverse impacts. The imperative to minimize energy consumption in buildings, particularly through HVAC systems, is highlighted as a pivotal step towards achieving climate resilience and sustainability goals. Subsequently, the review outlines the role of project management tools in orchestrating effective strategies to enhance energy efficiency within HVAC operations. By employing techniques such as project scheduling, risk management, and resource allocation, project managers can streamline the implementation of energy-efficient measures, thereby optimizing HVAC system performance and reducing carbon emissions. Moreover, the review underscores the importance of data analytics and technological advancements in augmenting the efficacy of project management tools for energy efficiency in HVAC operations. Leveraging real-time data monitoring, predictive analytics, and IoT-enabled devices enables proactive maintenance and continuous optimization of HVAC systems, thereby maximizing energy savings and bolstering climate resilience. Furthermore, the review elucidates the potential benefits and challenges associated with the adoption of project management tools for energy efficiency in HVAC operations. While improved cost-effectiveness, environmental sustainability, and operational performance emerge as primary benefits, challenges such as initial investment costs, technological complexities, and organizational inertia necessitate careful consideration. This review advocates for the integration of project management tools as a viable approach to foster energy efficiency in HVAC operations, thereby paving the way towards enhanced climate resilience and sustainability in built environments. By embracing innovative methodologies and technological solutions, stakeholders can mitigate energy consumption, reduce greenhouse gas emissions, and fortify infrastructure against the impacts of climate change.
 Keywords: HVAC, Climate Resilience, Project Management, Energy, Review.

This study presents an integrated approach for adapting building energy systems using Machine Learning (ML), the Internet of Things (IoT), and Building Information Modeling (BIM) in a hotel retrofit in Italy. In a concise multi-stage process, long-term climatic data and on-site technical documentation were analyzed to create a detailed BIM model. This model enabled energy simulations using the Carrier–Pizzetti method and supported the design of a hybrid HVAC system—integrating VRF and hydronic circuits—further enhanced by a custom ML algorithm for adaptive, predictive energy management through BIM and IoT data fusion. The study also incorporated photovoltaic panels and solar collectors, reducing reliance on non-renewable energy sources. Results demonstrate the effectiveness of smart energy management, showcasing significant potential for scalability in similar building typologies. Future improvements include integrating a temporal evolution model, refining feature selection using advanced optimization techniques, and expanding validation across multiple case studies. This research highlights the transformative role of ML, IoT, and BIM in achieving sustainable, smart, and efficient building energy systems, offering a replicable framework for sustainable renovations in the hospitality sector.

This study proposes an IoT-based smart campus framework integrating Arduino microcontrollers, cloud services, and sensor networks to automate traffic control, adaptive lighting, smart rooms, and irrigation systems. The system aims to transform traditional campus management by enhancing operational efficiency, sustainability, and safety through real-time data analytics. Objectives: Use of Arduino microcontrollers to automate processes in campus and remote monitoring over cloud through MQTT protocols to optimize resource utilization. Method: Sensor networks (motion, gas, RFID), microcontrollers (Arduino Mega, NodeMCU) and wireless staff (ESP8266) was applied to collect real-time data. Cloud integration (CloudMQTT) and REST APIs enabled centralized control. Automated algorithms adjust lighting, HVAC, traffic signals, and irrigation based on sensor feedback. Results: Some key metrics are as follows: 40% in energy savings in lighting, 35% global water savings towards irrigation, 98.7% in RFID accuracy and 40% decrease on global traffic wait time (on peak hours). Conclusion: The IoT substantially enhances campus management. Future work will combine AI with air quality sensors

Smart building's benefits range from improving comfort of occupant, increased productivity, reduction in energy consumption and operating costs, lower CO2 emission, to improved life cycle of utilities, efficient operation of building systems, etc. [65]. Hence, modern building owners are turning towards smart buildings. However, the current smart buildings mostly are not capable of achieving the objectives they are designed for and they can improve a lot better [22]. Therefore, a new technology called, Internet of Things, or IoT, is combined with the smart buildings to improve their performance [23]. IoT is the inter-networking of things embedded with electronics, software, sensors, actuators, and network connectivity to collect and exchange data, and things in this definition is anything and everything around us and even ourselves. Using this technology, e.g. a door can be a thing and can sense how many people have passed it's sensor to enter a space and let the lighting system know to prepare appropriate amount of light, or the HVAC (Heating Ventilation Air Conditioning) system to provide desirable temperature. IoT will provide a lot of useful information that before that accessibility to it was impossible, e.g., condition of water pipes in winter, which helps avoiding damages like frozen or broken pipes. However, despite all the benefits, IoT suffers from being vulnerable to cyber attacks. Examples have been provided later in Chapter 1. In this project among building systems, HVAC system is chosen to be automated with a new control method called MPC (Model Predictive Control). This method is fast, very energy efficient and has a lower than 0.001 rate of error for regulating the space temperature to any temperature that the occupants desire according to the results of this project. Furthermore, a PID (Proportional–Integral–Derivative) controller has been designed for the HVAC system that in the exact same cases MPC shows a much better performance. To design controllers for HVAC system and set the temperature to the desired value a method to automate balancing the heat flow should be found, therefore a thermal model of building should be available that using this model, the amount of heat, flowing in and out of a space in the building disregarding the external weather would be known to estimate. To automate the HVAC system using the programming languages like MATLAB, there is a need to convert the thermal model of the building to a mathematical model. This mathematical model is unique for each building depending on how many floors it has, how wide it is, and what materials have been used to construct the building. This process is needs a lot of effort and time even for buildings with 2 floors and 2 rooms on each floor and at the end the engineer might have done it with error. In this project you will see a software that will do the conversion of thermal model of buildings in any size to their mathematical model automatically, which helps improving the HVAC controllers to set temperature to the value occupants desire and avoid errors and time loss which is put both into calculations and troubleshooting. In addition, a test environment has been designed and constructed as a cyber physical system that allows us to test the IoT- enabled control systems before implementing them on real buildings, observe the performance, and decide if the system is satisfying or not. Also, all cyber threats can be explored and the solutions to those attacks can be evaluated. Even for the systems that are already out there, there is an opportunity to be assessed on this testbed and if there is any vulnerability in case of cyber security, solutions would be evaluated and help the existing systems improve.<br>Master of Science