Enhancing Building Energy Efficiency Through IoT Integration

Year : 2024 | Volume : 02 | Issue : 02 | Page : 15 23
    By

    Dhanush M,

  • Shivashankar Hiremath,

  • Subramanya R. Prabhu B.,

  1. Student, Department of Mechatronics, Manipal Institute of Technology, Manipal Academy Higher Education (MAHE), Manipal, Karnataka, India
  2. Professor, Department of Mechatronics, Manipal Institute of Technology, Manipal Academy Higher Education (MAHE), Manipal, Karnataka, India
  3. Professor, Department of Mechatronics, Manipal Institute of Technology, Manipal Academy Higher Education (MAHE), Manipal, Karnataka, India

Abstract

Building management systems featuring Internet of Things (IoT) technology provide a revolutionary way of maximizing user comfort and improve the use of energy. This study presents a comprehensive analysis of various components within an IoT subsystem utilized in building management, including Smart IoT Gateways, temperature and humidity sensors, lightweight database systems such as Tiny DB, and cloud communication platforms like Twilio. Each component plays a vital role in facilitating real- time monitoring, control, and data analysis, ultimately leading to informed decision-making and improved operational efficiency. A detailed examination of recent studies highlights the impact of daylight supplementation on user experience in office environments, showcasing positive user feedback regarding the integration of horizontal light pipes (HLP). Furthermore, the implementation of static pressure management in HVAC systems demonstrates significant potential for energy savings, with reductions exceeding 50% in certain scenarios. The study also addresses critical methodologies for ductwork calculations, emphasizing the Minimal Energy Dissipation Principle (Min EDP) as a robust alternative for analyzing airflow in duct networks. Additionally, various control techniques for air handling units (AHUs) are classified, ranging from classical methods to advanced strategies, underscoring the need for flexible and adaptive control mechanisms in HVAC systems. The findings underscore the importance of a well-implemented IoT framework, which not only enhances energy efficiency but also prioritizes user satisfaction and comfort in modern building environments. By synthesizing insights from various studies and practical applications, this research contributes to the ongoing discourse on sustainable building practices and the effective integration of IoT technologies in the quest for energy-efficient solutions.

Keywords: IoT, energy efficiency, smart IoT gateway, Tiny DB, Twilio, HVAC systems

[This article belongs to International Journal of Machine Systems and Manufacturing Technology ]

How to cite this article:
Dhanush M, Shivashankar Hiremath, Subramanya R. Prabhu B.. Enhancing Building Energy Efficiency Through IoT Integration. International Journal of Machine Systems and Manufacturing Technology. 2024; 02(02):15-23.
How to cite this URL:
Dhanush M, Shivashankar Hiremath, Subramanya R. Prabhu B.. Enhancing Building Energy Efficiency Through IoT Integration. International Journal of Machine Systems and Manufacturing Technology. 2024; 02(02):15-23. Available from: https://journals.stmjournals.com/ijmsmt/article=2024/view=196743


References

1. Gao J, Helle L. User perceptions of daylight supplementation via horizontal light pipes in office environments. Light Res Technol. 2019; 51(3): 356–371. DOI: 10.1177/1477153517751971
2. Shim H, Kwon H, Kim S. Performance analysis of VFD-motor-fan systems with static pressuremanagement. Energy Build. 2020; 207: 109681. DOI: 10.1016/j.enbuild.2019.109681
3. Ahmed T, Tukur A, Al-Mansoori M. Tools and technologies for retro- and ongoing commissioning of HVAC systems in existing buildings. Energy Rep. 2021; 7(2): 123–134. DOI: 10.1016/j.egyr.2021.02.004
4. Hossain MS, Khan S. A methodology for reducing carbon emissions from HVAC systems in pharmaceutical facilities. J Clean Prod. 2019; 237: 117688. DOI: 10.1016/j.jclepro.2019.117688

5. Milosavljevic P, Marchetti AG, Cortinovis A, Timm M, Faulwasser T, Mercangöz M, et al. Real-time optimization of load sharing for gas compressors in the presence of uncertainty. Appl Energy. 2020;272:114883. DOI: 10.1016/j.apenergy.2020.114883.
6. Afram A, Janabi-Sharifi F. Theory and applications of HVAC control systems—a review. Build Environ. 2014; 72: 368–375. DOI: 10.1016/j.buildenv.2013.11.016
7. Balasubramanian K, Jothi RJ, Manoharan A. Statistical and machine learning approaches for failure detection and diagnosis of air handling units. Energy Procedia. 2020; 158: 259–264. DOI: 10.1016/j.egypro.2019.01.199
8. Tarjan L, Cserhati C. IoT integration in Industry 4.0: A low-cost solution for industrial machines. Procedia Manuf. 2020; 45: 10–17. DOI: 10.1016/j.promfg.2020.04.052
9. Ali O, Ishak MK. Bringing intelligence to IoT Edge: Machine Learning based Smart City Image Classification using Microsoft Azure IoT and Custom Vision. J Phys Conf Ser. 2020;1529:042076. DOI: 10.1088/1742-6596/1529/4/042076
10. Shu X, Dong Y, Liu J, Xu X. Study of the optimal control of the central air conditioning cooling water system for a Deep Subway

Regular Issue Subscription Review Article
Volume 02
Issue 02
Received 28/10/2024
Accepted 14/11/2024
Published 27/11/2024
217

Login


My IP

PlumX Metrics