TRANSFORMING CLIMATE CONTROL WITH AI AND IMAGE PROCESSING FOR ENERGY EFFICIENT SMART HOMES AND INDUSTRIAL ENVIRONMENTS

This research presents an intelligent climate control system using artificial intelligence (AI) and image processing to enhance energy efficiency and user comfort in smart homes and industrial settings. By integrating You Only Look Once (YOLO)-based human detection and facial recognition algorithms, the system dynamically adjusts Heating, Ventilation, and Air Conditioning (HVAC) settings based on user presence and preferences. Experimental results showed 95% accuracy in human detection and 94% in facial recognition, ensuring reliability under various conditions. Energy savings of 30% were achieved by activating energy-saving modes during inactivity. User feedback highlighted ease of use and adaptability. While designed for smart homes, the system can also optimize HVAC settings in industrial environments, contributing to sustainable energy practices. Despite challenges such as low-light sensitivity and scalability, the proposed system demonstrates AI’s role in energy-efficient, user-focused automation. This work lays the foundation for smart home technology, advancing sustainable and personalized solutions while reducing costs and improving efficiency.

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Publication Details

Journal
Konya Journal of Engineering Sciences
Published
2026-09-01
DOI
https://doi.org/10.36306/konjes.1671699
Primary Topic
IoT-based Smart Home Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

TRANSFORMING CLIMATE CONTROL WITH AI AND IMAGE PROCESSING FOR ENERGY EFFICIENT SMART HOMES AND INDUSTRIAL ENVIRONMENTS

Ömer Aydın, Atahan Uyanık
Konya Journal of Engineering Sciences
IoT-based Smart Home Systems
article

TRANSFORMING CLIMATE CONTROL WITH AI AND IMAGE PROCESSING FOR ENERGY EFFICIENT SMART HOMES AND INDUSTRIAL ENVIRONMENTS

Ömer Aydın, Atahan Uyanık
article en

Abstract

This research presents an intelligent climate control system using artificial intelligence (AI) and image processing to enhance energy efficiency and user comfort in smart homes and industrial settings. By integrating You Only Look Once (YOLO)-based human detection and facial recognition algorithms, the system dynamically adjusts Heating, Ventilation, and Air Conditioning (HVAC) settings based on user presence and preferences. Experimental results showed 95% accuracy in human detection and 94% in facial recognition, ensuring reliability under various conditions. Energy savings of 30% were achieved by activating energy-saving modes during inactivity. User feedback highlighted ease of use and adaptability. While designed for smart homes, the system can also optimize HVAC settings in industrial environments, contributing to sustainable energy practices. Despite challenges such as low-light sensitivity and scalability, the proposed system demonstrates AI’s role in energy-efficient, user-focused automation. This work lays the foundation for smart home technology, advancing sustainable and personalized solutions while reducing costs and improving efficiency.

Konya Journal of Engineering SciencesVol. 14(3)
Manisa Celal Bayar University (TR)
Manisa Celal Bayar Üniversitesi
Affordable and clean energy
Openalex Percentile: Top 20%
IoT-based Smart Home Systems
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TRANSFORMING CLIMATE CONTROL WITH AI AND IMAGE PROCESSING FOR ENERGY EFFICIENT SMART HOMES AND INDUSTRIAL ENVIRONMENTS — Ömer Aydın, Atahan Uyanık · Konya Journal of Engineering Sciences (2026) | TGRS Research Map | TGRS