Abstract
Smart home technologies have emerged with the prominence of human safety and comfort today. With the advancement of technology, it is one of the most important automation issues being worked on. Smart home technologies provide home and environmental security first. These were also the house of cooling, heating, automatic control of the garage door, automatic control of lighting, home, and garden, office control of the safety of children, can perform many operations such as the automatic feeding of plants and animals. Smart home provides control of all your electrically powered devices through existing electricity. Physical quantities such as temperature, humidity, and light level in a smart home need to be controlled intelligently. Thus, users are provided with a convenient opportunity to fully control all electrical appliances in the house, and users are freed from tasks that previously required manual control. In recent years, studies have been conducted at a level that will rival many control methods such as PID (Proportional Integral Derivative) for many applications. Many control methods such as PID, artificial neural networks, model predictive control, genetic algorithm have been tried for climate control and different results have been obtained. With this study, it is aimed to introduce the fuzzy logic control algorithm and climate control system and to serve as an example of its use for smart homes.
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References
Li M, Li G-Y, Chen H-R, Jiang C-W (2018) QoE-aware smart home energy management considering renewables and electric vehicles. Energies 11(9):2304. https://doi.org/10.3390/en11092304
Francis M, Luqman R, Charles D, Audu A (2022) Energy savings for air conditioning system using fuzzy logic controller design for Northeastern Nigeria. https://doi.org/10.35313/ijatr.v3i2.95
Sevil M, Elalmış N (2015) Control of air conditioning with fuzzy logic controller design for smart home systems. Sigma J Eng Nat Sci 33(3):439–463
Asadullah M, Abbas S (2018) Social networks of things for smart homes using fuzzy logic. IJCSNS Int J Comput Sci Netw Secur 18(2)
Saddik LA, Benahmed K, Bounaama F (2022) Evaluation quality of service for internet of things based on fuzzy logic: a smart home case study. Indonesian J Electr Eng Comput Sci 25(2):825–839. https://doi.org/10.11591/ijeecs.v25.i2.pp825-839
Khajeh H, Laaksonen H, Godoy M (2023) A fuzzy logic control of a smart home with energy storage providing active and reactive power flexibility services. Electric Power Syst Res 216. https://doi.org/10.1016/j.epsr.2022.109067
Valiyev A, Imamguluyev R, Ilkin G (2021) Application of fuzzy logic model for daylight evaluation in computer aided interior design areas. In: 14th international conference on theory and application of fuzzy systems and soft computing—ICAFS-2020. https://doi.org/10.1007/978-3-030-64058-3_89
Imamguluyev R (2021) Application of fuzzy logic model for correct lighting in computer aided interior design areas. In: Intelligent and fuzzy techniques: smart and innovative solutions. https://doi.org/10.1007/978-3-030-51156-2_192
Imamguluyev R (2020) Determination of correct lighting based on fuzzy logic model to reduce electricity in the workplace. In: Conference: international conference on Eurasian economies, Baku, Azerbaijan. https://doi.org/10.36880/C12.02456
Imamguluyev R, Mikayilova R, Salahli V (2022) Application of a fuzzy logic model for optimal assessment of the maintenance factor affecting lighting in interior design. In: Mobile computing and sustainable informatics, proceedings of ICMCSI 2022. https://doi.org/10.1007/978-981-19-2069-1_32
Aliev R, Tserkovny A (2020) Fuzzy logic for incidence geometry. In: Beyond traditional probabilistic data processing techniques: interval, fuzzy etc. methods and their applications. https://doi.org/10.1007/978-3-030-31041-7_4
Abdullayev T, Imamguluyev R, Umarova N (2022) Application of fuzzy logic model for optimal solution of light reflection value in lighting calculations. In: 11th international conference on theory and application of soft computing, computing with words and perceptions and artificial intelligence—ICSCCW-2021. https://doi.org/10.1007/978-3-030-92127-9_53
Zadeh LA, Aliev R (2018) Fuzzy logic theory and applications: part I and part II, p 61. https://doi.org/10.1142/10936
Zadeh LA (1997) Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic. Fuzzy Sets Syst 90:111–127
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Valiyev, A., Imamguluyev, R., Mikayilova, R. (2023). Designing Climate Control with Fuzzy Logic for Smart Home Systems. In: Shakya, S., Papakostas, G., Kamel, K.A. (eds) Mobile Computing and Sustainable Informatics. Lecture Notes on Data Engineering and Communications Technologies, vol 166. Springer, Singapore. https://doi.org/10.1007/978-981-99-0835-6_48
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DOI: https://doi.org/10.1007/978-981-99-0835-6_48
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