Domestic Chicken Chick's Banda using Neuro fuzzy logic technique for reducing energy cost

Efficient hygro-thermal and ammonia control in day-old chick brooding box using internet of things and Tsukamoto Fuzzy controller

“…This controller is an important component of the system, and in this section, we study its design and function. Fuzzy logic control (FLC) is a well-established technique for managing complex systems without the need for detailed mathematical models [10], [11], [16], [24]. Fuzzy controller synthesis involves several main steps:…”

“…Rule Formulation: Create a set of rules that determine how inputs relate to outputs. In this study, the researchers propose the utilization of the Tsukamoto Fuzzy logic (T-FLC) as a means to improve the response, accuracy, and computational efficiency of the system [11], [16]. To apply the fuzzy logic method for brooding box micro-climate control with parameters of humidity, ammonia, and temperature, steps that can be taken done is as follows:…”

“…However, one of the primary impediments to livestock development in tropical regions is heat stress. Factors such as high temperatures, excessive humidity, and elevated concentrations of ammonia and carbon dioxide significantly affect the well-being of day-old chicks [4], [9]- [11]. Conventional control strategies employed by many farmers often overlook the intricate interactions between day-old chicks and their external environment, resulting in suboptimal performance and unnecessary energy consumption [2], [4].…”

“…In recent years, fuzzy logic controllers (FLCs) have gained prominence for various applications, including assessing the suitability of cooling systems for broiler buildings and controlling staged heating and ventilation systems [10], [11], [16], [18]. FLCs have demonstrated advantages over traditional On/Off controllers in day-old chick brooding house systems [19] due to their ability to operate without the need for precise mathematical models and their adaptability to set-point changes.…”

“…However, in commercial and research-oriented livestock facilities, these controllers often face limitations in achieving desired indoor parameters within an acceptable time frame and can lead to excessive energy consumption. [2], [11] Motivated by the advantages of fuzzy logic controllers, this research introduces a hybrid control scheme that combines self-tuning parameters adjusted by fuzzy rules with a Tsukamoto fuzzy controller. This novel approach capitalizes on the flexibility of past and future time integration, aiming to mitigate system fluctuations while maintaining the simplicity of controller implementation.…”