IoT-Based Shutter Movement Simulation for Smart Greenhouse Using Fuzzy-Logic Control

Ameen, Nihad M.; Al-Ameri, Janan A. Mahdi

doi:10.1109/dese.2019.00119

Cited by 5 publications

(2 citation statements)

References 4 publications

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“…The Internet of Things, also known as the acronym IoT, aims to expand the benefits of internet connectivity. IoT can be defined as a connection or link between physical devices with sensors and actuators to the internet, where devices are intelligently linked together, allowing for the exchange of data and information [11]. Sensors collect data from various physical conditions such as temperature and humidity, transmitting these data [12].…”

Section: B Iot and Mqttmentioning

confidence: 99%

Smart Chicken Coop Ecosystem for Optimal Growth of Broiler Chickens Using Fuzzy on IoT

Suprianto

Pristiya

Prasetyo

2022

Inf. J. Ilm. Bid. Teknol. Inf. dan Komun.

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Chicken consumption is one of the high-value economic sectors. In order to harvest chickens optimally, it is necessary to maintain the temperature and humidity of the chicken coop regularly. The application of IoT to monitor the temperature and humidity of the chicken coop is significant. Therefore, an automatic temperature-humidity control system based on decisions made using the Sugeno fuzzy method is also needed. Smart chicken coop with the fuzzy algorithm on platform internet of things can be used as an alternative process temperature and humidity control automatically replace conventional method. Based on the results of the tests, this system can control temperature and humidity at 30.3°C, which is the ideal temperature for the growing time of broilers.

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Section: B Iot and Mqttmentioning

confidence: 99%

Smart Chicken Coop Ecosystem for Optimal Growth of Broiler Chickens Using Fuzzy on IoT

Suprianto

Pristiya

Prasetyo

2022

Inf. J. Ilm. Bid. Teknol. Inf. dan Komun.

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“…Fuzzy logic is an alternative to the classic logic that proposes the modelling of systems where variables are handled with a certain level of imprecision (i.e., temperature, air pollution and tank filling level). These kind of variables can take ambiguous values such as: very-low, low, medium, high, very-high [1]; empty, low, medium, full, critical [2], among others. Handling this type of variables could not be supported by a precise mathematical model to establish control actions [3].…”

Section: Introductionmentioning

confidence: 99%

A Mandami Fuzzy Controller for Handling a OpenHAB Smart Home

Pico-Valencia

Holgado-Terriza

2021

Intelligent Environments 2021

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Fuzzy control systems are widely used to carry out control actions where variables with a certain degree of ambiguity are involved. Such control actions are modelled based on fuzzy rules that are expressed in a language analogous to that used by humans to conceive their reality. In this sense, fuzzy controllers can be applied in emerging technologies such as the Internet of Things (IoT) aimed at controlling the real world through a set of objects interconnected to the Internet. This article presents a fuzzy controller of Mamdani-type developed in Matlab. This controller is integrated into a smart home– created by the OpenHAB tool– using RESTful services. The results of the evaluation reveal that the integration of the fuzzy controller with smart home can provide an accurate control of comfort specifically in this case. In addition, a better organization of the control rules was also possible using the proposed fuzzy controller especially when large systems are developed.

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