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All Journal Vokasi UNESA Bulletin of Engineering, Technology and Applied Science
Amirullah Amirullah
Departement of Electrical Engineering, Faculty of Engineering, Universitas Bhayangkara Surabaya, Surabaya, Indonesia
Computer Science & IT Engineering Mechanical Engineering Transportation

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Solar-Powered IoT-Based Home Fire Early Warning and Protection System Muhammad Arief Wicaksono; Amirullah Amirullah; Boonyang Plangklang
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science Vol. 2 No. 2 (2025)
Publisher : Universitas Negeri Surabaya or The State University of Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/vubeta.v2i2.35773

Abstract

This paper presents the implementation of a prototype of a fire early warning system in a residential house using temperature and smoke sensors supplied by an Internet of Things (IoT) based solar module. The 10 Wp solar module is the energy source connected to a 12V battery via a solar charge controller (SSC). Data retrieval is carried out through testing by the MQ-2 Sensor and LM35 Sensor, respectively, to detect smoke (gas) and heat. The system then activates the buzzer, sends data from the detection of the status and level of smoke (gas) and heat to the smartphone screen and liquid crystal displays (LCD) in the form of an alarm, and orders the PLN switch to work to cut off the electricity. The results of the tool test show that the proposed prototype is able to provide early warning notifications regarding the status and level of smoke (gas) and heat - both from the LCD and remotely from the smartphone, and is able to activate the relay dan order the switch cuts off the electricity to prevent fire. The prototype system's source is supplied by solar modules independently, making it applicable in remote areas with limited electricity access-compared to the previous model which was supplied solely by the electricity grid.
Power Quality Enhancement Using Single Phase Shunt Active Filter Based ANFIS Supplied by Photovoltaic Anis Fitriani; Amirullah Amirullah; Krischonme Bhumkittipich
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science Vol. 2 No. 3 (2025)
Publisher : Universitas Negeri Surabaya or The State University of Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/vubeta.v2i3.39071

Abstract

This paper proposes a single-phase shunt active filter (ShAF) combined with photovoltaic (PV) to enhance power quality performance by reducing source current harmonics and compensating for reactive power in a single-phase 220-Volt distribution system with a frequency of 50 Hz connected to a non-linear load. The PV panel consists of several PV modules with a maximum power of 600 W each. An adaptive neuro-fuzzy inference system (ANFIS) controls the voltage in the DC link capacitor circuit in the ShAF. This method isproposed to overcome the weakness of the Fuzzy Sugeno method in neural network-based learning capabilities to determine the fuzzy rules of the input membership functions (MFs) and the weakness of the proportional-integral (PI) control in determining proportional and integral constants using trial and error method. The single-phase system is connected to a non-linear load with a combination, i.e. without ShAF, using ShAF, and using ShAF-PV, respectively, with a total of seven cases. Based on the three proposed control methods and model configurations, the ShAF-PV circuit with ANFIS control is able to result in the best performance because it is able to produce the lowest source current THD. The single-phase system using ShAF-PV with ANFIS control is also capable of injecting the largest reactive power compared to the ShAF and ShAF configurations with PI and Fuzzy-Sugeno control. The increase in reactive power in the ShAF-PV is further able to compensate for the reactive power, so it is able to suppress and reduce the source reactive power significantly.
Co-Authors Anis Fitriani Boonyang Plangklang Krischonme Bhumkittipich Muhammad Arief Wicaksono