Automated Smart Home Controller Based on Adaptive Linear Neural Network

Siswipraptini, Puji Catur; Aziza, Rosida Nur; Sangadji, Iriansyah Bm; Indrianto, Indrianto; Siregar, Riki Ruli A.

doi:10.1109/iccma46720.2019.8988733

Cited by 7 publications

(9 citation statements)

References 17 publications

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“…Monitoring button device to start the monitoring tool process entering current and voltage measurements in real-time and to reset the monitoring process, the Reset button is used. 300 load, from a power supply source, the next process is to monitor the devices that are on the application interface that has been designed [29]. In the output part of this system consists of: 1.…”

Section: Methodsmentioning

confidence: 99%

Fuzzy mamdani logic inference model in the loading of distribution substation transformer SCADA system

Ningrum

Siregar

Rusjdi

2021

IJ-AI

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The research objective of supervisory control and data acquisition (SCADA), with fuzzy Mamdani logic simulation on the loading section of distribution transformer substations. Data acquisition is available when saving SAIFI SAIDI data and storing the results of monitoring equipment. The method used is Mamdani fuzzy logic, there are two input variables, namely current and voltage devices. The membership function in Mamdani fuzzy logic has been created based on the input current and voltage variables. Currently: parameter {0, 600} low is created {0, 350, 450, 600}, normal {400-650} parameter is created {400, 500, 550, 650}, parameter high {≥600} is created {600, 650, 750, 1000}, when determining the voltage: low {≤10.5} parameters {0 4 7 10.5}, normal {9-14} parameters {9, 10, 13, 14} and high {≥13} - parameters {13, 14, 15, 16}. Based on the results of the Mamdani logic rule test on the output current containing a transformer and a voltage sensor, the results obtained are IF (normal current; (630) AND voltage (high); (13.2) (high load transformer). The components in the simulation tool include miniature substations made with the 1A travel substation model, 3A substation as the main substation, the relay as distribution substation as the monitoring application. Telestatus and Telecontrol use a microcontroller. Initial scenario. After substation is resumed, data is stored after downtime, service life, duration, and data period. Initial scenario After substation is resumed, data is stored after downtime, service life, duration, and data period.

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Section: Methodsmentioning

confidence: 99%

Fuzzy mamdani logic inference model in the loading of distribution substation transformer SCADA system

Ningrum

Siregar

Rusjdi

2021

IJ-AI

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“…Then, it is compared with the actual data. The methodology for implementing ADALINE for the prototype is shown in Figure 1 This study has identified the problem that less implementation of an ANN system model as a mobile system that allows setting the home appliances control in one interface [18]. Normally in previous research only had automatic control, but did not yet have any function for monitoring home appliances such as a lamp, temperature, air conditioning (AC), and television (TV) [18]- [21].…”

Section: Methodsmentioning

confidence: 99%

“…The methodology for implementing ADALINE for the prototype is shown in Figure 1 This study has identified the problem that less implementation of an ANN system model as a mobile system that allows setting the home appliances control in one interface [18]. Normally in previous research only had automatic control, but did not yet have any function for monitoring home appliances such as a lamp, temperature, air conditioning (AC), and television (TV) [18]- [21]. The designed science and technology for humanity (STH) applies adaptive linear neural network (ADALINE) as its method, IoT, and utilizes microcontrollers, sensors, and several other supporting electronic devices [21], [22].…”

Section: Methodsmentioning

confidence: 99%

IoT for smart home system

Siswipraptini

Aziza

Sangadji

et al. 2021

IJEECS

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This paper examines the integration of smart home and solar panel system that is controlled and monitored using IoT (internet ofthings). To enable the smart home system to monitor the activity within the house and act according to the current conditions, it is equipped with several sensors, actuators and smart appliances. All of these devices have to be connected to a communication network, so they can communicate and provide services forthe smart home’s in habitants. The smart home system was first introduced to provide comfort and convenience, but later it should also address many other things, e.g. the importance of the efficient use of energy or electricity and hybrid use of energy sources. A solar panel is added to the smart home prototype and its addition is studied. Adaptive linear neural network is implemented in the prototype as an algorithm for predicting decisions based on the current conditions. The construction of the proposed integrated systemis carried out through several procedures, i.e. the implementation of the adaptive linear neural network (ADALINE) as the neural network method, the design of the prototype and the testing process. This prototype integrates functionalities of several household appliances into one application controlled by an Android-based framework.

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“…Salah satu kendala masalah yang perlu mendapatkan perhatian adalah pada keberlanjutan operasi dari pembangkit listrik tenaga surya (PLTS) yang telah terpasang mengingat instalasi pembangkit tersebut memerlukan biaya investasi yang cukup tinggi. Lokasi pembangkit listrik tenaga surya yang tersebar di daerah terpencil dalam prakteknya menjadi kendala tersendiri dalam hal pemantauan data, kinerja dan kendali pembangkit yang telah terpasang [3]. Pada pembangkit yang dipasang sebagai Concentrated Standalone System, monitoring umumnya dilakukan secara lokal dan tersentral pada pusat pembangkit baik secara manual ataupun otomatis [3].…”

Section: Pendahuluanunclassified

“…Lokasi pembangkit listrik tenaga surya yang tersebar di daerah terpencil dalam prakteknya menjadi kendala tersendiri dalam hal pemantauan data, kinerja dan kendali pembangkit yang telah terpasang [3]. Pada pembangkit yang dipasang sebagai Concentrated Standalone System, monitoring umumnya dilakukan secara lokal dan tersentral pada pusat pembangkit baik secara manual ataupun otomatis [3]. Monitoring secara manual memiliki kelemahan diantaranya adalah akses parameter, kendali dan data monitoring yang sangat terbatas, tidak lengkap dan tidak kontinu karena keterbatasan operator.…”

Section: Pendahuluanunclassified

Sistem Kendali Dan Monitoring Dengan Syaraf Tiruan Pada Pembangkit Listrik Tenaga Surya

Sikumbang

Haris

Elly

2020

petir

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The problem with the condition of the Solar Power Plant is still not optimal due to position of the solar cells in generator is still static so that absorption of light is still not even though Hybrid technology is now available but cannot be optimized properly and still cannot be optimized implemented especially in small scale and remote areas. Another problem that needs attention is the continued operation of installed Solar Power Plants (SPPs), considering the installation and maintenance of the plant requires high investment costs because the installation of solar panels requires a large amount of land and costs besides requiring qualified technical personnel to handle problems and monitoring plant conditions are needed quickly and accurately. From the description of the problem, the first step is to identify the technology used in the factory, the second is the need to design a new system to be able to solve important problems in the plant and the third is to build a computerized system that uses the Hybrid Method on the plant used. is a combination of Artificial Intelligence and Data Mining Processes so that it can present accurate data so that it can help and analyze plant performance, monitor and control plants remotely quickly by using Web Control.

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Automated Smart Home Controller Based on Adaptive Linear Neural Network

Cited by 7 publications

References 17 publications

Fuzzy mamdani logic inference model in the loading of distribution substation transformer SCADA system

Fuzzy mamdani logic inference model in the loading of distribution substation transformer SCADA system

IoT for smart home system

Sistem Kendali Dan Monitoring Dengan Syaraf Tiruan Pada Pembangkit Listrik Tenaga Surya

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