Internet of things (IoT) based I-V curve tracer for photovoltaic monitoring systems

The use of solar PV system in Indonesia has expanded to various field and area. One example is residential buildings in urban areas. This article discusses calculation methods for designing a solar power generation system that is applied to residential buildings, such as homes, offices, or colleges. Electricity generated from the solar home system (SHS) is used to support many kinds of electrical equipments, where the electrical equipments are used by building occupants in their daily life. The calculation method is considered from the potential of solar energy and the reliability of the on-site system to generate electricity. The system is designed in an off-grid topology by exchanging connections with the public electricity grid owned by PLN. Calculation results shows that this SHS has a generation capacity of 1 kWp, 24 V 300 Ah battery storage, and a 200 W inverter. This SHS can reduce electricity usage in this sector by 18.2 kWh in average every month.

Section: Scc Specificationmentioning

confidence: 99%

A practical method to design the solar photovoltaic system applied on residential building in Indonesia

Megantoro

Anugrah

Afif

et al. 2021

“…The individual model exhibits its own pros and cons and is best fit for specific types of target complications. A discussion of problems in the Internet of Things (IoT) application [5][6][7][8][9] using regression analysis has been presented in [10]. In addition, each model can be recyclable and is built by a training set of algorithms using classical data.…”

Section: Related Studiesmentioning

confidence: 99%

Performance evaluation of listwise deletion for impaired datasets in multiple regression-based prediction

Jittawiriyanukoon¹

2019

Multiple Regression-Based Prediction (MRBP) is an emerging calculation to or analysis technique cope with the future by compiling the history of data. The MRBP characteristic will include an approximation for the associations between physical observations and predictions. MRBP is a predictive model, which will be an important source of knowledge in terms of an interesting trend to be followed in the future. However, there is impairment in the MRBP dataset, wherein each form of missing and noisy data has caused an error and is unavailable further analysis. To overcome this unavailability, so that the data analytics can be moved on, two treatment approaches are introduced. First, the given dataset is denoised; next, listwise deletion (LD) is proposed to handle the missing data. The performance of the proposed technique will be investigated by dealing with datasets that cannot be executed. Employing the Massive Online Analysis (MOA) software, the proposed model is investigated, and the results are summarized. Performance metrics, such as mean squared error (MSE), correlation coefficient (COEF), mean absolute error (MAE), root mean squared error (RMSE), and the average error percentage, are used to validate the proposed mechanism. The proposed LD projection is confirmed through actual values. The proposed LD outperforms other treatments as it only requires less state space, which reflects low computation cost, and proves its capability to overcome the limitation of analysis.

“…In this work, we designed an effective low-cost infant incubator with remote monitoring based IoT. An IoT is a concept that exploits the advantages of internet connectivity in a continuous manner with the possibility to share data, remote controlling, and several other features, while, ThingSpeak enables the creation of sensor logging applications [20][21][22][23][24]. According to that, the change in the temperature and humidity of infant incubator is possible to be observed through the IoT program of Arduino using ESP8266 wireless module.…”

Section: Introductionmentioning

confidence: 99%

Remote monitoring of a premature infants incubator

Shabeeb

Al-Askery

Nahi

2020

In this paper, the air temperature and humidity levels in the infant' incubator are monitored remotely by means of Arduino microcontroller with different sensors and an open source internet of things (IoT) applications. The system is connected to a network via a wireless fidelity (Wi-Fi) connection to be linked to an application on the smart phone or to the computer. The system is designed using Arduino microcontroller, DHT11/DHT22 sensor for measuring the body parameters, such as the temperature and the humidity, LCD monitor, ESP8266 WiFi modules, and NodeMCU-v3.The results have shown that real time updated medical records can be transferred to the medical staff utilizing ThingSpeak IoT applications.