The Design of Directions and Shot Sound Distance Using Fuzzy Logic Method Based on Raspberry Pi

Abstract - The rise of a shooting incident that occurred in the border areas of the Republic of Indonesia is a big loss for the state in terms of personnel. Technological developments can be used as an alternative in the military world to help the role of soldiers so as to reduce personnel losses. This study aims to create a system for detecting the direction and distance of gunshots. This study uses an experimental method. This gunshot detection system also applies the Fuzzy Logic Method which is applied to the Raspberry Pi 4 and Microphone Max 4466 which is expected to detect the direction and distance of gunshots. This Fuzzy Logic method is used as an inference system or decision maker according to the input given. Fuzzy Logic broadly consists of fuzzification, rule base, and defuzzification. Fuzzification is useful for input normalization, so that the input quantity is in accordance with the fuzzy magnitude, namely the value in the range 0 to 1. After that, enter the rule base where in this step, the input set is compared with the rules or provisions of sound decibels so that it can be classified whether the distance and the direction of the captured sound is in the data range that has been programmed, in this step the signal is analyzed how much decibel sound SS2-V1 is by the MAX 4466 sensor. The conclusion is done by defuzzification, so the final result is that the closest distance to a gunshot at 1 meter is 250 Decibels.

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Flood Detection System Using Ultrasonic Sensor with Fuzzy Logic Method

10.2991/aer.k.211106.027 ◽

2021 ◽

Author(s):

Jessy Nasyta Putri Santoso ◽

Tri Tisna Firly Hartini ◽

Ali Suryaperdana Agoes

Keyword(s):

Fuzzy Logic ◽

Detection System ◽

Ultrasonic Sensor ◽

Fuzzy Logic Method ◽

Flood Detection ◽

Logic Method

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Automatic Drain System in Seawater Aquarium with Fuzzy Logic Method

JURNAL MEDIA INFORMATIKA BUDIDARMA ◽

10.30865/mib.v4i3.2209 ◽

2020 ◽

Vol 4 (3) ◽

pp. 753

Author(s):

Nur Adin ◽

Hilal Hudan Nuha

Keyword(s):

Fuzzy Logic ◽

Sea Water ◽

Ph Sensor ◽

Ornamental Fish ◽

Measurement Results ◽

Technological Developments ◽

Fuzzy Logic Method ◽

Seawater Quality ◽

Logic Method

In seawater aquariums, seawater quality plays a very important role for the survival of the biota in it. There are measurement parameters that determine the quality of the seawater fit to be inhabited by seawater ornamental fish such as clown fish. Measurement parameters are such as temperature, salinity, dissolved oxygen content (DO), pH, ammonia, nitrite, and nitrate. Current technological developments make it possible to create a system that automatically conducts seawater drainage in a seawater aquarium so that the quality of the seawater remains in accordance with its measurement parameters and is fit for habitation by seawater ornamental fish such as clown fish. In this study the measurement parameters that become the reference are the temperature, pH (acidity) values obtained from the temperature sensor and the pH sensor. For normal temperatures, if the temperature is in the range of 24°C to 28°C, while for the ideal temperature is in the range of 25-27°C. For an appropriate pH in a saltwater aquarium is 7.5-8.5 with an ideal pH of 8.2. From the results of measurements made by these sensors, the value will be processed using the fuzzy logic method, then the condition of sea water quality in the aquarium can be seen from the smartphone, and when the measurement results show an inappropriate value, the system will automatically drain the water

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Prediction of Unconfined Compressive Strength of Microfine Cement Injected Sands Using Fuzzy Logic Method

10.21203/rs.3.rs-232296/v1 ◽

2021 ◽

Author(s):

Eray Yildirim ◽

Eyubhan Avci ◽

Nurten Akgün Tanbay

Keyword(s):

Compressive Strength ◽

Fuzzy Logic ◽

Unconfined Compressive Strength ◽

Injection Pressure ◽

Coefficient Of Determination ◽

Rule Base ◽

Logic Models ◽

Fuzzy Logic Method ◽

Microfine Cement ◽

Logic Method

Abstract In this study, unconfined compressive strength values of sand soil injected with microfine cement were predicted using fuzzy logic method. Mamdani and Sugeno methods were applied in the fuzzy logic models. In addition, a regression analysis was carried out in order to compare these two methods. In the models, water/cement ratio and injection pressure were the input variables, and unconfined compressive strength was the output variable. The dataset includes 427 samples, which were experimentally injected with microfine cement. Predictions for unconfined compressive strength were obtained by creating membership functions and rule base for each input (predictive) parameter in fuzzy logic models. The coefficient of determination (R2) and Mean Square Error (MSE) were used as criteria for evaluating the performance of the developed models. The results suggested that the three applied models (i.e. Mamdani, Sugeno and regression) provided statistically significant results, and these methods could be used in the future prediction-based studies. The results showed that Sugeno model provided the best performance for predicting unconfined compressive strength. It was followed by Mamdani and Regression models, respectively. This study has suggested that the fuzzy logic method can be an alternative to the regression method which traditionally has been used in prediction process.

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Covid-19 Symptom Detection System in Public Area using Fuzzy Logic Method

10.1109/ies53407.2021.9594030 ◽

2021 ◽

Author(s):

Abdillah S. Nursam ◽

Moch. Zen Samsono Hadi ◽

Prima Kristalina

Keyword(s):

Fuzzy Logic ◽

Detection System ◽

Fuzzy Logic Method ◽

Public Area ◽

Logic Method

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Egg Quality Detection System Using Fuzzy Logic Method

Kinetik Game Technology Information System Computer Network Computing Electronics and Control ◽

10.22219/kinetik.v4i3.839 ◽

2019 ◽

pp. 207-216

Author(s):

Ikbar Mahesa ◽

Aji Gautama Putrada ◽

Maman Abdurohman

Keyword(s):

Fuzzy Logic ◽

Real Time ◽

Data Storage ◽

Egg Quality ◽

Detection System ◽

Optimization Method ◽

Light Sensor ◽

Fuzzy Logic Method ◽

Logic Method

Determining the quality of eggs in general is used by placing eggs on a flashlight. The detection system is very necessary to determine good egg quality or rotten eggs, so that the conditions of the eggs can be known by the chicken farm company and then will be sold to the community. This egg detecting system utilizes several sensor devices that are combined. The sensor used to detect the quality of eggs is a light sensor and a heavy sensor by connected with a microcontroller. So that there is no ambiguity towards the decision making of good egg or rotten eggs, then processing the data is obtained from these sensors using Fuzzy Logic and Firebase methods in real time as data storage media, and actuators will distribute or separate good eggs or the rotten eggs one. With the development of technology now, we can use the Internet of Things (IoT) technology, one of the systems check the quality of eggs which are good or not good. This system is built using a microcontroller to coordinate the running of the system using the Fuzzy Logic Method that applies inside. Final information is obtained on the form of egg quality in real time. The test results were carried out using the Fuzzy Logic method and obtained 95% results from 20 eggs and had 1 wrong egg. When using system hardware without using the fuzzy logic method on the microcontroller that using only a light sensor and a heavy sensor it produces a result of 75% from 20 eggs and had 5 wrong eggs. Using the egg detection optimization method can be increased up to 20%.

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Pengembangan Nominal Aturan Fuzzy pada Metode Fuzzy Mamdani untuk Menyeimbangkan Beban Tiga Phasa pada Saluran Distribusi Tegangan Menengah

Rekayasa ◽

10.21107/rekayasa.v14i3.10655 ◽

2021 ◽

Vol 14 (3) ◽

pp. 431-442

Author(s):

Martinus W Djagolado ◽

Amirullah Amirullah ◽

Saidah Saidah

Keyword(s):

Fuzzy Logic ◽

Low Voltage ◽

Fuzzy Rules ◽

Voltage Distribution ◽

Voltage Transformer ◽

Load Current ◽

Inference System ◽

Medium Voltage ◽

Fuzzy Logic Method ◽

Logic Method

The use of electrical equipment on the customer side with low voltage absorbs unbalanced power. The load unbalances in each phase will result in an unbalanced current, resulting in a phase voltage shift in the secondary coil of the 20 kV/380 V medium voltage transformer. Shifting the voltage in the distribution transformer phase, then causes the flow of current in the transformer neutral wire causing losses. This paper proposes a fuzzy logic method with the Mamdani fuzzy inference system (FIS) to balance three-phase load currents at seven feeders of 20 kV medium voltage distribution at PLN Rayon Taman Jawa-Timur. The feeders are Ngelom, Tawang Sari, Geluran, Bringin, Masangan Kulon, Palm Residence, and Pasar Sepanjang. There are three input variables used, namely the load current in phase R, phase S, and phase T respectively. There are three output variables in one FIS block, namely changes in load current in phase R, phase S, and phase T respectively. With the number of fuzzy rules as many as 509 rules, the proposed method is able to produce the lowest load current unbalance value of 1.6% at Palm Residence Feeders. The development of a nominal (number) of fuzzy rules in the Fuzzy Logic Method with FIS Mamdani is able to reduce the value of unbalance load current at the 20 kV medium voltage distribution feeder better than the method proposed by previous researchers.

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