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Development of Embedded System for Centralized Insomnia System Novi Azman; Mohd Khanapi Abd Ghani; Muhammad Haikal Satria; Muhammad Zillullah Mukaram
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Insomnia is a common health problem in medical field as well as in psychiatry. The measurement of those factors could be collected by using polysomnography as one of the current standards. However, due to the routine of clinical assessment, the polysomnography is impractical and limited to be used in certain place. The rapid progress of electronic sensors to support IoT in health telemonitoring should provide the real time diagnosis of patient at home too. In this research, the development of centralized insomnia system for recording and analysis of patient with chronic-insomnia data is proposed. The system is composed from multi body sensors that connected to main IOT server. The test has been done for 5 patients and the result has been successfully retrieved in real time.

Artificial Neural Network Parameter Tuning Framework For Heart Disease Classification Mohamad Haider Abu Yazid; Haikal Satria; Shukor Talib; Novi Azman
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Heart Disease are among the leading cause of death worldwide. The application of artificial neural network as decision support tool for heart disease detection. However, artificial neural network required multitude of parameter setting in order to find the optimum parameter setting that produce the best performance. This paper proposed the parameter tuning framework for artificial neural network. Statlog heart disease dataset and Cleveland heart disease dataset is used to evaluate the performance of the proposed framework. The results show that the proposed framework able to produce high classification accuracy where the overall classification accuracy for Cleveland dataset is 90.9% and 90% for Statlog dataset.

DESIGN OF THE POLLUTION GAS CARBON MONOXIDE (CO) MONITORING SYSTEM BASED ON MICROCONTROLLER Erna Kusuma Wati; Fitria Hidayanti; Novi Azman
Spektra: Jurnal Fisika dan Aplikasinya Vol 5 No 1 (2020): SPEKTRA: Jurnal Fisika dan Aplikasinya, Volume 5 Issue 1, April 2020
Publisher : Program Studi Fisika Universitas Negeri Jakarta

Carbon monoxide is a flammable gas and very toxic to humans, to determine the concentration of carbon monoxide (CO) gas requires a tool that can measure the concentration of the gas. The design of the CO gas monitoring measuring instrument in this study has dimensions of 11cm x 8.6 cm x 2.9 cm using the MQ-135 sensor, Arduino Uno microcontroller to control and process the signal, to display temperature and humidity with a 4.2 Inch LCD. Krisbow KD09-224 Carbon Monoxide Meter is a comparison tool or calibrator, against our monitoring gauges. Testing by experimenting as much as 15 times, to determine the value of the measurement uncertainty. Based on the results of the data when testing, the average amount of measurement = 103.33, with a standard deviation δ 1.29, and the uncertainty value of the measurement results is 0,33 %. Thus the system can be used as monitoring of CO gas pollution in units of ppm (parts per million).

Development of a Remote Straw Mushroom Cultivation System Using IoT Technologies Novi Azman; Muhammad Habiburrohman; Endang Retno Nugroho
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol 9, No 3 (2023): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v9i3.26280

Indonesia's tropical climate creates vast potential for straw mushroom cultivation. However, crop failures are frequent during the rainy season due to lower temperatures. To address this challenge, this paper presents an innovative, IoT-based system designed to remotely control and monitor temperature and humidity in mushroom cultivation sites, thereby minimizing crop failure and optimizing production. The proposed system employs a DHT11 sensor to measure temperature and humidity levels accurately. A DS3231 module is incorporated to schedule automatic watering procedures, ensuring adequate hydration for the mushrooms without manual intervention. For real-time monitoring, an ESP32-Cam is used to capture images of the mushroom cultivation site. The core of this system is a NodeMCU microcontroller, which processes environmental data and automatically adjusts the cultivation conditions. The system triggers a heater if the temperature falls below 30°C, or an exhaust fan if it exceeds 35°C. Similarly, a humidifier activates if humidity falls below 80%, and an exhaust fan turns on when humidity exceeds 90%. To provide users with instant updates, the system integrates with the Blynk application, sending notifications when these specified conditions are met. This feature allows for prompt intervention when necessary, facilitating optimal growth conditions at all times. During testing, the proposed system demonstrated its effectiveness, enabling successful straw mushroom cultivation within nine days. Furthermore, it achieved this with modest power consumption, using a total of 661.608Wh. This system offers a promising solution to improve straw mushroom farming in regions with similar climates to Indonesia.

Development of a Remote Straw Mushroom Cultivation System Using IoT Technologies Azman, Novi; Habiburrohman, Muhammad; Nugroho, Endang Retno
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 9 No. 3 (2023): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v9i3.26280

Indonesia's tropical climate creates vast potential for straw mushroom cultivation. However, crop failures are frequent during the rainy season due to lower temperatures. To address this challenge, this paper presents an innovative, IoT-based system designed to remotely control and monitor temperature and humidity in mushroom cultivation sites, thereby minimizing crop failure and optimizing production. The proposed system employs a DHT11 sensor to measure temperature and humidity levels accurately. A DS3231 module is incorporated to schedule automatic watering procedures, ensuring adequate hydration for the mushrooms without manual intervention. For real-time monitoring, an ESP32-Cam is used to capture images of the mushroom cultivation site. The core of this system is a NodeMCU microcontroller, which processes environmental data and automatically adjusts the cultivation conditions. The system triggers a heater if the temperature falls below 30°C, or an exhaust fan if it exceeds 35°C. Similarly, a humidifier activates if humidity falls below 80%, and an exhaust fan turns on when humidity exceeds 90%. To provide users with instant updates, the system integrates with the Blynk application, sending notifications when these specified conditions are met. This feature allows for prompt intervention when necessary, facilitating optimal growth conditions at all times. During testing, the proposed system demonstrated its effectiveness, enabling successful straw mushroom cultivation within nine days. Furthermore, it achieved this with modest power consumption, using a total of 661.608Wh. This system offers a promising solution to improve straw mushroom farming in regions with similar climates to Indonesia.

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