Modeling of water temperature in evaporation pot with 7 Ds18b20 sensors based on Atmega328 microcontroller

Mahardika, Pillar Satya; Gunawan, Anak Agung Ngurah

doi:10.21744/lingcure.v6ns3.2123

Cited by 7 publications

(6 citation statements)

References 18 publications

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“…This thermal sensor was powered from a 3.2 V DC power supply. A DS18B20 waterproof temperature sensor was used [44] to measure the temperature of the oil before and after the experiments. Temperature changes less than one degree Celsius were detected.…”

Section: Optimal Position Of the Polarizersmentioning

confidence: 99%

Characterization of Partial Discharges in Dielectric Oils Using High-Resolution CMOS Image Sensor and Convolutional Neural Networks

Monzón-Verona,

González-Domínguez,

García-Alonso

2024

Sensors

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In this work, an exhaustive analysis of the partial discharges that originate in the bubbles present in dielectric mineral oils is carried out. To achieve this, a low-cost, high-resolution CMOS image sensor is used. Partial discharge measurements using that image sensor are validated by a standard electrical detection system that uses a discharge capacitor. In order to accurately identify the images corresponding to partial discharges, a convolutional neural network is trained using a large set of images captured by the image sensor. An image classification model is also developed using deep learning with a convolutional network based on a TensorFlow and Keras model. The classification results of the experiments show that the accuracy achieved by our model is around 95% on the validation set and 82% on the test set. As a result of this work, a non-destructive diagnosis method has been developed that is based on the use of an image sensor and the design of a convolutional neural network. This approach allows us to obtain information about the state of mineral oils before breakdown occurs, providing a valuable tool for the evaluation and maintenance of these dielectric oils.

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Section: Optimal Position Of the Polarizersmentioning

confidence: 99%

Characterization of Partial Discharges in Dielectric Oils Using High-Resolution CMOS Image Sensor and Convolutional Neural Networks

Monzón-Verona,

González-Domínguez,

García-Alonso

2024

Sensors

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“…The DS18B20 sensor detects blood temperature in the infusion tube via the heater. The DS18B20 sensor has a 12 Bit inter ADC with an accuracy value of +/-0.5ºC [21]. The MLX90614 sensor detects body temperature, and the optocoupler sensor indicates when the liquid has run out.…”

Section: ) Datasheet Descriptionmentioning

confidence: 99%

Fuzzy Logic Temperature Control on Blood Warmer Equipped with Patient Temperature and Blood Temperature

Hafizh,

Hamzah,

Syaifudin

2024

Indones.J.electronic.electromed.med.inf

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Body temperature in humans varies greatly depending on the location where the reading is taken. Normal core body temperature in humans is maintained by the hypothalamus and usually ranges from 36.5°C to 37.5°C. One of the causes of the failure of Too high or too low of a temperature during the blood transfusion procedure may cause blood to freeze or get damaged, both of which can be fatal to humans, therefore the purpose of this tool is to lower blood temperature admission to the patient can be achieved so that there is no temperature drop or temperature drop and so that the blood is not too hot because it can cause damage to red blood cells. This study uses the DS18B20 Sensor to control the heater with PID and Fuzzy controls, the MLX90614 Sensor to adjust the temperature according to the patient's body temperature and the Optocoupler Sensor as an indicator when fluids run out. Previous studies have not used the MLX90614 sensor to detect patient body temperature, have not used TFT Nextion and have not used Fuzzy controls. This Fuzzy control is used as a heater control which then the results are displayed on the Nextion TFT. The results of this study obtained the highest error value of 0.09 with an average error value of 0.04 and obtained the highest overshoot value of 0.8. From the results of the above study it can be concluded that by using the Fuzzy control the response time is slower with a larger overshoot. In the creation of this tool, the benefits that can be derived for the community are facilitating the monitoring of patient temperature and blood temperature during blood transfusions using the Blood Warmer device. The device is also equipped with sensors to detect patient and blood temperatures, and it comes with a Nextion TFT display. Therefore, this device is crucial in assisting the community in performing Blood Transfusions.

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“…These sensors use a digital protocol called 1-wire to send the data readings directly to the development board without the need of an analog to digital converter or other extra hardware. Its accuracy ranges from −10 to 85 • C [106]. The DS1922L on the other hand, is a self-sufficient system that measures temperature and records the result in a protected memory section and the temperature range is −40 to 85 • C [107].…”

Section: Sensing Technologies-the Sensing Layermentioning

confidence: 99%

A Systematic Review of Real-Time Monitoring Technologies and Its Potential Application to Reduce Food Loss and Waste: Key Elements of Food Supply Chains and IoT Technologies

et al. 2022

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Continuous monitoring of food loss and waste (FLW) is crucial for improving food security and mitigating climate change. By measuring quality parameters such as temperature and humidity, real-time sensors are technologies that can continuously monitor the quality of food and thereby help reduce FLW. While there is enough literature on sensors, there is still a lack of understanding on how, where and to what extent these sensors have been applied to monitor FLW. In this paper, a systematic review of 59 published studies focused on sensor technologies to reduce food waste in food supply chains was performed with a view to synthesising the experience and lessons learnt. This review examines two aspects of the field, namely, the type of IoT technologies applied and the characteristics of the supply chains in which it has been deployed. Supply chain characteristics according to the type of product, supply chain stage, and region were examined, while sensor technology explores the monitored parameters, communication protocols, data storage, and application layers. This article shows that, while due to their high perishability and short shelf lives, monitoring fruit and vegetables using a combination of temperature and humidity sensors is the most recurring goal of the research, there are many other applications and technologies being explored in the research space for the reduction of food waste. In addition, it was demonstrated that there is huge potential in the field, and that IoT technologies should be continually explored and applied to improve food production, management, transportation, and storage to support the cause of reducing FLW.

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Modeling of water temperature in evaporation pot with 7 Ds18b20 sensors based on Atmega328 microcontroller

Cited by 7 publications

References 18 publications

Characterization of Partial Discharges in Dielectric Oils Using High-Resolution CMOS Image Sensor and Convolutional Neural Networks

Characterization of Partial Discharges in Dielectric Oils Using High-Resolution CMOS Image Sensor and Convolutional Neural Networks

Fuzzy Logic Temperature Control on Blood Warmer Equipped with Patient Temperature and Blood Temperature

A Systematic Review of Real-Time Monitoring Technologies and Its Potential Application to Reduce Food Loss and Waste: Key Elements of Food Supply Chains and IoT Technologies

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