Temperature Monitoring System Research Articles

Achieving temperature stability for storage of biological samples in an autodefrost freezer.

To assess the temperature stability of an autodefrost freezer commonly used in veterinary practices, whether the use of a Styrofoam cooler within the freezer provides temperature stability, and the ease of use of a remote monitoring system for the notification of temperature elevations. None. Temperature in the freezer and 2 Styrofoam coolers were assessed with remote monitoring thermometers every 15 minutes. Temperature values were monitored from October 11 to December 18, 2023 (for a 68-day period). Data analysis focused on temperatures for the freezer exceeding 0 °C and the elevations in temperatures within the coolers relative to the freezer. The freezer had an increase in temperature approximately every 16 hours. Over 68 days, the freezer had a temperature greater than 0 °C 27 times, representing 26 separate elevations. The Styrofoam coolers within the freezer never registered a temperature higher than -5 °C. Elevations in temperature within the freezer were larger in magnitude than temperature elevations within the coolers, which showed smaller-magnitude changes in temperature. The temperature stability provided by the Styrofoam cooler would avoid potential freeze-thaw cycles of any stored biological samples. Additionally, the remote temperature monitoring system is easy to install and monitor, providing peace of mind to practice management.

Monitoring Soil Temperature and Humidity in an IoT-Based Green House to Improve Plant Management

This study aims to develop and validate a soil temperature and humidity monitoring system using DHT 11 and YL 69 sensors connected to an ESP 8266 microcontroller. Calibration was performed by comparing sensor data with a reference instrument, followed by regression analysis to determine sensor accuracy. Validation involved calculating the standard deviation and accuracy of the sensor measurements. Temperature and soil humidity monitoring was conducted over five days in September, with average temperature measurements ranging from 22.4°C to 32.6°C and soil humidity ranging from 66.47% to 88.78%. The results showed that the temperature sensor had an average accuracy of 99.19%, while the humidity sensor had an average accuracy of 97.95%. The low standard deviation values for both sensors indicate good measurement consistency. These findings align with the literature emphasizing the importance of high-performance sensors for environmental monitoring in smart agriculture systems. The implementation of this system is expected to enhance the efficiency and effectiveness of agricultural management and support the sustainability of agricultural practices.

Temperature Monitoring System for 3 Phase Electric Arc Furnace (EAF) Transformer Cooling

The Electric Arc Furnace (EAF) transformer is a key component in the steel melting system using a furnace. The transformer functions to convert the electrical voltage from the main electrical network into the electrical voltage needed to form an electric arc in the melting furnace. In this research, the EAF transformer configuration uses a delta-wye configuration with a furnace melting capacity of 10 kg nickel ore. In its working system, this transformer will produce a very high current when the melting system is running. So this process will produce excessive heat on the EAF transformer side. As a result of the significant heat generated in the melting process, this transformer is equipped with a cooling system in the form of transformer oil which is a heat release medium and maintains the correct operating temperature. An appropriate temperature monitoring system will increase the work efficiency of the transformer and prevent excessive damage to the system. The sensor used in the design is the RTD PT 100 sensor which is installed at 7 measurement points. The main controller for data collecting and data processing used is a Siemens PLC. Data that has been processed on the main control device is transmitted to the IoT cloud server using a V-box device. As a human machine interface (HMI) web SCADA is used to read data in real time. From the results of the tests that have been carried out, the highest error presentation value obtained in measurements on the T phase is 0.05%. Meanwhile, when measuring the transformer oil sensor, an error value of 0% was obtained.

Analysis on the cooperative variation law of pile-soil temperature field in Island permafrost region

To determine the cooperative variation laws of temperature fields in bridge concrete piles and the surrounding frozen soil during the freezing process in high-latitude, low-altitude insular permafrost regions, we utilized a practical bridge construction project within the frozen soil area of the Daxing'an Mountains, China. This served as the foundation for developing a method to remotely and dynamically monitor the temperatures of piles and soil in permafrost regions, enabling continuous, automatic monitoring of pile-soil temperature data. Employing this automatic temperature monitoring system, we collected temperature data from two 15-m-long concrete bored piles before and after freezing, and monitored the freezing process of the pile foundations in real-time. The cooperative variation laws of the pile-soil temperature field over time were summarized, and a calculation equation for the pile foundation's freezing time was established based on finite element analysis results. Monitoring and analysis reveal that under the influence of the frozen soil temperature field, the pile foundation initially freezes from the bottom up in a unidirectional manner. When the atmospheric temperature falls below 0 °C, the pile foundation freezes simultaneously from both the upper and lower directions. Post-freezing, the internal temperature of the pile body aligns with the surrounding soil temperature, with a temperature difference of less than 0.1 °C at the same depth. For similar in-place temperatures, the freezing time for a test pile with a 1.2m diameter is 1.14 times that of a 1.0m diameter test pile. The range of the hydration heat effect of cement concrete extends 1–2 times the pile diameter.

Remote Water Quality Monitoring System In Shrimp Ponds With Photovoltaic (PV)-Based Energy Source

Introduction: Shrimp has great potential to be used as a business field in Indonesia. Especially in Parigi Regency itself, there are now many shrimp ponds that can be found because of the benefits obtained, so people are interested in making shrimp farming a livelihood. One of the main problems of shrimp ponds is pond water quality. There are several factors that affect pond water quality, namely water temperature, water pH, and water salinity, good pond water quality management can maintain quality standards and can increase shrimp yield and productivity Method: To facilitate the shrimp farmers, innovations need to be made in order to help the shrimp farmers manage their shrimp ponds, therefore using a remote water quality monitoring was system in shrimp ponds with photovoltaic (PV) based energy sources is expected to be an innovation in managing shrimp ponds, especially in monitoring water quality in shrimp ponds. The monitoring system designed using the NRF24L01 module as a remote communication module, at the research location the distance from the shrimp pond to the house is approximately 100 meters, so the tools that have been designed can facilitate shrimp farmers to monitor the shrimp pond Results and Disscussion: The results of testing the DS18B20 temperature sensor compared with a digital thermometer measuring instrument get an average error of 0.014%. The test results of the pH sensor compared to the pH meter get an average error of 0.026%. TDS sensor test results compared with the TDS meter get an average error of 0.04%. Conclusion: The temperature, pH, and salinity monitoring system uses transmitter and receiver modules, where the transmitter module reads and sends data to the receiver module wirelessly with NRF24L01. Using DS18B20 temperature, pH, and TDS sensors, as well as energy from photovoltaics, this system helps shrimp farmers monitor pond water quality remotely.

Influence of Slope Aspect and Vegetation on the Soil Moisture Response to Snowmelt in the German Alps

Snow, especially in mountainous regions, plays a major role acting as a quasi-reservoir, as it gradually releases fresh water during the melting season and thereby fills rivers, lakes, and groundwater aquifers. For vegetation and irrigation, the timing of the snowmelt is crucial. Therefore, it is necessary to understand how snowmelt varies under different local conditions. While differences in slope aspect and vegetation (individually) were linked to differences in snow accumulation and ablation, this study connects the two and describes their influence on the soil moisture response to snowmelt. This research focuses on the catchment of the “Brunnenkopfhütte” (BKH) in Bavaria, southern Germany, where an automatic weather station (AWS) has operated since 2016. In addition, soil temperature and moisture monitoring systems in the surrounding area on a south aspect slope on an open field (SO), on a south aspect slope in the forest (SF), and a north aspect slope in the forest (NF) have operated since 2020. On snow-free days in winter, the soil temperature at the SF site was on average 1 °C lower than on the open site. At the NF site, this soil temperature difference increased to 2.3 °C. At the same time, for a 1 °C increase in the air temperature, the soil temperature increases by 0.35 °C at the NF site. In addition, at this site, snow cover disappeared approximately one week later than on the south aspect slopes. Snow cover at the SF site disappeared even earlier than at the SO site. Finally, a significant difference in the soil moisture response was found between the sites. While the vegetation cover dampens the magnitude of the soil moisture increases, at the NF site, no sharp increases in soil moisture were observed.

Electro-mechano transduction of stacked triboelectric nanogenerator considering wave force: Modeling, validation and applications

Aiming at the low-frequency characteristics of ocean wave energy, triboelectric nanogenerators (TENGs) provide an efficient collection method. We propose a multi-layer contact-separation mode triboelectric nanogenerator (MS-TENG) based on a frequency-up mechanism to collect water wave energy. First, we study the effects of frequency rising and TENG unit stacking on the output of the MS-TENG. Experiments show that the short-circuit current of the MS-TENG with 12 layers stacked is 152.16 μA when the rotating speed is 60 rpm. Compared with a single TENG unit, the short-circuit current of the MS-TENG is increased by 6.35 times. Second, the hydrodynamic simulation method is used to study the force and energy capture efficiency of floating bodies with different shapes in water waves. The results show that the energy capture efficiency of the cylindrical floating body is 70.14 % higher than that of the spherical floating body under the same volume. Third, we use a cylindrical floating body to package the MS-TENG. In water tank experiments, when the load resistance is 4 MΩ, the peak power density of the packaged MS-TENG is 14.56 W/m3. In addition, with the help of the MS-TENG, we set up a wireless temperature and humidity monitoring system to realize the preliminary marine environmental monitoring.

Online Monitoring of the Temperature and Relative Humidity of Recycled Bedding for Dairy Cows on Dairy Farms

In large-scale dairy farming, the use of high-temperature-fermented dairy manure bedding instead of rice husk-based bedding and other commercial types of bedding is widely favored. Strip-stacking aerobic fermentation is the main production method of dairy manure bedding, but it has problems including unstable fermentation and the secondary breeding of pathogens. In this work, a multi-probe, integrated, online monitoring system for temperature and relative humidity was used for fermentation process optimization. The effects of the temporal and spatial distribution of fermentation temperature and relative humidity on the nutrient content curve and the moisture and ash content of manure bedding materials were systematically studied. The effect of the fermentation process on the retention rate of effective bedding materials (cellulose, hemicellulose, and lignin) was analyzed. The experiments proved that high-quality bedding material can be obtained through reasonable stacking fermentation. The fabricated bedding material has a total dry base content consisting of cellulose, hemicellulose, and lignin of 78%, an ash content of 6%, and a nutrient content of 17%. The obtained bedding material was produced to increase the bed rest rate and continuously inhibit the bedding bacteria content, keeping it at a low level for 5 days. This study proves that temperature and humidity monitoring can guide the optimization of the strip-stacking fermentation process of dairy manure and that it can be applied to large-scale farms to improve fermentation parameters.

Temperature Monitoring Efficiency With Internet of Things-Based Temperature Sensor Variations

This research was conducted in the lab. Automation to measure temperature by several temperature sensors monitored through Internet of Things (IoT) technology. The method used is a quantitative method with experiments. The temperature monitoring system with a variety of temperature sensors based on the Internet of Things (IoT) can work well. The difference in temperature measurements taken through the IoT simulation within 1 hour between the sensors used has a small value, an average of 0.07 Celsius. This means that the precession level of each sensor is relatively good. The need for calibration on the sensor in order to obtain the best measurement results. Noting the results of the above analysis, it is recommended that users conduct a more in-depth study to obtain a more appropriate (actual) value. This analysis can also be taken into consideration for users to develop IoT-based monitoring systems in the future.

Application of ZigBee Technology in Smart Soil Temperature and Humidity Control Systems

As global food security increasingly becomes a focus, challenges faced by Chinese agriculture are particularly prominent. This study introduces an intelligent monitoring and control system for soil temperature and humidity using ZigBee technology, aimed at enhancing agricultural production efficiency and crop yield. The system's core, equipped with an STC89C52 microcontroller and DHT11 temperature and humidity sensors, gathers data and wirelessly transmits it to a central control unit via ZigBee modules, which then automatically adjusts the agricultural production environment to ensure crops grow in the most ideal soil temperature and humidity conditions. Compared to traditional methods, this system achieves remote monitoring and precise control, providing an innovative solution for modern agricultural production. Experiments prove that the system not only improves control accuracy but also significantly enhances operational convenience and response speed, playing an important role in promoting the development of smart agriculture.

Design of Temperature Monitoring and Control System in Smart Hen Coop Based on Internet of Things

Every temperature error detected by the system would be notified to users by the Blynk application, and the system would attempt to stabilize the temperature in hen coop with a lamp and fan. Notification from the Blynk application is set to stop until the temperature returns to an ideal. The Blynk application is equipped with a reset button to reset the chicken age counter. This system used temperature and humidity sensors DHT22 to sense the temperature, which the data from the sensor output read by Arduino Uno. The data that Arduino Uno reads is sent to NodeMCU. Afterward, NodeMCU sent the data to the Blynk server; therefore, the Blynk application displayed the temperature and humidity data on the Blynk dashboard. This system is expected to facilitate users/breeders in monitoring the temperature in the hen coop. Therefore, users/breeders do not need to worry about chickens dying due to heat or cold stress. The waterfall method is used in this design of the system. This system was tested in a 70 x 70 x 130 cm sized hen coop and entirely tested the system each minute for 35 minutes.

Design and Implementation of Tire Pressure and Temperature Monitoring System for Hatchback and Multi-Purpose Vehicle Based on IoT

Tire Pressure Monitoring Systems (TPMS) have developed into an essential element in vehicles to improve safety and driving experience. In general, TPMS systems rely on special hardware to collect and transmit tire pressure data to the vehicle's on-board computer and this data can only be viewed by the driver and passengers in the vehicle. In this study, we developed a remote tire pressure and temperature monitoring system using IoT technology. The MQTT protocol facilitated communication between the cloud server and controller, while the system uses Docker container to simplify program integration. The results revealed the optimal standard deviation for tire pressure in hatchback vehicles to be 2.24, and for Multi-Purpose Vehicles (MPVs), it was 2.97. For tire temperature, the best standard deviation in hatchback vehicles was 1.93, compared to 1.05 in MPVs. This system effectively monitors tire pressure and temperature changes in real time, accessible remotely via smartphones and computers.

Enhancing energy efficiency in tyre pressure and temperature monitoring systems

This study addresses the pivotal challenge of enhancing power efficiency in tyre pressure and temperature monitoring systems (TPMS) for heavy vehicles and trailers. Employing field-programmable gate arrays (FPGA) and adaptive channel frequency hopping in bluetooth low energy (BLE) communication, the research focuses on mitigating power consumption issues specific to heavy vehicles with multiple tyres. The proposed solution incorporates strategic BLE channel blocking and adaptive frequency hopping on the FPGA platform to alleviate channel congestion and interference, ultimately reducing TPMS power consumption. The FPGA's adaptability tailors frequency hopping strategies to automotive TPMS nuances, optimizing channel selection and minimizing energy-intensive processes. Empirical results showcase a significant reduction in power consumption, with the TPMS operating at 100 MHz during active mode consuming 66 mW, dropping to 11 mW in sleep mode, and reaching 0 mW in hibernate mode for the majority of operational time. This research establishes a practical FPGA-based approach for power optimization in commercial TPMS, promising heightened reliability, safety improvements, and environmental impact reduction in the automotive sector.

Optimizing gula apong production with an IoT-based temperature monitoring system

<p>Determining the quality of <em>gula apong</em> is crucial to optimizing its production, with cooking temperature being a key factor affecting both taste and shelf life. The <em>gula apong</em> industry faced challenges due to the lack of reliable real-time temperature monitoring methods during the cooking process. Traditional approaches were inefficient and inaccurate, leading to difficulties in maintaining consistent product quality and meeting market demands. This highlights the necessity of monitoring the temperature throughout each cooking process. This research aims to develop an internet of things (IoT)- based cooking temperature monitoring system to enhance quality control measures in the production of <em>gula apong</em>. The IoT prototype collects temperature data from the thermocouple sensor, then transmits it to cloud storage through a Wi-Fi communication network, utilizing the Node-RED platform for data processing and analysis. Data obtained from the on-site measurement shows that the optimal temperature for producing standard-quality <em>gula apong</em> is approximately around 165 °C. The recommended boiling temperature for Nipah sap is 140 °C. This IoT system can reduce the cooking time of <em>gula apong</em> to 3 hours from the traditional 4 to 6 hours. Utilizing the data acquired from this study helps the producers not only maintaining the quality of <em>gula apong</em> but also reduce the cooking time and cost.</p>

Website-Based Monitoring System for Methane (CH4) Concentration, Humidity, and Temperature

Abstract The research developed a monitoring system that focuses on the development of a system and the acquisition of its readings into a simple website. This research was conducted in an effort to obtain data that can be used for managing methane gas pollution in the environment. Methane gas (CH 4) is a natural gas consisting of one carbon atom and four hydrogen atoms. Methane gas is one of the greenhouse gases that contribute to global warming, while humidity and temperature can increase or decrease methane gas productivity. Therefore, in this research, a monitoring system was created for methane gas concentration using TGS2611 sensor, humidity and temperature using DHT11 sensor through the creation of a chamber connected to test materials such as cow dung digesters and tofu wastewater as a source of methane gas production. The results obtained indicate that, in the development of the monitoring system as a measuring tool, it successfully detects the concentration of methane gas, humidity and temperature for each test material using calibration through characteristic equation V = 0,5591 ln(n) − 2,2657. For data acquisition in the form of methane gas concentration parameter readings by the TGS2611 sensor, humidity and temperature by the DHT11 sensor to the ESP8266 microcontroller to be displayed on the serial monitor, LCD, and the website that has been created in real-time. To display the data acquisition of the monitoring system, each component of the system is connected. Starting from software, hardware, and test materials. Data acquisition begins with sensor readings by ESP8266 through a program from Arduino IDE displayed on the serial monitor and LCD. Once connected to wifi or a hotspot and the data is successfully sent, the data will be checked by notepad++ and entered into the phpMyAdmin website database for storage. From this database. The data will then be displayed on the website that has been created in real-time. Additionally, humidity and temperature affect the increase and decrease in methane gas concentration productivity.

Real Time Monitoring of Temperature And Humidity Using LabVIEW and ML

Abstract: This project presents a Real-Time Temperature and Humidity Monitoring System built on LabVIEW, featuring ML predictive analytics. It facilitates real-time data collection from diverse sensors, ensuring precise environmental monitoring. The ML algorithms within the system forecast future temperature and humidity trends, aiding proactive decision-making. Users enjoy an intuitive graphical interface for visualizing data, analysing historical trends, and receiving alerts for threshold variations. Additionally, the system provides remote monitoring, data logging, and reporting, enhancing its usability and accessibility. This integrated solution caters to the crucial requirement for accurate environmental monitoring, with applications spanning industries like manufacturing, agriculture, and climate control, ultimately enhancing efficiency and decision-making in these sectors.

Simulation and on-line monitoring using optical fiber Bragg grating sensors of temperature history during laser-assisted automated fiber placement

Automated fiber placement (AFP) in situ consolidation (ISC) of thermoplastic composite possess the potential to reduce manufacturing costs and improve manufacturing efficiency. The properties of composite manufactured by the ISC are affected by several mechanisms including polymer degradation, crystallization, intimate contact, polymer healing and void dynamics. All these mechanisms are directly affected by the temperature history. Consequently, the control and accurate measurement of temperature history during ISC are particularly important for improving the properties of composite. In this study, a simplified three-dimensional transient heat transfer model was established. The effect of tool temperature and placement speed on the temperature history and peak temperature were predicted. Simultaneously, an online temperature monitoring system was built and the optical Fiber Bragg Grating sensors (FBGS) was used to measure the temperature history. The results indicated that the predicted results of the model were consistent with the measured results, the error was below 8%. In addition, the temperature history of layers was significantly affected by the tool temperature and placement speed. The temperature of the layers decreased to near the tool temperature after cooling, and a higher tool temperature increasing its peak temperature because of the reduce of the cooling rate. On the contrary, an increase in placement speed will reduce the peak temperature of the layers.

Smart Gas Leakage Detector Using Arduino Gas Sensor

This project is carried out using the Methane Quality (MQ-2) sensor to detect Liquefied Petroleum Gas LPG, smoke and Carbon Monoxide (CO) leakage in the environment. The microcontroller used was an Arduino Uno for controlling the environmental temperature monitoring system. The results obtained from the sensor would be displayed on the 16x2 i2c Liquid Crystal Display (LCD). The new system with an Arduino microcontroller and MQ2 consists of the hardware design which includes the device design, as well as the software design which consist of the Arduino source code. They also consist of Internet of Things (IoT) enabled sensors, which work as a real-time indicator. After testing, we have 17.7% failure and 82.3% accuracy.

Development of an automated monitoring system for soil moisture and temperature in smart agriculture to enhance lettuce farming productivity based on IoT

Development of an automated monitoring system for soil moisture and temperature in smart agriculture to enhance lettuce farming productivity based on IoT

ARDUINO AND IOT-BASED OBSERVATION METHOD FOR MONITORING TEMPERATURE, HUMIDITY, AND AIR PRESSURE OF ELECTRON BEAM ACCELERATOR’S ROOM

The monitoring system for temperature, humidity and air pressure in the electron accelerator’s room has been designed. This research is based on operational environmental monitoring procedures in the accelerator room that must be carried out before the accelerator operates. We offer a simple and adaptable monitoring solution for the electron accelerator room. Parameter data can be monitored using a smart device. Operators do not need to go into the accelerator room to carry out environmental monitoring. The proposed system uses Arduino technology and the Internet of Things (IoT). Data acquisition programming was performed using Arduino IDE and ESP8266 NodeMCU as microcontrollers. The microcontroller then transmits temperature, humidity, and pressure data parameters to the cloud server, where they are then displayed on the smart device via the Blynk app. The results show that the system that has been designed is able to read and store parameter readings on the sensors used and the system has been able to make decisions in the form of notifications about whether the Electron Beam Machine is ready or not to be operated.