SD Card Research Articles

Performance of low cost sensor temperature logger in double jacket reactor vacuum distillation

Heat transfer occurs due to the difference in temperature between the system and its surroundings. The effect of temperature can affect various aspects of the refining process, including efficiency, selectivity, reaction kinetics, and the quality of the final product. This study aims to analyze heat transfer in a double-jacket reactor by measuring temperature data taken using a temperature data logger system. Prototype low cost-effective temperature monitoring for double jacket reactor vacuum is this system integrates an Arduino Mega 2560, a type K thermocouple, amplifier MAX 6675 module, and an SD card data logger to measure and record reactor temperature for 30 minutes. The temperature data obtained is used to calculate the heat transfer and analyze the heat transfer characteristics of the reactor. Heat transfer analysis based on measured temperature data is able to provide insight into the characteristics of heat transfer in the observed system and can identify hot spots and heat transfer energy in the system. Thus, the temperature data logger used in the double jacket reactor in the vacuum distillation system can produce accurate data and information, and this system has broad application potential in temperature monitoring in various fields.

Sistem Pembatas Pembelian BBM Menggunakan RFID (Radio Frequency Identification) dan Arduino Uno

The dwindling availability of fuel (fuel oil) in Indonesia, Pertamina is conducting a trial run on limiting purchases of fuel. Payment transactions using a card with RFID (Radio Frequency Identification) technology are one type of non-cash transaction that can be used as an alternative payment method. In this study, we will discuss the use of RFID tags to complete purchases on BBM with a predetermined number of calculations. This tool uses Arduino Uno as its microcontroller to process data received from RFID tags and RFID readers to read the value of the fuel purchase balance, which then the buyer writes down the nominal purchase using the programmed 4x4 keypad by limiting purchases to no more than a predetermined nominal in one day. This tool uses the YF-S401 flow meter sensor to determine the volume of fuel flowing in accordance with the nominal previously inputted, the data will be displayed via a 16x2 LCD in real time using the RTC DS1307 to store month, date and time data stored in the module SD card with all data obtained in measurements.

Development of an Arduino-based Multi-Channel Temperature and Relative Humidity Data Acquisition System for Domestic and Industrial Applications

Losses incurred during postharvest processes of food and other agricultural products in the rural and some urban areas of West African countries have been attributed to poor thermal conditions of the indoor air. The quality of these products at storage or after thermal processes such as drying, cooking, frying, etc. has been identified to be majorly dependent on the temperature and humidity of the air. The objective of this study was therefore to develop a low cost Arduino based multi-channel temperature and humidity data acquisition system for domestic and industrial applications. It comprises an ATmega 328P controller type, fourteen (14) DS18B20s temperature sensors, and six (6) DHT22 humidity sensors. The system was configured and programmed to log in readings every 30 minutes (30 min) on the SD card or through the Bluetooth module in Excel format directly into the computer. The results from the experiments conducted with this data acquisition system demonstrated reliability because they were within the reasonable and acceptable range for commercial logging devices.

Arthrospira platensis growth control system in semi-industrial environment

The paper proposes the design of a device based on the Arduino platform for obtaining data on the biomass of micro-algae, the temperature of the cultural suspension and the irradiation of the pool surface during semi-industrial cultivation of A. platensis. The task was to offer the simplest possible design, consisting of widely available components. In the course of the work, sensor designs were developed, calibration curves were taken, and correction factors were calculated that are necessary for using this device. The device includes a temperature, irradiance and optical density sensor connected to the Arduino Mega platform. The data from the sensors are displayed on the LCD screen and recorded on the Micro SD card.

Wireless internet of things solutions for efficient photovoltaic system monitoring via WiFi networks

<div align="center"><span>The imperative for sustainable energy production has necessitated the significant expansion of renewable energy sources, particularly photovoltaic (PV) systems. The utilization of real-time monitoring and data analysis is imperative to enhance the efficiency and performance of photovoltaic systems. This abstract presents developing and deploying a wireless monitoring system for a photovoltaic system. The system utilizes a Raspberry Pi device connected to a WiFi network and an SD card for data storage to enable remote monitoring and management of PV systems. The proposed monitoring system comprises a Raspberry Pi equipped with sensors to measure various parameters such as voltage, current, temperature, and the ambient conditions of the solar panels; the monitoring system can be remotely accessible through the wireless capabilities of the Raspberry Pi, which are activated by establishing a connection to an existing WiFi network. The proposed configuration facilitates the placement of the monitoring station in any desired location, hence eliminating the requirement for intricate wiring connections. These real-time data enable solar system managers to quickly identify anomalies, anticipate breakdowns, and optimise energy production. The paper presents a wireless monitoring system with a cost-effective and scalable solution for monitoring photovoltaic systems.</span></div>

ZX Fusion: A ZX Spectrum Implementation on an FPGA with Modern Peripherals

The ZX Spectrum was a popular 8-bit home computer by Sinclair Research in the 1980s. Even though some of these computers may still work, the audio tapes, the TV with an analog tuner, and the micro-switch joystick that were used with the original ZX Spectrum are outdated and hard to find in good working order or to replicate. As many other old closed systems are also very difficult to update to support modern peripherals there is a necessity to provide a methodology to adapt such systems to support new peripherals while being compatible with existing software. This implementation is a means by which to validate the methodology before applying it to a physical system. The work proposed in this paper focused on recreating a ZX Spectrum+/48K computer and interfacing it with modern peripherals on an FPGA. This was accomplished by adding a co-processor to assist with the control of the more complex peripherals. Otherwise, the original system would require complex architectural changes and would perform poorly due to the low performance of the Z80 CPU. This work distanced itself from previous works on emulating a ZX Spectrum, as it focused on the use of different upgraded peripherals and the use of a NIOS II soft processor as a co-processor to manage the SD card accesses and save-state functionality. A demonstration of the proposed modernized architecture was made by successfully running a diagnostics ROM and playing original ZX Spectrum games from an SD card for games with a PS/2 keyboard and a pair of joysticks.

Community Farm monitoring toolkit: Design and implementation of a Low-cost tool for sustainable community based agricultural projects in Africa

Nowadays sustainable agriculture exploits new technologies such as internet of things (IoT) mixed with community engagement and participation that represent a great potential for addressing sustainability goals at large. This paper presents a low-cost community-based control system for remote monitoring of surrounding parameters and other sustainability indicators such as quantity of yearly harvests, yearly local employments and so on with the use of sensors. The hardware system includes an air quality sensor, an air humidity and temperature sensor, a soil moisture sensor, a real time clock providing the time and an SD card to record the collected data. The designed tool gathers both data from sensors and incoming data from community through SMS which are therefore processed and forwarded to a specific online dashboard to support community decision-making, thus forming the community control system feedback loop. Experimental results from the considered agricultural community project show that the system works well and could be used in other similar and/or larger scale projects.

DEVELOPMENT OF DC-DC BUCK CONVERTER FOR SOLAR PANEL ENERGY STORAGE THROUGH LOAD OPTIMIZATION AND FEEDBACK CIRCUIT

Solar panels are crucial components in converting sun radiation into electrical energy through the photovoltaic effect. A solar panels cannot be connected directly to the load due to its low energy conversion efficiency and low output voltage. One of the methods used to control solar cells to operate efficiently at their maximum power point is MPPT. In this paper, we design a DC-DC converter by modifications of the Butterworth filter circuit and feedback circuit in the MPPT system for storing solar panel electrical using the Hill Climbing (HC) method. The device consists of a DC-DC buck converter circuit, two pieces of INA219 sensors, a DS18B20 temperature sensor, a MAX44009 light intensity sensor, a SD card module and a DS3231 RTC. The DC-DC buck converter circuit simulation is carried out to determine the optimal load. The load optimization was conducted by analyzing the AC simulation using Ltspice software. The magnitude of the output voltage ripple in nine different loads was observed. From the simulations performed, it was found that the 50 Ω load has an output voltage ripple of 8.96 mV and is smaller than the other loads. The main DC-DC buck converter circuit is designed using a butterworth low pass filter with a cut-off frequency of 1000 Hz (R = 50 Ω, L = 33.8 mH and C = 750 nF) and a feedback circuit with a cut-off frequency of 500 Hz is added. From the prototype measurement, it was found that the average output power was 3249,7 milliwatts and the average input power was 4779 milliwatts, thus the average efficiency was 68%. With these results, the DC-DC converter circuit configuration is suitable for use in electrical energy storage systems from solar panels that have high efficiency.

Digital forensics in healthcare: An analysis of data associated with a CPAP machine

The need for digital forensic services across all sectors is not a new concept, nor is the increasing demand seen globally. However, the devices on which we perform digital forensics have changed and continue to evolve. For each device new approaches need to be developed or adapted to facilitate the secure preservation and analysis of the data it contains. The healthcare sector has seen particular adoption of a range of devices, from traditional through to cutting edge. The Covid-19 pandemic facilitated the need for a more boundary-agnostic level of care for patients, and medical devices are becoming increasingly more interconnected to facilitate remote care. This presents challenges in that devices are no longer “secured” in medical premises and will often be found in patient's homes, making them more exposed to attack, but also in a position to record significant amounts of personal data. The integration of information technology in medical environments has influenced the need for the development of a digital forensic process to perform analysis on medical devices. One such device is a continuous positive airway pressure (CPAP) machine, used by patients who suffer from Obstructive Sleep Apnea (OSA). It is estimated that 3-9% of the world's population suffer from this disorder, the normal medical treatment is the use of some form of CPAP machine. The research undertaken focuses on the ResMed AirSense 10 CPAP machine and a complete forensic postmortem analysis of the data contained and recorded by the device. The application of digital forensics to a traditional medical device, such as a CPAP machine, requires an adapted version of digital forensics, but in general the same tools and processes can be used. Through the analysis conducted, all patient data was located on a removable FAT32 formatted SD card, allowing the recovery of specific medical information about the device and personally identifiable information about the patient. The recovered data was then visualised using a variety of tools and systems. Information that can be derived from the visualisations include a sequence of events, to some extent how the device was operating, and the clinical information recorded on the device.

Power Consumption Minimization of a Low-Cost IoT Data Logger for Photovoltaic System

This paper introduces an innovative IoT-based data logger for photovoltaic (PV) system monitoring, emphasizing low power consumption and affordability. The system comprises a PV panel, a charging controller, and a backup battery, focusing on monitoring their voltages and currents through a network of voltage and current sensors. Data is stored on an SD card and displayed in real-time on a web server. The FireBeetle 2 ESP32-E microcontroller, chosen for its efficient deep-sleep mode power management, is central to the data logger's design. This study employs several low-power strategies, notably reducing supply voltage and CPU frequency to decrease power consumption significantly. A data buffering mechanism stores sensor readings in the microcontroller's flash memory, transferring them to the SD card hourly to balance power efficiency and data security. Wi-Fi connection intervals are optimized to 45 seconds, balancing power use and system monitoring frequency. The data logger averages a power consumption of 122.78 mW and demonstrates its efficacy against the commercial DI-145 model. Priced at C$ 55.05, the system is both cost-effective and scalable, capable of monitoring multiple PV panels and batteries, reducing per-unit costs. The study underscores the successful integration of affordability, low-power operation, and efficient monitoring in a PV system data logger, showcasing its potential in future renewable energy research.

Analisis Sharing Data Wemos D1 R32 Menggunakan Web

The advancement of technology has increased the demand for media file storage. One common storage system used today involves the use of cables or devices that need to be connected to other devices. However, this method is not efficient for simultaneous file sharing, especially when many people want to access the same files. This research utilizes the Naive Bayes algorithm and Quality of Service method for testing and SPI (Serial Peripheral Interface) as the serial communication on Wemos D1 R32 with its sensors, in order to address this issue. The research is conducted through stages of literature review, design, testing, implementation, and testing using Wemos D1 R32 as the main platform along with supporting components such as a micro SD card reader module, an LCD OLED display, a micro SD card, and a battery. In the testing phase, conducted three times with each tested file format using the Naive Bayes algorithm in our system, the evaluation results are as follows: Very Good 86.66%, Good 13.33%, Moderate 0%, and Poor 0%.

Development of an Inertial Measurement Unit (IMU) with datalogger and geopositioning for mapping the Earth’s magnetic field

The Earth’s magnetic field is used in various navigation systems, but this field has a dynamic behavior that can be affected by different physical factors in local environments. These factors can pose risks to navigation systems and at the same time be a signal of a phenomenon that needs to be investigated, such as mineral concentration or the presence of interference from electrical equipment, among others. For that reason, in this project, this system was designed and integrated using a low-cost, military-grade magnet inductive magnetometer, which is integrated into two Inertial Measurement Units to corroborate the movement data, and at the same time a geopositioning system to georeference the sensor measurements. The information is managed by an MCU, which also stores data on an SD card. The system includes a lithium battery management system to provide more than an hour of autonomy. Wireless communication systems are intentionally avoided to prevent interference, and an infrared transmission LED is included instead, in case the real-time transmission is necessary. The results show that the proposed system allows for obtaining maps of magnetic field intensity in open spaces, and this information can be used to determine regions with anomalies.

Acoustic Wave Based Forest Fire Extinguisher and Detection Using Machine Learning

Worldwide, forest fires are a serious hazard to people, property, and the environment, needing creative approaches to early detection and prompt control. In order to establish an intelligent forest fire control system, this research introduces a cutting-edge methodology that blends conventional fire detection techniques with machine learning and cutting-edge technology. To find fires in a forest, we use flame sensors. The flame sensor informs a microcontroller when a fire is found. We offer a revolutionary form of fire suppression using Sonic Fire Extinguisher technology, which puts out flames by emitting high-frequency sound waves, as opposed to traditional fire suppression methods that use water or carbon dioxide. This strategy offers a safer and more environmentally friendly fire suppression technique. The technology incorporates machine learning to improve the speed and accuracy of fire detection. A SD card for sound file storage is included with the ARDUINO UNO microcontroller. In addition, the microcontroller is wired up with an amplifier and speaker. The microcontroller uses machine learning techniques to analyses the characteristics of the fire, such as size and intensity, and chooses the best sound wave frequency for suppression when the flame sensor detects a fire. This device can put out fires more effectively than conventional techniques and can adjust to various fire circumstances. The device can tailor the produced sound waves for effective fire suppression by fusing real-time data from the flame sensor with machine learning insights. This novel strategy improves the safety from forest fires while simultaneously minimizing the negative ecological effects of fire management activities. A promising approach to protecting priceless natural resources, people's lives, and property from the destructive impacts of forest fires is the combination of machine learning and Sonic Fire Extinguisher technology. This research Endeavour marks a significant advancement in the practice of finding fires and extinguishment, allowing a more environmentally responsible and sustainable method of managing forest fires.

Assessing efficacy of cellular transmission technology in camera trapping for wildlife research

AbstractCamera traps are an important noninvasive tool used by scientists to monitor wildlife efficiently and at reduced costs. New camera trap features improve performance and encourage increased use by researchers and the public. Cellular transmission of image data, which provides users the ability to digitally receive images instead of retrieving or downloading images in the field is a useful new feature. Cellular data transmission has 2 key benefits for wildlife research in that it reduces travel time required for downloading image data and the uncertainty involving storage capacity of SD cards and battery life, and cellular transmission allows for near real‐time analysis of images, which could redistribute the time usually devoted to processing a large data set when the memory card is retrieved. Despite potential benefits, cellular transmission technology in camera traps is still new and questions remain about its reliability. Our objective was to determine the efficacy of cellular transmission technology in wildlife research by designing a camera trap study as part of a senior‐level class (Wildlife Management Applications and Planning; NREM 4522) project at Oklahoma State University. We used ArcGIS to generate a stratified random sample of trap locations, deploying five cellular transmission camera traps in open grassland and five in closed canopy forest areas from 5 September to 5 October 2021. We monitored the number of transmitted images each day online, and after camera trap retrieval, we compared the number of transmitted images to those stored on the memory card to determine transmission efficiency. Our data indicated the majority of the images taken each day were transmitted successfully; however, transmission efficiency (i.e., number transmitted divided by total number taken by the camera trap) tended to be lower in forested areas (47%) compared to open grassland (86%). Though cellular transmission technology shows promise, the combination of cellular signal, landscape features, and transmitted data quality may limit the effectiveness of cellular transmission technology for near real‐time data analysis. Based on our results, we recommend that researchers consider advantages and disadvantages of cellular transmission when designing studies and note that researchers may need to adopt an adaptive approach or conduct pilot testing that includes quantifying the transmission functionality.

Design and Development of an Automatic Angklung Robot Based on Microcontroller

The angklung is a traditional musical instrument from West Java, Indonesia. It can be played both individually and in groups. Playing the angklung requires precision in terms of tempo, rhythm, pitch, and beats to ensure that the music aligns with the intended song and is enjoyable to listen to. Therefore, not everyone can play the angklung, as it demands skill to achieve the right tempo, pitch, rhythm, and beats. To address this issue, a solution was developed, which involved creating a system and device capable of playing the angklung automatically. In this research, a system was designed to move the angklung automatically, simulating a robot, and it is referred to as the "angklung robot." This angklung robot consists of a set of 16 notes, and the electrical components used include an Arduino Mega 2560 as the microcontroller, a 16-channel relay module, motor drivers, a micro SD module. To play a song, the device uses a score file that has been converted and stored on a micro SD card, adjusting the tempo to match the desired Beats Per Minute (BPM).Through several experiments, the angklung robot successfully played 10 pre-composed songs with a 100% accuracy rate. According to the opinions of 10 music enthusiasts who were surveyed, the level of accuracy in which the angklung robot played the songs was 90%.This innovation brings automation to the traditional art of playing the angklung, making it accessible to a wider audience and ensuring consistent and precise musical performances.

Heart condition determination based on MET value to NYHA Classification and abnormal ST segment identification

Cardiovascular diseases have always been among the top causes of death. Thus, there were variety of research focuses on cardiac stress test and on self-stress test as well. However, the portable device existed for heart monitoring were still insufficient where most device are for fitness monitoring rather than functional capacity. Thus, this paper determines heart condition based on New York Heart Classification (NYHA) for The Rockport Walking Fitness Test (TRWFT). TRWFT gave out parameters to calculate maximum oxygen consumption (VO2max) to find metabolic equivalent (MET) value. The MET values were compared with NYHA functional capacity classes. Hence, the comparison simplified the heart condition to the urgency to visit hospitals. Plus, ST segments of MIT-BIH ECG database were extracted and assessed for abnormality. Accordingly, a mobile application was developed. The prototype is built using Genuino 101 microcontroller, an AD8232 ECG module with leads to sense heart pulse, and a SD card module. Meanwhile, simulation test on the prototype shows that the prototype succeeds in produce the same values with manual calculation and managed to assess ST segments as programmed. In conclusion, a prototype to demonstrate the implementation of TRFWT and prediction of cardiac condition based on MET value is successful.

Remote Data Acquisition System for Photovoltaic Water Pumping System in Sukkar, Pakistan

Access to high-speed internet connectivity is limited in Sukkur, Pakistan, making alternative communication technologies essential for real-time monitoring and control of photovoltaic (PV) water pumping systems. This research paper presents the design, implementation, and evaluation of a GSM-based remote data acquisition and logging system for a PV water pumping system in Sukkur. Leveraging abundant sunlight in the region, the proposed system utilizes 2G GSM technology for communication between the PV system and the remote monitoring station. A network of sensors captures key parameters, and the acquired data is processed, stored, and transmitted using 2G GSM, enabling remote access and real-time monitoring from any location with GSM coverage. The implemented system incorporates an Arduino microcontroller for core operation and employs an SD card for data logging. Real-time data logging allows for detailed tracking and analysis of system performance, facilitating troubleshooting and optimization. Data stored on the SD card can be transferred to a computer for further analysis using data analysis software or custom applications, providing meaningful representation of trends and insights into system operation. The system also features an OLED display for real-time feedback on essential parameters, including solar irradiance, water level, and pump status. Furthermore, the integration of user prompts and GSM communication enables remote monitoring and control, empowering users to inquire about system status and remotely activate or deactivate the pump through SMS commands. The system offers a robust and adaptable solution for efficient management and maintenance of the solar-powered water pumping system in Sukkur, Pakistan.

The Sensor Occlusion SEN0257 on the Infusion Device Analyzer 2 Channel with TFT Display ensures high accuracy in detecting occlusions.

Syringepump and Infuspump function to provide drugs or fluids that are carried out directly and continuously for a certain period of time through a blood vessel. Often encountered problems of blockage or occlusion in the use of infusion pumps and syringe pumps. Occlusion in the infusion device causes the incoming drug fluid to not flow constantly. Occlusion limit set at 20 Psi according to ECRI. To ensure this, proper calibration is required at least once a year. The purpose of this research is to analyze the accuracy of the pressure sensor on the Occlusion measurement on the Infusion Device Analyzer 2 Channel showing TFT. This study has 2 channels so that it can calibrate 2 tools simultaneously. The design of this module uses a Water Pressure Sensor to measure occlusion and a solenoid valve for pressure simulation. When the sensor is depressed, the sensor detects the pressure and is processed by the Arduino. The pressure results are then displayed on a 7-inch TFT LCD in the form of graphs and numbers in real time and stored on the SD card.

Monitoring of electricity generation from exhaust waste heat and wireless data recording from a mobile phone in real driving conditions of a vehicle.

In this study, a system is designed to generate electrical energy from the exhaust waste heat of vehicles using a thermoelectric generator. Electronic hardware that can communicate wirelessly, firmware, and mobile software specific to the system have been developed to control and monitor this system. The system comprises hexagonal aluminum components, thermoelectric generators, a cooler, sensors, software, and electronic hardware. The easily removable hexagonal modular aluminum component is designed to transmit heat from the exhaust pipe to thermoelectric generators. It used a thermoelectric generator (TEG-SP1848) on each edge of this hexagonal component and a heatsink to cool the generator. The voltage and current values of the electrical energy produced in the observations made under real driving conditions are recorded on the SD card on the system. In addition, system-specific mobile software has been developed by the work team. With this software, the system can be controlled, as well as visualizing the instantaneous parameters of the system. According to the results obtained from the test drives, electrical energy was obtained at a maximum voltage of 9.8 V and a current of 0.32 A. This electrical energy from the exhaust waste heat can be stored in the vehicle's existing battery. In this way, since the alternator used for the vehicle's electricity generation will be activated less, fuel savings will be achieved in the engine, and harmful exhaust emissions will be reduced. In addition, the electrical energy obtained by this method can be stored in an external battery independent of the vehicle battery and used for various purposes. In contrast, the vehicle is stationary or has a portable battery.

BLUETOOTH ENABLED WALKING CANE INTEGRATED WITH AUDIO ASSISTANCE

We are inventing this assistive aid to help the visually impaired persons to fulfil their essential activities. Walking cane integrated with GPS, Bluetooth, camera, ultrasonic sensor, SpO2 sensor, pulse sensor. Camera is fixed in the walking cane for object recognition and outdoor navigation. The ultrasonic sensor is attached in the walking cane for identify the obstacles. GPS module is fixed for tracking the location and the destination pathway instruction. SD card is inserted into the walking cane to store their daily routine places. The physiological parameters like blood oxygen level and heart rate are detected by SpO2 sensor and pulse sensor respectively. . Keywords :(Bluetooth, GPS, camera, pulse sensor, SpO2 sensor, ultrasonic sensor)