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The key requirement for electric vehicles is efficient braking. The objective of this study is to provide a detailed description of the regenerative braking system utilizing various power flow regulators. This study utilizes a buck-boost type Boost Converter. There are two methods employed to modify the voltage derived from the fluctuating input produced during regenerative braking: one to decrease it and the other to boost it. Subsequently, a voltage sensor detects the resulting output voltage, which is then regulated using an Arduino microcontroller. The examination findings indicate that the buck-boost converter performs well, maintaining an output voltage within the range of 39- 40 volts. This allows it to function well even when there are fluctuations in the input voltage. The voltage value can be utilized for the purpose of charging a battery for a 36 Volt electric motor. The findings demonstrate the efficacy of utilizing a Buck-Boost Converter regulator. Furthermore, it could charge the battery within a span of 8 seconds, making it a viable option for electric vehicles as an alternative to regenerative braking for battery recharging. [ABSTRACT FROM AUTHOR]

To measure the electrical parameters of 25Hz phase-sensitive track circuit, a testing instrument with STM32 microcontroller as the control core is designed. It mainly uses the method of root mean square and fast Fourier transform to measure the effective value of the coil voltage of the track relay and the phase difference between the coil voltage of the track relay and the local coil voltage. The voltage waveform and calculation results are displayed on TFT-LCD, which has the advantages of simple structure, fast processing speed and high measurement accuracy. It is convenient for the daily detection and fault diagnosis of 25Hz phase-sensitive track circuit. [ABSTRACT FROM AUTHOR]

A significant attention has concentrated on systems with "hidden attractors" in recent years. The aim of this work is to study an oscillator displaying "hidden attractors". The oscillator has all nonlinear terms but no equilibrium. The oscillator exhibits attractive dynamics such as chaos, bubble bifurcation, symmetrical attractors, and boosting attractors. Oscillator's feasibility is verified by a microcontroller. Utilizing the oscillator for biomedical image encryption illustrates its application. In addition, the adaptive control is designed for the oscillator. [ABSTRACT FROM AUTHOR]

This research paper focuses on the application of fuzzy logic control in the high-frequency switching control of SEPIC DC/DC converters and three-phase inverters for photovoltaic systems. The research is separated into two distinct sections. The first part entails the design and development of a prototype mechanism for a single-ended primary-inductor converter (SEPIC), which is utilized to manage the input voltage from the PV system. The operation of this SEPIC DC/DC converter incorporates real-time fuzzy logic control principles and methods. The second part involves the design and creation of a three-phase inverter mechanism (SVPWM) responsible for driving a three-phase induction motor. In a similar manner, fuzzy logic control principles and methods are independently employed for the operation control of this three-phase inverter. Both control mechanisms are integrated with the mathematical model of MATLAB/Simulink program and synchronized with the TMS320F28379D microcontroller in order to effectively regulate their respective functions. The evaluation and experimentation of the developed mechanisms demonstrate the successful regulation of input and output voltages for the SEPIC DC/DC Converter, as well as the efficient control of the three-phase induction motor's speed, torque, and power using the three-phase inverter. [ABSTRACT FROM AUTHOR]

This research aims to find out how effective the IoT microcontroller training kit learning media is and to analyze the effect of using the IoT microcontroller training kit compared to the common microcontroller training kit on students' cognitive learning outcomes in learning microcontroller and microprocessor programming techniques. The normalized gain method was used to determine the effectiveness of the IoT microcontroller training kit learning media. The ANOVA method was used to determine the effect of using the IoT microcontroller training kit and common microcontroller training kit on the average student cognitive learning outcomes. The research results show that the IoT microcontroller training kit learning media has a normalized gain value of 59.62% in the effective enough category. The average cognitive learning outcomes of students using the IoT microcontroller training kit are greater than those using the regular microcontroller training kit, according to the results of the study using one-way ANOVA, where the p-value is less than the a value of 0.05. This IoT microcontroller training kit can be used to improve students' cognition regarding microcontroller learning in vocational schools. [ABSTRACT FROM AUTHOR]

This research paper aims to design an energy-efficient surveillance camera utilizing the ESP32-CAM module, incorporating Wi-Fi connectivity, and using 3D printed custom case made from ABS plastic. The central goal is to determine the most effective video streaming protocol for transmitting real-time data to a web-based interface that manages the camera. The camera prototype is developed through a technical feasibility study and prototype construction methods, with a primary focus on assessing power consumption across various protocols including HTTP, RTP, RTSP, and WebSocket. The findings indicate that WebSocket emerges as one of the most optimal and power-efficient protocols for streaming video from the ESP32-CAM web server to a client device. This superiority arises from WebSocket's browser-based approach, enabling full-duplex communication through a single TCP connection, thereby facilitating real-time interaction between the client and server. [ABSTRACT FROM AUTHOR]

Home automation represents the integration of computerized or automatic control into various commonplace electrical and electronic systems within residences. Beyond resolving lighting concerns, this sophisticated technology paves the way for a centralized home entertainment system and offers comprehensive mastery over home security. Given the rapid escalation in resource consumption, there exists a compelling inclination to conserve our resources through every feasible means. A significant contributor to energy wastage is the absence of remote control and access to appliances. This project unveils a user-friendly home automation system, operable wirelessly via wifi on a smartphone. The Firebase real-time database, a cutting-edge IoT solution, serves as the conduit between the hardware and the mobile application. Facilitating automated control of up to eight appliances through a mobile app, the system also incorporates sensors that enable gas leak detection within the home. [ABSTRACT FROM AUTHOR]

Sensor networks are regularly sent to monitor certain physical properties that run in length from divisions of a second to many months or indeed several years. Nodes must advance their energy use for expanding network lifetime. The fault detection of the network node is very significant for guaranteeing the correctness of monitoring results. Due to different network resource constraints and malicious attacks, security assurance in wireless sensor networks has been a difficult task. The implementation of these features requires larger space due to distributed module. This research work proposes new sensor node architecture integrated with a self-testing core and cryptoprocessor to provide fault-free operation and secured data transmission. The proposed node architecture was designed using Verilog programming and implemented using the Xilinx ISE tool in the Spartan 3E environment. The proposed system supports the real-time application in the range of 33 nanoseconds. The obtained results have been compared with the existing Microcontroller-based system. The power consumption of the proposed system consumes only 3.9 mW, and it is only 24% percentage of AT mega-based node architecture. [ABSTRACT FROM AUTHOR]

Technology can have a positive impact on various fields, including agriculture. By integrating technology, agricultural practices can be automated, specifically in plant maintenance management systems, simplifying the process of growing and caring for plants. In the context of automated plant maintenance and growth, the Green House method incorporates factors such as humidity, temperature, and illumination. To facilitate faster and more effective plant cultivation and care, this study proposes an intelligent plant system that aims to promote plant growth. The data collected by connected sensors is gathered and interpreted using Arduino, enabling the generation of recommendations for greenhouse plant maintenance. The sensor's output properties demonstrate its capability in supporting the objectives. [ABSTRACT FROM AUTHOR]

With the increasing development of EVs, the energy demand from the conventional utility grid increases in proportion. On the other hand, photovoltaic (PV) energy sources can overcome several problems when charging EVs from the utility grid especially in remote areas. This paper presents an effective photovoltaic stand-alone charging station for EV applications. The proposed charging station incorporates PVarray, a lithium-ion battery representing the EV battery, and a lead-acid battery representing the energy storage system (ESS). A bidirectional DC-DC converter is employed for charging/discharging the ESS and a unidirectional DC-DC converter is utilized for charging the EV battery. The proposed controllers achieve maximum power extraction from the PVand regulate the DC-link voltage. It also controls the voltage and current levels of both the ESS and the EV during the charging/discharging process. The study has been applied to two cases with different power levels. Analysis, simulation, and implementation of the proposed system are presented. A 120 W laboratory prototype is carried out to verify the system performance, experimentally. Design guides for higher power levels are proposed to help in choosing the proper parameters of the converters. Both the simulation and experimental results are matched and verify the high performance of the proposed system. [ABSTRACT FROM AUTHOR]

Hearing loss is the inability to hear sounds ranging from 20 decibels or more in one or both ears. It can affect one or both ears and leads to difficulty in hearing speech or sounds in general. Single-sided deafness or unilateral hearing loss is a very widespread disability. However, most people only see hearing loss as being a binary problem assuming that you either have perfect hearing in both ears or are completely deaf in both ears, and dismiss the other types of hearing loss. Sensory substitution involves remapping the information gathered by one sensory receptor to another. Sensory receptors regardless of the signals they receive or capture, all encode the gathered information as electrochemical signals. This biological property of sensory receptors, coupled with the human brain's neuroplasticity allows sensory receptors to be substituted, giving rise to new methods of sensory perception. This study aims to develop a sensory device known as a localizer. The localizer detects sound using numerous sound sensors, and feeds the input to the microcontrollers which then use the input to control the eccentric mass motor by implementing various motor drivers. The results gotten from this prototype device shows great improvement in the ability of a single-sided deaf person to localize sound. [ABSTRACT FROM AUTHOR]

Electrical energy is linked to two signals, current and voltage; before feeding a load, both are sinusoidal signals with equal frequencies but different amplitudes. Microgrids commonly include a communication system that connects all parts of the system. This study builds a prototype of an electrical system with a PIC 18F4550 microcontroller to monitor loads of the University of Sucre microgrid in real-time. They are also designed in MATLAB, a platform to monitor voltage and current variables. The proposed system will be considered an essential solar energy exploitation project component. [ABSTRACT FROM AUTHOR]

Leaks in pipelines caused by acid are destructive to both economic growth and capital which should be avoided at all costs. Damage to underground pipelines is caused by a hard-to-find leak, the unavailability of a real-time monitoring system and the lack of a pipeline history database. The aim of this work is to develop an early warning system to detect acid leaking in the pipeline using Internet of Things (IoT) technology. To detect changes in the pH of acid soil parameters near the pipeline, two mechanisms are required: first, to provide an early warning before the leak is detected and second, to report the occurrence of the leak. The notification system is equipped with three LED indicators, each showing the offline, online and signal detection status. The novelty of the work is a prototype that can detect the acid leak in the pipeline and record the pH values in a database for future research. Using continuous pH monitoring, real-time analysis and a database, this system can detect leaks before they become a major problem. Consequently, the manufacturing industry will benefit from this initiative as it is automated, efficient and cost-effective. [ABSTRACT FROM AUTHOR]

The desire of man to be in control of everything around him in recent times is born out of the rapid development of smart technologies as everything now depends on the internet. Irrigation system is also becoming smart by using modern technologies, which is more advantageous than traditional irrigation methods. In this work, a smart irrigation system is developed that automates the irrigation process powered by solar energy. This proposed system can optimize the use of water based on different data, such as soil moisture level, weather prediction, and soil temperature. A soil moisture sensor that utilizes IoT technology will be inserted into the farmland to detect the moisture level and then notify the farmer about the current condition of the soil through a developed mobile application. Furthermore, the system can automatically turn ON the motor pump from the mobile app to irrigate the farm when the moisture level and soil temperature are below 50% and will automatically turn OFF the pump after fulfilling the demand of the soil when the moisture level and temperature is above 75%. The whole proposed system is controlled by a microcontroller and a DC power is generated from the solar panel which helps to keep the system working at any time of the day. All these features will make the irrigation system much smarter, more economical, and more eco-friendly. In conclusion, this system is recommended for use by farmers who lives in areas with low access to constant water supply. [ABSTRACT FROM AUTHOR]

Gas chromatography is a separation technique heavily utilized in the field of analytical chemistry. It is an important technique to master for an analyst. During the undergraduate years, students of chemistry or related sciences must understand and learn instrumental techniques and develop a practical approach to handling instruments. This article describes the construction of a micro-controller-based gas Chromatograph system with a packed column and a reducing gas detector. Such a gas Chromatograph is easy and cheap to construct and can be used to demonstratively teach analytical chemistry to undergraduate students. [ABSTRACT FROM AUTHOR]

The prevalence of diabetes has been steadily increasing in the past few decades, in particular in low- and middle-income countries. This work develops a non-invasive diabetes monitoring device that is cost effective, stress and pain free which can measure glucose level on the spot. The developed glucose monitoring device consists of three parts; the transmitter section (light source) and the receiver section (photodiode) as well as the processor and the data display section. A Near Infrared (NIR) light is applied onto one side of the ear lobe, while a receiver on the other side receives the attenuated light and then converts the signal into a voltage signal. All these variables are then amplified, sampled, and processed inside the PIC16F877A microcontroller after which the glucose reading will be displayed on the LCD and communicated via the Bluetooth on an android application. From the results obtained, the device has successfully shown that the relationship between the output voltages from photodiode is directly proportional to the concentration of glucose. When the concentration of glucose increases, the output voltage from photodiode also increases. This proved that the concentration of glucose could be predicted using near-infrared light at a wavelength of 1550 nm. [ABSTRACT FROM AUTHOR]

Cardiac arrhythmia is one of the most important cardiovascular diseases (CVDs), causing million deaths every year. Moreover it is difficult to diagnose because it occurs intermittently and as such requires the analysis of large amount of data, collected during the daily life of patients. An important tool for CVD diagnosis is the analysis of electrocardiogram (ECG), because of its non-invasive nature and simplicity of acquisition. In this work we propose a classification algorithm for arrhythmia based on recurrent neural networks (RNNs) that operate directly on ECG data, exploring the effectiveness and efficiency of several variations of the general RNN, in particular using different types of layers implementing the network memory. We use the MIT-BIH arrhythmia database and the evaluation protocol recommended by the Association for the Advancement of Medical Instrumentation (AAMI). After designing and testing the effectiveness of the different networks, we then test its porting to an embedded platform, namely the STM32 microcontroller architecture from ST, using a specific framework to port a pre-built RNN to the embedded hardware, convert it to optimized code for the platform and evaluate its performance in terms of resource usage. Both in binary and multiclass classification, the basic RNN model outperforms the other architectures in terms of memory storage (∼117 KB), number of parameters (∼5 k) and inference time (∼150 ms), while the RNN LSTM-based achieved the best accuracy (∼90%). [ABSTRACT FROM AUTHOR]

The detection of cracks is a key aspect for assessing the condition of in-service structures such as road, bridges or dams. Therefore it assumes a great importance for civil infrastructures monitoring, road maintenance and traffic safety. Intelligent detection methods based on convolutional neural networks (CNNs) have been widely applied to the field of crack detection in recently years. In this work we propose a vision system based on two lightweight and accurate CNN models implemented in a low-cost, low-power platform, namely the OpenMV Cam H7 Plus, to monitor and to detect concrete cracks in real-time, suitable to realize a prototype of early warning system. In order to be useful, such a system must provide a very high accuracy, so as not to give false alarms, and be parsimonious enough on computational resources to be embedded into low-power, portable systems that can be deployed on the field. To reach this goal, firstly we analyze different state-of-the-art CNNs applied to the concrete crack detection task in order to discover the smallest network in terms of memory storage and number of parameters. Then, we compare the performance, in terms of memory occupancy and accuracy, of the proposed CNN architectures with the smallest network in the investigated literature, LeNet, all trained on two different image datasets, the Concrete Crack Images for Classification dataset and the SDNET2018 dataset, and implemented on the embedded system OpenMV Cam H7 Plus. The proposed CNN architectures perform nicely on this platform, using only a small fraction, between 6% to 26%, of the memory required by LeNet, and always providing better accuracy in all the tested cases and on both the datasets tried, with only a marginal increase in inference time. [ABSTRACT FROM AUTHOR]

AM-FM decomposition techniques have been successfully used for extracting significative features from a large variety of signals, helping realtime signal monitoring and pattern recognition, since they represent signals as a simultaneous composition of amplitude modulation and frequency modulation, where the carriers, amplitude envelopes, and the instantaneous frequencies are the features to be estimated. Human activities often involve repetitive movements, such as in running or cycling, where sinusoidal AM-FM decompositions of signals have already demonstrated to be useful to extract compact features to aid monitoring, classification, or detection. In this work we thus present the challenges and results of implementing the iterated coherent Hilbert decomposition (ICHD), a particularly effective algorithm to obtain an AM-FM decomposition, within a resource-constrained and low-power ARM Cortex-M4 microcontroller that is present in a wearable sensor we developed. We apply ICHD to the gyroscope data acquired from an inertial measurement unit (IMU) that is present in the sensor. Optimizing the implementation allowed us to achieve real-time performance using less then 16 % of the available CPU time, while consuming only about 5.4 mW of power, which results in a run-time of over 7 days using a small 250 mAh rechargeable cell. [ABSTRACT FROM AUTHOR]

The relevance of the research is due to the fact that one of the prerequisites for the implementation of Internet of things and Wireless sensor network technologies is the reliable operation of the involved information and measurement systems as parts of the automation and digitalization systems on the rights of subsystems. Thus, the main purpose of the article is to substantiate scientific approaches to increasing the reliability of budget serial microcontroller boards as parts of information and measurement systems by developing methods of improving their technical and functional characteristics. Basic research methods are: methods of critical analysis and logical generalization; methods of computerized monitoring of electrical parameters; methods of experiment planning; methods of computer analysis of measurement results; approaches to experimental testing of information and measuring equipment. The main results of the article are as follows: the current state of scientific research and practical developments on ways to improve the technical and functional characteristics of microprocessor platforms has been analysed; the stabilization characteristics of the output voltage of the microprocessor platform have been investigated; the temperature dependences of the microcontroller at different denominations and types of load have been obtained; the priority areas for further research have been substantiated. [ABSTRACT FROM AUTHOR]

The start phase is a crucial techniques in sprinting. A good start is characterized by an extraordinary force exerted in the horizontal direction. This study develops a start block that can read a three-axis force and a practical device to monitor the sprint start technique based on the force exerted by the feet and block time at the start. The foot pedals obtain feet pushing forces at the start block. These foot pedals are equipped with load cell sensors that record forces in the X (front-back), Y (right-left), and Z (up-down) axes. The start block processes the sensor readings using a microcontroller. The data can be viewed using a smartphone or other mobile devices. The block time is calculated by analyzing the output force reading on the start block. Load Cell testing and calibration were performed for the two load cells used. Measurement results showed a very good linear correlation (>0.99). This linearity indicates that the system can properly measure the load for the tested range. To test the device, A total of 6 elite-level athletes performed two maximum sprints over a distance of 10 m during two separate testing sessions. Intraclass correlation coefficients were used to determine each parameter's reliability. The device showed high reliability (p > 0.5) on the Lx, Lz, Rx, and Rz axes, while the Ly and Ry axes had relatively moderate reliability. This result shows that the Lx, Lz, Rx, and Rz axes gave reliable measurements during the two separate testing sessions. In addition, the device produced accurate data readings, which correlated well with sprint performance. Thus, the developed device is suitable for biomechanical analysis of sprinting starts. [ABSTRACT FROM AUTHOR]

Ways of application of Arduino-like systems in devices for measurement of physical and mechanical indices of quality of long flax fiber that will allow to improve process of measurement and to reduce time for its carrying out are described. Different approaches to determining of the average length of flax fiber are analysed. The developed method for determining the average length of flax fiber using Arduino systems is considered. [ABSTRACT FROM AUTHOR]