In this work, an indirect coupling used in a pair of simple autonomous discrete systems in order to enhance the emergence of hyperchaos is presented. The peculiarity that the used systems will never ...generate chaotic or hyperchaotic dynamics by itself makes this case an interesting problem to address. Moreover, it is possible to achieve in-phase or anti-phase synchronization by varying some parameters of the indirect coupling. Additionally, different methods to analyze the emerging dynamics of the coupled systems using an indirect coupling compared to a conventional coupling are presented. Finally, an electronic digital implementation is conducted by using the SPI protocol of two coupled PIC-24FJ64GA006 16-bit microcontrollers.
Variable-step incremental conductance (Inc.Cond.) technique, for photovoltaic (PV) maximum power point tracking, has merits of good tracking accuracy and fast convergence speed. Yet, it lacks ...simplicity in its implementation due to the mathematical division computations involved in its algorithm structure. Furthermore, the conventional variable step-size, based on the division of the PV module power change by the PV voltage change, encounters steady-state power oscillations and dynamic problems especially under sudden environmental changes. In this study, an enhancement is introduced to Inc.Cond. algorithm in order to entirely eliminate the division calculations involved in its structure. Hence, algorithm implementation complexity is minimised enabling the utilisation of low-cost microcontrollers to cut down system cost. Moreover, the required real processing time is reduced, thus sampling rate can be improved to fasten system response during sudden changes. Regarding the applied step-size, a modified variable-step size, which depends solely on PV power, is proposed. The latter achieves enhanced transient performance with minimal steady-state power oscillations around the MPP even under partial shading. For proposed technique's validation, simulation work is carried out and an experimental set up is implemented in which ARDUINO Uno board, based on low-cost Atmega328 microcontroller, is employed.
The growing number of low-power smart devices in the Internet of Things is coupled with the concept of "edge computing" that is moving some of the intelligence, especially machine learning, toward ...the edge of the network. Enabling machine learning algorithms to run on resource-constrained hardware, typically on low-power smart devices, is challenging in terms of hardware (optimized and energy-efficient integrated circuits), algorithmic, and firmware implementations. This article presents a FANN-on-MCU, an open-source toolkit built upon the fast artificial neural network (FANN) library to run lightweight and energy-efficient neural networks on microcontrollers based on both the ARM Cortex-M series and the novel RISC-V-based parallel ultralow-power (PULP) platform. The toolkit takes multilayer perceptrons trained with FANN and generates code targeted to low-power microcontrollers. This article also presents detailed analyses of energy efficiency across the different cores, and the optimizations to handle different network sizes. Moreover, it provides a detailed analysis of parallel speedups and degradations due to parallelization overhead and memory transfers. Further evaluations include experimental results for three different applications using a self-sustainable wearable multisensor bracelet. The experimental results show a measured latency in the order of only a few microseconds and power consumption of a few milliwatts while keeping the memory requirements below the limitations of the targeted microcontrollers. In particular, the parallel implementation on the octa-core RISC-V platform reaches a speedup of <inline-formula> <tex-math notation="LaTeX">22\times </tex-math></inline-formula> and a 69% reduction in energy consumption with respect to a single-core implementation on Cortex-M4 for continuous real-time classification.
Flexural ultrasonic transducers experience sustained residual vibrations after their excitation has ended. This behavior limits both the minimum range and the range resolution of single-transducer ...distance sensors operating in pulse-echo mode. Two methods are presented to address residual vibration issues without reducing the intensity of the transmitted pressure waves. The first method is a transmitter enhancement; a number of out-of-phase damping cycles is appended to the desired number of excitation cycles, thereby hastening the decay of the pulse-imposed transducer voltage. The second method is a receiver enhancement; the echo-induced transducer voltage is isolated from the pulse-imposed transducer voltage by subtracting a stored masking signal from the acquired receiver signal. The proposed methods rely on a simple learning procedure that does not require a mathematical model of the system. Because this procedure is executed on an embedded microcontroller, the proposed methods are insensitive to variations in components or parameters. Experiments demonstrate improvements in both minimum range and range resolution.
Face masks offer efficient, convenient, and affordable defense against infectious agents or airborne diseases namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and many others. ...Various types of face masks have been developed for people in previous years. However, any of these face masks do not provide any effective means to provide feedback to users to wear them accurately. In this work, the authors present a sensorized adjustable strap for a face mask to ensure its accurate position on the face. This strap allows wearing a face mask comfortably without putting any pressure on the ears of a user. In this strap, a push-button is interfaced with a microcontroller which sets up a threshold value as per the orientation of the face mask on the user. The microcontroller is pre-processed with a protocol to evaluate and store the threshold values. In this work, the flex sensor is used to measure the amount of bending angle of a strap, wherein the microcontroller, on processing and comparing the analog value from the flex sensor with the set threshold value, generates a command in case the value recedes the threshold value. For real-time feedback, a vibrator is used to alert the user to wear the mask properly. The proposed work has provided an effective performance with an average accuracy of 95.25%. As we move towards a future where avoiding cross-infection is crucial and contactless experiences are preferred, the advancements in this field will greatly benefit society.
An accurate and fast solid-state transfer switch (SSTS) has the potential to automate conventional utility network. Presently, it consumes most of the transfer time in detecting the condition for ...initiating the transfer process. Recent developments in the power semiconductor devices technology have reduced the switching time to the tune of nanoseconds. Hence, time consumed by the disturbance detection is significant in SSTS. IEEE Std. 1100-2005 and IEEE Std. 446-1995 require fast load transfer for SSTS. Realization of an innovative machine learning technique is implemented on three AVR microcontrollers for each of three phases. The microcontroller executes segmentation of acquired signal and calculates derivative of each segment. From each preprocessed 10-sample segment, mean absolute deviation and energy features are extracted. On the basis of feature values, support vector machine classifier with the linear kernel detects disturbance. Logical OR gate generates transfer enable signal to initiate the transfer process. Results of case studies appreciate the ability of proposed hardware to detect common disturbances in power system under different operating conditions. The hardware provides a feasible solution for SSTS with required accuracy and speed.
In this article, a novel and an efficient methodology is presented for real-time monitoring of ECG signals. The method involves fast Fourier transform (FFT) based discrete wavelet transform (DWT) for ...extracting the features from the heartbeats which involves less computational complexity in terms of additions and multiplications operations for higher order filter lengths. These features extracted are recognized using particle swarm optimization (PSO) tuned twin support vector machines (TSVM) classifier. The TSVM classifier is four times faster than the standard SVM while the PSO technique is employed to gradually tune the classifier parameters to achieve more accuracy. The proposed methodology is implemented on IoT based microcontroller platform and validated on the benchmark Physionet data to classify 16 categories of ECG signals. Once an abnormality is detected, the platform generates a pop-up message as a warning and sends the information to a remote platform allowing hospitals to take preventive measures. The platform reported a higher overall accuracy of 95.68% than the existing studies. Further, such implementation can be utilized as a warning system in both homecare as well as tele-monitoring applications to continuously monitor the cardiac condition of a subject anywhere to the state-of-art heart disease diagnosis.
After carrying out the manufacture of prototypes and desin from the robots that carry goods, it needs to be developed into the actual robot making so that dpat can be implemented with a real goods ...lifting robot so that it can be useful for the survival of the academic activities. The academic activity here is to lift goods in this case is a book or file from the third floor corner to the academic bureau room. With various tests have been carried out so that later the work of this tool is expected to operate properly in accordance with the wishes of the researcher. With the right analysis and calculation, this tool can lift items with a maximum weight of 5 kg and all items or items that are lifted can be placed in the designated place at the top of the robot. Control of the smartphone can move the robot so that it reaches the destination. The voice command is inputted to the smartpone that has been connected to the Arduino Uno system so that it can command the robot with a forward, backward movement, turn left and turn right. The control system is centered on the Arduino Uno microcontroller that has been loaded with a program to run this tool or robot. Research has succeeded in making robots designed according to the work and the desired system to help work in the lifting of goods.
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