IAES International Journal of Robotics and Automation (IJRA)
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The use and significance of machine learning to screen COVID-19
Get PDFCoronavirus disease 2019 (COVID-19) virus was first seen in 2019 December in China and rapidly spread all over the world and millions of people are infected with this virus. This disease has sited the entire world in dangerous circumstances. At the start of this virus, it was a very serious matter in China but now it is being observed all over the world. The virus is life-threatening, and other public who are affected by previous diseases or those people whose age is more than 60 are more affected by this virus. The healthcare and drug industries have tried to find a treatment. While machine learning algorithms are largely applied in other areas, at this time every health care unit has to want to use machine learning techniques to find, predict, track, and screen the spread of COVID-19, and try to find the treatment of it. we show what is the journey of machine learning to find and track COVID-19 and also observing it from a screening and detecting the COVID-19. We show how much research has been done yet to detection of COVID-19 and which algorithm of machine learning is best for the detection and screening of the COVID-19
Water injection control modelling by using model-based calibration
Get PDFThis study presents the development of water injection system for turbocharged spark ignition engine. The water injection control system is built for turbocharged spark ignition (SI) engine where water was injected at the intake port just before the throttle body. The data was collected from the simulation through the GT-Power software to determine the optimized injection output for the engine. Single-stage statistical engine responses and boundary models were established by using Model-Based Calibration (MBC) Toolbox. Control system was built using Simulink and simulation tests were conducted based on the speed and throttle position as the variables. The highest value of brake torque achieved in the GT-Power simulation was taken as the base value to determine the injection amount. The mean value of the predicted injection was recorded at 12.29 g/s while the variance of the predicted injection to the optimized injection was below 1%. The control system was simulated with the set predicted injection and the standard deviation of the predicted injection was 1.18. The control system simulation recorded a low percentage of 0.04% variance to the optimized injection with the pulse width modulation signal. The control system is ideal to be constructed and tested on actual engine test bed
A smart door prototype with a face recognition capability
Get PDFThis research aimed to integrate a face recognition capability in a smart door prototype. By using a camera-based face recognition, the house owner does not need to make physical contact to open the door. Avoid physical contact is important due to the coronavirus disease 2019 (COVID19) pandemic. Raspberry Pi 3B was used as the main controller, while a servo motor was utilized as a locking door actuator. The program was developed using Node-RED, Blynk, and message queue telemetry transport (MQTT) platforms which are very powerful for developing internet of things (IoT) devices. All of the programs were coded using Python. Haar cascade and local binary pattern histogram methods were implemented on the face recognition stage. Google Assistant integration was done by using Dialogflow and Firebase as Google Cloud services. Integration of face recognition and the smart door was successful. The smart door was unlocked if faces were recognized (average threshold=60%). If a face was not recognized, an email notification containing a face image is sent to the house owner. The Google Assistant could handle user requests successfully with a success rate of 92.8% from 147 trials
Development of an electronic payment system using the Internet of things
Get PDFSmartphone has become more widely used than ever and become necessary to develop electronic payment systems using the internet of things (IoT) techniques with the smartphone. Payment solution is one of the most important issues in the IoT. It is the future to make life easier and better through the new relationships will be commercial, requiring payment for services and products. This paper develops a prototype of a payment system consisting of a network from several interconnecting devices such as radio frequency identification (RFID) reader, RFID card tag, equipped with microprocessors NodeMCU, and corresponding software represented by an interactive website for making process of purchase, a database (MySQL) for store data of payments. Focusing on the side of protecting the payment system, a security model for a simplistic payment system based on the IoT is represented by using biometric authentication in the sensor of smartphones like fingerprint authentication and face detection to make sure the identification of the user before making the payment process in the system
Modified power rate sliding mode control for robot manipulator based on particle swarm optimization
No full textThis work suggests an optimized improved power rate sliding mode control (PRSMC) to control a 4-degrees of freedom (DOF) manipulator in joint space as well as workspace. The proposed sliding mode control (SMC) aims to improve the reaching mode and to employ an optimization method to tune the control parameters that operate the robotic manipulator adaptively. Inverse kinematics is used to obtain the joint desired angles from the end effector desired position, while forward kinematics is used to obtain the real Cartesian position and orientation of the end effector from the real joint angles. The proposed enhancements to the SMC involve the use of the hyperbolic tangent function in the control law to improve the reaching mode. Added to that, particle swarm optimization (PSO) is used to tune the parameters of the improved SMC. Furthermore, the Lyapunov function is utilized to analyze the stability of the closed-loop system. The proposed enhanced sliding mode combined with the optimization method is applied experimentally on a 4-DOF manipulator to prove the feasibility and efficiency of the proposed controller. Finally, the performance of the suggested control scheme is compared with the conventional power rate SMC in order to demonstrate the enhanced performance of the suggested method
The surface electromyography noise filtering and unwanted recordings attenuation for lower limb robotic system
Get PDFExoskeleton robotic device (ERD) for rehabilitation purposes, physically interacts alongside with the user where high cognitive interaction and the safe human - machine system is required. To ensure safe interaction, there is a need to detect the user’s motion intention. One of the bio-signals that have been found to reflect directly the individual’s motion intention is surface electromyography (sEMG). However, sEMG signals are inevitably full of noises, not to mention the unwanted recordings and other artifact s between muscles where they cannot be freely used as a control signal for ERD. This paper presents the use of the Butterworth filter for noise suppression and the attenuation of unwanted recordings. Using classical Butterworth filter typically is unable to eliminate or attenuate the unwanted contamination on the signal of interest to its baseline level. Therefore, it is critical to modify the Butterworth filter at this stage. sEMG signals from the biceps femoris and rectus femoris muscles of seven health y male young adults were recorded in this study. The onset/ offset technique is utilized to detect the presence of the additional signal contaminated on the signal of interest. If the onset/offset index points are not approximately correlated with the movement, this means there is a contaminated measurement on the signal of interest. At this interval, a filter with distributed cutoff frequency plays the role to have the already smoothed baseline signal. In summary, the modified Butterworth filter shows to have a good performance to suppress the noises and to attenuate the unwanted recordings adaptively which ensures a safe human-machine system
Synthesis of control laws for magnetic levitation systems based on serial invariant manifolds
Get PDFIn this paper, a nonlinear controller is designed for a magnetic levitation system (MLS) based on serial invariant manifolds. Synthesized controller based on the method of synergetic control theory (SCT) through invariant manifolds, asymptotically stable. In this method, the control law is synthesized to ensure the motion of the closed-loop control object from an arbitrary initial state into the vicinity of the desired invariant manifold. Thereby, the control system not only ensures the necessary control quality but also ensures the asymptotic stability of the entire system. The quality and efficiency of the control law are proven through simulation results and comparison with the sliding mode controller (SMC)
An efficient regression method for 3D object localization in machine vision systems
No full textMachine vision or robot vision plays is playing an important role in many industrial systems and has a lot of potential applications in the future of automation tasks such as in-house robot managing, swarm robotics controlling, product line observing, and robot grasping. One of the most common yet challenging tasks in machine vision is 3D object localization. Although several works have been introduced and achieved good results for object localization, there is still room to further improve the object location determination. In this paper, we introduce a novel 3D object localization algorithm in which a checkerboard pattern-based method is used to initialize the object location and followed by a regression model to regularize the object location. The proposed object localization is employed in a low-cost robot grasping system where only one simple 2D camera is used. Experimental results showed that the proposed algorithm significantly improves the accuracy of the object localization when compared to the relevant works
An effective approach to enhance the balancing control in bycycorobot using the soft computing techniques
Get PDFThe balancing and control of bycycorobot is a challenging task. The pre-specified controller available in the literature for balancing has been reduced with novel optimization to improve the effectiveness of balancing, uncertainty, and the complexity of the complete system. The novel Harris hawk optimization (HHO) which is based on the hunting behavior of the hawk has been utilized to improve the balancing of the bycycorobot. The paper proposes the decreased order controller of a pre-specified controller for a bycycorobot. The obtained controller response with bycycorobot in the complete closed loop is analyzed, and the best performance is compared with the reduced order controller available in the literature. The comparison is based on the response indices and response characteristics
Active object search using a pyramid approach to determine the next-best-view
Get PDFThe development of service robotics continues to arouse interest in the scientific community due to the complexity of the activities performed like interaction in human environments, identifying and manipulating objects, and even learning by themselves. This paper proposed to improve the perception of the environment by searching for objects in service robotics tasks. We present the development and implementation of an active object search method based on three main phases: Firstly, image pyramid segmentation to examine in detail the im- age features. Second step, object detection at each level of the pyramid through a local feature descriptor and a mutual information calculation. Finally, the next camera position selection through analyzing the object detections accumulation in the pyramid. To evaluate the implementation of the proposed method, we use a NAO robot in a familiar place for humans, such as an office or a home. Ordinary objects are part of our database with the premise that a robot must know them before looking for an object. The results in the experiments showed an acceptable performance in simulation and with a real platform