Electronics

Thanks to the recent rapid technological advancement in IoT usage, there is a need for students to learn IoT-based concepts using a dedicated experimental platform. Furthermore, being forced into remote learning due to the ongoing COVID-19 pandemic, there is an urgent need for innovative learning methods. From our perspective, a learning platform should be reconfigurable to accommodate multiple applications and remotely accessible at any time, from anywhere, and on any connected device. Considering that many of the university courses are now held online, the reliability and scalability of the system become critical. This paper presents the design and development of a wireless configurable myRIO-based sensor node that connects to SystemLink Cloud. The sensors that were used are for ambient light, temperature, and proximity. A graphical programming environment (G-LabVIEW) and related APIs were used for rapid concept-to-development process. Distinct applications have been developed for...

A low cost High Definition (HD) security surveillance system with motion detection and device control over the internet is explained in this paper. The system is reconfigurable and can be applied to many applications. However for the purposes of this project a system configured to monitor a home and home devices is explained. Further reconfigurability can make the system suitable for use in military surveillance, bank vaults and locker rooms, shopping malls and authenticated areas depending on the devices to be controlled. The real time surveillance is carried out by the D-Link DCS 930 IP wireless camera that works with both Wi-fi and Ethernet connection. The camera is powered by both mains supply and battery which then makes it suitable for continuous surveillance monitoring. An integration of the camera with a motion detector is also done to be able activate notifications (video, images and sound) that are sent via mail and in case of bad internet connection it uses the Subscriber...

This article describes the design and development of the NI myRIO device-based remote laboratory. The cloud-based, expandable, and reconfigurable remote laboratory is intended to give students access to an online web-based user interface to perform experiments. Multiple myRIO devices are programmed to host several experiments each. A finite state machine is used to select specific experiments, while a single state can contain several. The laboratory web virtual instruments interfaces are hosted on the SystemLink cloud and SystemLink server. A user-friendly interface has been designed to help students to understand important electronic concepts. Virtual and real experiments were fused to give students a wide range of experiments they can access online. The instructor can check outputs of an experiment being executed on the device. Achieving connection between myRIO and SystemLink through global variables and SystemLink ensured that the low-cost device was utilized, and this is suitab...

A study conducted by the World Economic Forum revealed that about 75 million jobs will disappear because of the Artificial Intelligence (AI), but AI will bring with it more than 133 million new job. Therefore, for making a smooth transition to the next Industrial Revolution, the reskilling initiatives play a key role. In the information age, it is crucial to educate students to acquire the skills necessary for the new jobs that will be created thanks to AI. Because everything we touch and everything we do will be enhanced by AI in the near future, new ways of working will become increasingly popular. Therefore, this paper aims to define new learning methods based on AI to educate engineers for the jobs that will emerge in the following years. AI is the fusion of many fields of study. Electrical engineering and computer science are determining the hardware and software implementation of the systems based on AI. The teaching practice used in this study combines several fields of study and is based on using LabVIEW including the Deep Learning Toolkit (DeepLTK) and Python Node to teach engineers all the necessary steps for developing, validating and deploying machine learning-based systems. The approach is based on learning by examples and by comparisons with human intelligence, methodologies which have proven to be very efficient. The key anticipated outcome of this study is that students and engineers will gain relevant knowledge about the powerful machine learning algorithms.

Music is important in everyday life, and music therapy can help treat a variety of health issues. Music listening is a technique used by music therapists in various clinical treatments. As a result, music therapists must have an intelligent system at their disposal to assist and support them in selecting the most appropriate music for each patient. Previous research has not thoroughly addressed the relationship between music features and their effects on patients. The current paper focuses on identifying and predicting whether music has therapeutic benefits. A machine learning model is developed, using a multi-class neural network to classify emotions into four categories and then predict the output. The neural network developed has three layers: (i) an input layer with multiple features; (ii) a deep connected hidden layer; (iii) an output layer. K-Fold Cross Validation was used to assess the estimator. The experiment aims to create a machine-learning model that can predict whether ...