A shared aperture 2-element multiple-input-multiple-output (MIMO) antenna design for 5G standards is presented in this study, one which uses the same radiating structure to cover both the sub-6GHz and millimeter-wave (millimeter-wave) bands. The proposed antenna comprises four concentric pentagonal slots that are uniformly separated from one another. For the sub-6GHz band, the antenna is excited by a single open-end microstrip transmission-line, while a 1 × 8 power divider (PD) connected via a T-junction structure excites the millimeter-wave band. Both the sub-6GHz and mm-wave antennas operate in a MIMO configuration. The proposed antenna design was fabricated on a 120 × 60 mm² substrate with an edge-to-edge distance of 49 mm. The proposed sub-6GHz antenna covers the following frequency bands: 4–4.5 GHz, 3.1–3.8 GHz, 2.48–2.9 GHz, 1.82–2.14 GHz, and 1.4–1.58 GHz, while the millimeter-wave antenna operates at 28 GHz with at least 500 MHz of bandwidth. A complete antenna analysis is provided via a step-by-step design procedure, an equivalent circuit diagram showing the operation of the shared aperture antenna, and current density analysis at both millimeter-wave and sub-6GHz bands. The proposed antenna design is also characterized in terms of MIMO performance metrics with a good MIMO operation with maximum envelop correlation coefficient value of 0.113. The maximum measured gain and efficiency values obtained were 91% and 8.5 dBi over the entire band of operation. The antenna is backward compatible with 4G bands and also encompasses the sub-6GHz and 28 GHz bands for future 5G wireless communcation systems.

This work presents a compact meandered loop slot-line 5G antenna for Internet of Things (IoT) applications. Recently, sub-gigahertz (sub-GHz) IoT technology is widely spreading. It enables long-range communications with low power consumption. The proposed antenna structure is optimized to operate at sub-GHz bands without any additional complex biasing circuitry or antenna structure. A miniaturized design was achieved by a meandered structured loop slot-line that is loaded reactively with a varactor diode. Wideband frequency reconfigurability (FR) was achieved by the use of the varactor diode. The proposed antenna resonates over the frequency band of 758–1034 MHz with a minimum bandwidth of 17 MHz over the entire frequency band. The RO4350 substrate with dimensions of 0.18λ_g × 0.13λ_g mm² is used to design the proposed antenna design. The efficiency and gain values varied from 54–67% and 0.86–1.8 dBi. Compact planar structure, narrow-band operation (suitable for NB-IoT) and simple biasing circuitry, which allows for sub-GHz operation, are unique and attractive features of the design.

The COVID-19 pandemic has shown that there is a lack of healthcare facilities to cope with a pandemic. This has also underscored the immediate need to rapidly develop hospitals capable of dealing with infectious patients and to rapidly change in supply lines to manufacture the prescription goods (including medicines) that is needed to prevent infection and treatment for infected patients. The COVID-19 has shown the utility of intelligent autonomous robots that assist human efforts to combat a pandemic. The artificial intelligence based on neural networks and deep learning can help to fight COVID-19 in many ways, particularly in the control of autonomous medic robots. Health officials aim to curb the spread of COVID-19 among medical, nursing staff and patients by using intelligent robots. We propose an advanced controller for a service robot to be used in hospitals. This type of robot is deployed to deliver food and dispense medications to individual patients. An autonomous line-follower robot that can sense and follow a line drawn on the floor and drive through the rooms of patients with control of its direction. These criteria were met by using two controllers simultaneously: a deep neural network controller to predict the trajectory of movement and a proportional-integral-derivative (PID) controller for automatic steering and speed control.

With the development of artificial intelligence technology, various sectors of industry have developed. Among them, the autonomous vehicle industry has developed considerably, and research on self-driving control systems using artificial intelligence has been extensively conducted. Studies on the use of image-based deep learning to monitor autonomous driving systems have recently been performed. In this paper, we propose an advanced control for a serving robot. A serving robot acts as an autonomous line-follower vehicle that can detect and follow the line drawn on the floor and move in specified directions. The robot should be able to follow the trajectory with speed control. Two controllers were used simultaneously to achieve this. Convolutional neural networks (CNNs) are used for target tracking and trajectory prediction, and a proportional-integral-derivative controller is designed for automatic steering and speed control. This study makes use of a Raspberry PI, which is responsible for controlling the robot car and performing inference using CNN, based on its current image input.

A line follower robot is an autonomous intelligent system that can detect and follow a line drawn on floor. Line follower robots need to adapt accurately, quickly, efficiently, and inexpensively to changing operating conditions. This study proposes a deep learning controller for line follower mobile robots using complex decision-making strategies. An Arduino embedded platform is used to implement the controller. A multilayered feedforward network with a backpropagation training algorithm is employed. The network is trained offline using Keras and implemented on a ATmega32 microcontroller. The experimental results show that it has a good control effect and can extend its application.

In this paper, a folded slot-based multiple-input–multiple-output (MIMO) antenna design for Cube Satellite (CubeSat) applications is presented for the ultra-high frequency (UHF) band. A unique combination of a reactively loaded meandered slot with a folded structure is presented to achieve the antenna’s miniaturization. The proposed antenna is able to operate over a wide frequency band from 430~510 MHz. Moreover, pattern diversity is achieved by the antenna’s element placement, resulting in good MIMO diversity performance. The four elements are placed on one Unit (1U) for CubeSat dimensions of 100 mm × 100 mm × 100 mm. The miniaturized antenna design with pattern diversity over a wide operating band is well suited for small satellite applications, particularly CubeSats in the UHF band.