This study proposes a duty cycle-based direct search method that capitalizes on a bioinspired optimization algorithm known as the salp swarm algorithm (SSA). The goal is to improve the tracking capability of the maximum power point (MPP) controller for optimum power extraction from a photovoltaic system under dynamic environmental conditions. The performance of the proposed SSA is tested under a transition between uniform irradiances and a transition between partial shading (PS) conditions with a focus on convergence speed, fast and accurate tracking, reduce high initial exploration oscillation, and low steady-state oscillation at MPP. Simulation results demonstrate the superiority of the proposed SSA algorithm in terms of tracking performance. The performance of the SSA method is better than the conventional (hill-climbing) and among other popular metaheuristic methods. Further validation of the SSA performance is conducted via experimental studies involving a DC-DC buck-boost converter driven by TMS320F28335 DSP on the Texas Instruments Experimenter Kit platform. Hardware results show that the proposed SSA method aligns with the simulation in terms of fast-tracking, convergence speed, and satisfactory accuracy under PS and dynamic conditions. The proposed SSA method tracks maximum power with high efficiency through its superficial structures and concepts, as well as its easy implementation. Moreover, the SSA maintains a steady-state oscillation at a minimum level to improve the overall energy yield. It thus compensates for the shortcomings of other existing methods.

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This paper presents the development of Augmented Reality (AR) for smart campus urbanization using library as the environment for the demonstration of the AR prototype. The main goal of the AR development is to help users to get information and direction easily using AR based mobile application when walking inside the library. In normal circumstances, users typically walk around and explore the library area before reaching their targeted destinations. Depending on the library size and number of reading corners, exploration and walking in the library can be time consuming. Therefore, an AR technology is introduced in this paper to improve the user experience inside the library in the right direction and information instantly. This application is developed using Vuforia software to set the image marker-based and process the output into Unity3D software, Android Studio for the Main Menu interface and IBM Watson for voice recognition. The final form of the application is successfully generated from the development of Augmented Reality (AR) application for the smart campus by using a library for the demonstration of the AR prototype. A series of application tests are conducted in each corner of the library to evaluate the effectiveness of developed AR.

A microstrip patch antenna is designed for a wearable antenna. The performance of microstrip patch antenna loaded with reactive impedance surface (RIS) is described in terms of gain, bandwidth and return loss. The antenna is investigated in two conditions which are conventional microstrip antenna with RIS and without RIS. The designed antenna is also aimed at size reduction therefore it will be suitable for a wearable application. This antenna which is made fully using textile and it is designed for operation in the 2.45 GHz band. The performance of microstrip patch antenna loaded with RIS is described in terms of gain, bandwidth, return loss and radiation pattern. The antenna designed with RIS operates at 2.45 GHz. Bandwidth enhancement is achieved with RIS where the designed antenna can cater frequency from 2.4 GHz to 3 GHz. A gain enhancement is achieved of 20% is achieved compared with the conventional patch antenna. Although the size of the patch is reduced with the introduction of RIS, the overall size of the antenna with the substrate is almost similar to the conventional patch antenna. However, the performance of the antenna is greatly enhanced with the use of RIS.

<span>This paper presents a low-cost PV current-voltage or <em>I-V</em> curve tracer that has the Internet of Things (IoT) capability. Single ended primary inductance converter (SEPIC) is used to develop the <em>I-V</em> tracer, which is able to cope with rapidly changing irradiation conditions. The <em>I-V</em> tracer control software also has the ability to automatically adapt to the varying irradiation conditions. The performance of the <em>I-V</em> curve tracer is evaluated and verified using simulation and experimental tests.</span>

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