The unmanned aerial vehicle (UAV) swarm is gaining massive interest for researchers as it has huge significance over a single UAV. Many studies focus only on a few challenges of this complex multidisciplinary group. Most of them have certain limitations. This paper aims to recognize and arrange relevant research for evaluating motion planning techniques and models for a swarm from the viewpoint of control, path planning, architecture, communication, monitoring and tracking, and safety issues. Then, a state-of-the-art understanding of the UAV swarm and an overview of swarm intelligence (SI) are provided in this research. Multiple challenges are considered, and some approaches are presented. Findings show that swarm intelligence is leading in this era and is the most significant approach for UAV swarm that offers distinct contributions in different environments. This integration of studies will serve as a basis for knowledge concerning swarm, create guidelines for motion planning issues, and strengthens support for existing methods. Moreover, this paper possesses the capacity to engender new strategies that can serve as the grounds for future work.

In recent years, the power system has been evolved into microgrids, which are little pockets of self-contained entities. Different distributed, interconnected generation units, loads, and energy storage units make up a typical microgrid system. The increased energy efficiency of these units on microgrids is gaining popularity day by day. Because of their stochastic behavior, renewable generation causes an imbalance in the power system, which needs microgrid energy management. To solve these issues, a variety of novel approaches have been explored in the literature. For the stand-alone microgrid in this research, efficient energy management and control mechanism is adopted. A photovoltaic system, a wind turbine, and a battery energy storage device make up this stand-alone microgrid. The power stability of the hybrid system is ensured by a sophisticated controller. The main purpose of this study is to regulate the DC/DC bidirectional converter (DBC), which connects the Li-ion battery to the DC bus of the stand-alone microgrid. This paper describes the development of a wind/photovoltaic power generation system to the load, as well as MPPT techniques like perturb and observe (P&O). The system is simulated and the results are presented using MPPT techniques. There is no requirement for a specific power model in the suggested method. Only power and voltage system data are used by DBC. A stand-alone microgrid system was simulated using MATLAB.

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the brain source localization has attained the significant fascination over the last few decades. Source localization in the human brain is a prospective complication that is derived in the multifaceted real-world complications because of the brain’s practical and biological density, other than medical precincts of assembling EEG from enormously various subjects. It is validated that the electromagnetic signal recorded on the top of scalp is owing to the collective actions of a neurons inside the brain. Any impulsive action of the brain, sensory stimulus, cognitive action, or the generation of motor yield possibly will offer intensification to such neuronal actions. Source- localization in human brain implicates the localization and detection of such primary neuronal originators into the brain. Although the renowned and different research in the area, the complications remnants to be mysterious inverse problem in the brain signal processing research. This paper highlighted the performance analysis the EEG source localization techniques based on standardized low resolution brain electromagnetic tomography (sLORETA) and exact low resolution brain electromagnetic tomography (eLORETA).  The event related potential (ERP) records with chromatic stimulus are considered for analysis at diverse time intervals for both techniques and finally results are discussed in reports of scalp map, slice view and cortex map and proposed the optimum techniques for EEG source localization.