Understanding environmental information is necessary for functions correlated with human activities to improve healthcare quality and reduce ecological risk. Tapered optical fibers reduce some limitations of such devices and can be considerably more responsive to fluorescence and absorption properties changes. Data have been collected from reliable sources such as Science Direct, IEEE Xplore, Scopus, Web of Science, PubMed, and Google Scholar. In this narrative review, we have summarized and analyzed eight classes of tapered-fiber forms: fiber Bragg grating (FBG), long-period fiber grating (LPFG), Mach–Zehnder interferometer (MZI), photonic crystals fiber (PCF), surface plasmonic resonance (SPR), multi-taper devices, fiber loop ring-down technology, and optical tweezers. We evaluated many issues to make an informed judgement about the viability of employing the best of these methods in optical sensors. The analysis of performance for tapered optical fibers depends on four mean parameters: taper length, sensitivity, wavelength scale, and waist diameter. Finally, we assess the most potent strategy that has the potential for medical and environmental applications.

Timely detection and diagnosis are essentially needed to guide outbreak measures and infection control. It is vital to improve healthcare quality in public places, markets, schools and airports and provide useful insights into the technological environment and help researchers acknowledge the choices and gaps available in this field. In this narrative review, the detection of coronavirus disease 2019 (COVID-19) technologies is summarized and discussed with a comparison between them from several aspects to arrive at an accurate decision on the feasibility of applying the best of these techniques in the biosensors that operate using laser detection technology. The collection of data in this analysis was done by using six reliable academic databases, namely, Science Direct, IEEE Xplore, Scopus, Web of Science, Google Scholar and PubMed. This review includes an analysis review of three highlights: evaluating the hazard of pandemic COVID-19 transmission styles and comparing them with Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS) to identify the main causes of the virus spreading, a critical analysis to diagnose coronavirus disease 2019 (COVID-19) based on artificial intelligence using CT scans and CXR images and types of biosensors. Finally, we select the best methods that can potentially stop the propagation of the coronavirus pandemic.

This review describes a cloud-based intelligent power management system that uses analytics as a control signal and processes balance achievement pointer, and describes operator acknowledgments that must be shared quickly, accurately, and safely. The current study aims to introduce a conceptual and systematic structure with three main components: demand power (direct current (DC)-device), power mix between renewable energy (RE) and other power sources, and a cloud-based power optimization intelligent system. These methods and techniques monitor demand power (DC-device), load, and power mix between RE and other power sources. Cloud-based power optimization intelligent systems lead to an optimal power distribution solution that reduces power consumption or costs. Data has been collected from reliable sources such as Science Direct, IEEE Xplore, Scopus, Web of Science, Google Scholar, and PubMed. The overall findings of these studies are visually explained in the proposed conceptual framework through the literature that are considered to be cloud computing based on storing and running the intelligent systems of power management and mixing.

The constant innovative advancements of brushless DC motors (BLDCMs) have discovered a wide scope of utilizations. For instance, underground electric vehicles, drones, and submerged bikes have just confirmed elite BLDCMs. Be that as it may, their appropriation requires control frameworks to screen torque, speed and other execution attributes. This paper presents numerous brilliant controllers structure and order line programming to assemble, alter and mimic intelligent to control BLDCMs. Recently planned graphical user interface (GUI) structure for Multi controllers: conventional proportional integral derivative (PID) controller, intelligent controller based fuzzy techniques: type 1, type 2, and modified type 2 fuzzy logic controller (T1FLC, IT2FLC, and MIT2FLC respectively). Different phases of the problematic framework configuration process, from the underlying depiction to the last usage, can be acquired from the altered tool compartment. MATLAB Ver.2019b was utilized to mimic and plan all procedure GUI. The agreeable aftereffects of MIT2FLC have been approved also; the examination gives the subtleties of the GUI program through estimations, shapes, flowcharts and code, giving understanding into the presumptions of common-sense boundaries that may emerge in such a minimal effort mentor for BLDCM. At last, the outcomes acquired through a few reproduction tests affirm the legitimacy of the showed math model and designing of intelligent controllers.