Performance analysis of smart optimization antenna for wireless networks

Antenna design has significantly advanced as a result of the widespread need for wireless communications and data substitution through wireless devices. The research article's goal is to provide a conceptual framework, difficulties, and opportunities for a source as well as a general overview of the antenna used in wireless communications applications. In this proposed research, we will go over a variety of topics related to mobile communication and fifth generation (5G) technologies, including its pros and benefits. A thorough comparison between the expected properties of the antennas and each generation, from 1st generation (1G) to 5G, is also included. This article also provides an overview of the investigated 5G technologies and various antenna designs

Smartphone Applications for Providing Ubiquitous Healthcare Over Cloud with the Advent of Embeddable Implants

The world we live in today has been defined by the rise of the smartphone and smartphone apps. There is a huge potential for these apps to have an impact in healthcare via the use of the emerging field of biosensor technology in the form of wearables and implants. This paper discusses the future of healthcare from a technological standpoint, looking specifically at the use of these wearables and implants in conjunction with the power of cloud computing to provision healthcare in efficient and effective ways. There is also a discussion involving a specific example of how an app currently in development can be augmented with biosensor technology in the near future.</p

Consumer-friendly food allergen detection : moving towards smartphone-based immunoassays

In this critical review, we provide a comprehensive overview of immunochemical food allergen assays and detectors in the context of their user-friendliness, through their connection to smartphones. Smartphone-based analysis is centered around citizen science, putting analysis into the hands of the consumer. Food allergies represent a significant worldwide health concern and consumers should be able to analyze their foods, whenever and wherever they are, for allergen presence. Owing to the need for a scientific background, traditional laboratory-based detection methods are generally unsuitable for the consumer. Therefore, it is important to develop simple, safe, and rapid assays that can be linked with smartphones as detectors to improve user accessibility. Smartphones make excellent detection systems because of their cameras, embedded flash functions, portability, connectivity, and affordability. Therefore, this review has summarized traditional laboratory-based methods for food allergen detection such as enzyme-linked-immunosorbent assay, flow cytometry, and surface plasmon resonance, and the potential to modernize these methods by interfacing them with a smartphone readout system, based on the aforementioned smartphone characteristics. This is the first review focusing on smartphone-based food-allergen detection methods designed with the intention of being consumer-friendly. [Figure not available: see fulltext.

An intelligent healthcare system with peer-to-peer learning and data assessment

Modern e-healthcare systems are prevalent in many medical institutions to reduce physicians&#039; workload and enhance diagnostic accuracy, which leverages affordable wearable devices and Machine-Learning (ML) techniques. The healthcare systems collect various vital biosignals (e.g., heart rate and blood pressure) from wearable devices of users (e.g., chronic patients living alone at home) and analyze these patients&#039; data in real-time by different ML classifiers (e.g. Support Vector Machine (SVM) or Hidden Markov Model (HMM)). The automatic diagnosis effectively improves the physicians&#039; performance in terms of diagnostic efficiency and accuracy. There are three challenges impacting these healthcare systems -- the increasing number of patients, new diseases and the changes of existing disease patterns, which are caused by population aging as well as the alteration of environment and lifestyle. This research is intended to explore a novel healthcare system with advanced ML solutions that can solve the challenges and exhibit high accuracy and efficiency