An Intelligent cognitive sensing and detection strategy for medical telemetry networks

In medical telemetry networks, cognitive radio technology is mostly used to avoid licensed spectrum underutilization and by providing access to unlicensed spectrum users without causing interference to primary users, this concept is widely used in development of smart hospitals and smart cities. In medical telemetry networks frequency spectrum concept is used for providing treatment to patients who are far away from hospitals. In cognitive radios, spectrum sensing concept is used in which energy detection method is mostly used because it is simple to implement. While measuring health care environments using cognitive radios probability detection, false alarm probability and threshold parameters are calculated. In this paper for identifying spectrum holes in spectrum sensing using energy detection, distributed diffusion non-negative least mean square algorithm is proposed. It gives better results compared to energy detection concept alone in terms of probability detection converged earlier. If number of nodes are increasing probability detection is decreased from one and move towards left and its SNR is around 1.5-2 dB with proposed method. Hence simulation results give better results in terms of sensing ability while measuring patient condition.

Analysis of FBMC Waveform for 5G Network Based Smart Hospitals

Nowadays, many prevalent frameworks for medical care have been projected, studied, and implemented. The load and challenges of traditional hospitals are increasing daily, leading to inefficient service in the health system. Smart hospitals based on advanced techniques play a crucial part in advancing the health services of rural people. It spares the time and money involved in travel, and patient medical reports can be shared instantly with the experts regardless of geographical constraints. Currently, the role of technology in hospitals is limited due to various restrictions, such as the obtainability of a high spectrum, low latency, and high-speed network. In this paper, we focused on the implementation of an advanced waveform with high spectral performance. Filer Bank Multi-Carrier (FBMC) is considered a strong contender for the upcoming 5G-centered smart hospitals due to its high data rate, no leakage of the spectrum, and less sensitivity to frequency error. In addition, a comparison of the spectral utilization of orthogonal frequency division multiplexing (OFDM) and FBMC in terms of bit error rate (BER), peak power (PP), power spectral density (PSD), noise-PSD, capacity and magnitude, and phase response is illustrated. Numerical results show that the FBMC achieved a throughput gain of 1 dB and its spectral performance is better than the OFDM; hence, it is a better choice for the proposed application compared to the current standard OFDM.

Implementation of User Authentication System in Smart Hospitals Useful in the Age of the Covid-19 Pandemic

The security system for authentication and user records in a smart hospital is part of an integrated security system consisting of various authentication devices. The security system should be adapted to different characteristics of users, their user processes, but also to periods when the possibility of infection is increased due to a virus pandemic and contamination during multiple touches of different persons on authentication devices. The use of gloves and a medical face mask during a pandemic limits biometric scanning of fingerprints and facial images. During a virus pandemic, some authentication devices have limitations that need to be considered when creating an integrated security system that will have the purpose of securing doctors, staff, patients, information, and things in a smart hospital. In this paper, the parameters on the basis of which it is possible to design an optimally integrated security system are recommended.

Application of IoT in the COVID-19 Pandemic

As we all know, the Internet has altered everything, and the Internet of Things has given us hope for a bright future of the Internet with Machine-to-Machine (M2M) connectivity. This review study demonstrated that smart systems based on the Internet of Things are feasible and economical to build (IoT). In the field of healthcare, the Internet of Things has made significant progress. This article examines how the Internet of Things (IoT) is revolutionising the healthcare industry by giving huge healthcare advantages to humanity through accessible and practical healthcare solutions specially during the hard coronavirus situation around the world. The purpose of this study is to address the function of IoT in smart hospitals, as well as its importance in dealing with pandemics. Various smart gadgets that can provide a variety of features, such as adequate monitoring of high-risk patients, tracking their bio-metric measurements, and gathering real-time data, can be used to serve community-specific demands during pandemic spread. We've also looked into other plans that can detect unforeseen events utilising a variety of sensors and display the information gathered on an LED display. The results of observational studies have indicated a high level of agreement with the hypothetical claims.

Multimodal Brain Tumor Segmentation Based on an Intelligent UNET-LSTM Algorithm in Smart Hospitals

Smart hospitals are important components of smart cities. An intelligent medical system for brain tumor segmentation is required to construct smart hospitals. To achieve intelligent brain tumor segmentation, morphological variety and serious category imbalance must be managed effectively. Conventional deep neural networks have difficulty in predicting high-accuracy segmentation images due to these issues. To solve these problems, we propose using multimodal brain tumor images combined with the UNET and LSTM models to construct a new network structure with a mixed loss function to solve sample imbalance and describe an intelligent segmentation process to identify brain tumors. To verify the practicability of this algorithm, we used the open source Brain Tumor Segmentation Challenge dataset to train and verify the proposed network. We obtained DSCs of 0.91, 0.82, and 0.80; sensitivities of 0.93, 0.85, and 0.82; and specificities of 0.99, 0.99, and 0.98 in three tumor regions, including the whole tumor ( WT ), tumor core ( TC ), and enhanced tumor ( ET ). We also compared the results of the proposed network with those of other brain tumor segmentation methods, and the results showed that the proposed algorithm could segment different tumor lesions more accurately, highlighting its potential application value in the clinical diagnosis of brain tumors.

BIM for Smart Hospital Management during COVID-19 Using MCDM

In context of the recent COVID-19 pandemic, smart hospitals’ contributions to pre-medical, remote diagnosis, and social distancing has been further vetted. Smart hospital management evolves with new technology and knowledge management, which needs an evaluation system to prioritize its associated criteria and sub-criteria. The global effect of the COVID-19 pandemic further necessitates a comprehensive research of smart hospital management. This paper will utilize Analytical Hierarchy Process (AHP) within Multiple Criteria Decision Making (MCDM) to establish a smart hospital evaluation system with evaluation criteria and sub-criteria, which were then further prioritized and mapped to BIM-related alternatives to inform asset information management (AIM) practices. This context of this study included the expert opinions of six professionals in the smart hospital field and collected 113 responses from hospital-related personnel. The results indicated that functionalities connected to end users are critical, in particular IoT’s Network Core Functionalities, AI’s Deep Learning and CPS’s Special Network Technologies. Furthermore, BIM’s capability to contribute to the lifecycle management of assets can relate and contribute to the asset-intensive physical criteria of smart hospitals, in particular IoT, service technology innovations and their sub-criteria.

On-demand multi-hop forwarding for sustainable vehicular data transfer network

Smart cities play a vital role to develop a sustainable infrastructure with efficient management of the Internet of things devices. The infrastructure is used to support various applications for smart hospitals, smart factories, and intelligent transportation systems. With the extensive deployment of Internet of things devices, unprecedented growth in data has lead to capacity and transfer issues. In this article, we proposed an efficient data transfer mechanism based on self-sustainable networks over the vehicular environment. Depending on whether the network is connected with vehicles available to support direct connection from the source to destination, we propose end-to-end and hop-by-hop forwarding for vehicular networks that are inherently disconnected. The evaluation results demonstrate that the lifetime of the discovered paths depends on the coverage area, vehicle mobility, and vehicle speed. Therefore, at times redundant disjoint paths are selected for communication. In the proposed work, selected vehicles are used to reach the destination.

Smart hospitals around the world: a systematic review

Background It is almost impossible to think about a non-digital world today. digital technologies have changed our life style and they have also affected many domains including health domain. We are all aware that paper-based hospitals have changed a lot to be paper-less. Then a new term was born which is “smart hospital” and studies have been conducted in this field, so this study was designed to conduct a comprehensive review about smart hospitals. Methods 741 studies were identified using unique keywords through searching in the PubMed, ScienceDirect, Embase and Scopus databases. Overall, after applying the inclusion and exclusion criteria (647 based on abstract title and 33 after reading full text) and removing duplicates (43), 18 studies were included in this review. Results Geographically, most of the articles were from Asia (50%). The highest number of publications were observed in 2012. A multidisciplinary team were involved in 77% of the researches and 61.12% of them were conducted in more than one research center. The majority of articles have been published in Q1 quality journals (33.34%) and high-income countries accounted for the largest percentage (66.67) of publishing smart hospital related articles. 27.78% of the studies were aimed at patient care, which had the highest percentage. Among the technologies used, RFID was the most and 66.67% of the articles came from researches about the implementation of a smart hospital. Conclusions it should be noted that development or implementation of a smart device in a hospital should not be considered as implementing a smart hospital, while many studies have used the term smart hospital in their study. Many Asian researchers have used the term “smart hospital” in their articles, but on the other hand, most of related articles published in Q1 journals were from America and Europe. Also, it was also observed that most studies focused on the two concepts including resource management and patient care.