Impact of Covid Pandemic on OTT Streaming Services

Starting from Cable connections to various options in satellite TV brands, the transition paved the way gradually for free content on applications like YouTube, which further led to the demand for quality content on OTT platforms. Over-the- Top or OTT is the abbreviation for "over-the-top” which is a new age streaming of films and TV series over the web without the need for traditional cable, or satellite pay-TV providers;the consumers can stream across multiple gadgets according to our time convenience. Beginning in the late 90s, the early 2000s marked the era of Television streaming in India. The first OTT application launched in India was BigFix, which changed the course of content consumption in our country. The Television industry once driven by cable and satellite operators has transitioned into a consumer-driven domain. Unlike TV, which requires a cable connection or an antenna, OTT material is delivered directly over Online platforms and paid for directly by viewers. The implications are that the consumers may get OTT services including video, voice, messaging and audio services, at any time and from any location, which serves to be a significant advantage over traditional TV programming. In this paper, we focus on how this paradigm change took place and what impact it has created, especially since the pandemic. © 2023 IEEE.

Design and Implementation of a Microstrip Array for WiFi External Antenna

The wireless communication system very essential technology and have significant use after corona virus effect the world very badly. The Wi-Fi technology exhibits good wireless communication to provide internet facility but suffers with low antenna gain. This novel array proposed method with different dielectric material properties is used to enhancement the gain of the Wi-Fi antenna. The operating frequency of the proposed antenna is at 2. 5GHZ. This proposed method consist of Teflon dielectric material with dielectric constant of 2.02 has the gain of 8.4dbi, return loss of -30db and VSWR is 1.85, with loss tangent 0.0002. This proposed method compares with different dielectric material like kapton and fr-4 substrate but Teflon exhibit the good results. This proposed method work good for PCB antennas and flexible and wearable antennas with kapton substrate. © 2022 IEEE.

Scenic Beauty Evaluation of Forests with Autumn-Colored Leaves from Aerial and Ground Perspectives: A Case Study in Qixia Mountain in Nanjing, China

In recent years, on-site visitation has been strictly restricted in many scenic areas due to the global spread of the COVID-19 pandemic. "Cloud tourism”, also called online travel, uses high-resolution photographs taken by unmanned aerial vehicles (UAVs) as the dominant data source and has attracted much attention. Due to the differences between ground and aerial observation perspectives, the landscape elements that affect the beauty of colored-leaved forests are quite different. In this paper, Qixia National Forest Park in Nanjing, China, was chosen as the case study area, and the best viewpoints were selected by combining tourists' preferred viewing routes with a field survey, followed by a scenic beauty evaluation (SBE) of the forests with autumn-colored leaves in 2021 from the aerial and ground perspectives. The results show that (1) the best viewpoints can be obtained through the spatial overlay of five landscape factors: elevation, surface runoff, slope, aspect, and distance from the road;(2) the dominant factors influencing the beauty of colored-leaved forests from the aerial perspective are terrain changes, forest coverage, landscape composition, landscape contrast, the condition of the human landscape, and recreation frequency;and (3) the beauty of the ground perspective of the colored-leaved forests is strongly influenced by the average diameter at breast height (DBH), the dominant color of the leaves, the ratio of the colored-leaved tree species, the canopy width, and the fallen leaf coverage. The research results can provide scientific reference for the creation of management measures for forests with autumn-colored leaves. © 2023 by the authors.

Hand-breathe: Non-Contact Monitoring of Breathing Abnormalities from Hand Palm

In post-covid19 world, radio frequency (RF)-based non-contact methods, e.g., software-defined radios (SDR)-based methods have emerged as promising candidates for intelligent remote sensing of human vitals, and could help in containment of contagious viruses like covid19. To this end, this work utilizes the universal software radio peripherals (USRP)-based SDRs along with classical machine learning (ML) methods to design a non-contact method to monitor different breathing abnormalities. Under our proposed method, a subject rests his/her hand on a table in between the transmit and receive antennas, while an orthogonal frequency division multiplexing (OFDM) signal passes through the hand. Subsequently, the receiver extracts the channel frequency response (basically, fine-grained wireless channel state information), and feeds it to various ML algorithms which eventually classify between different breathing abnormalities. Among all classifiers, linear SVM classifier resulted in a maximum accuracy of 88.1%. To train the ML classifiers in a supervised manner, data was collected by doing real-time experiments on 4 subjects in a lab environment. For label generation purpose, the breathing of the subjects was classified into three classes: normal, fast, and slow breathing. Furthermore, in addition to our proposed method (where only a hand is exposed to RF signals), we also implemented and tested the state-of-the-art method (where full chest is exposed to RF radiation). The performance comparison of the two methods reveals a trade-off, i.e., the accuracy of our proposed method is slightly inferior but our method results in minimal body exposure to RF radiation, compared to the benchmark method. IEEE

Theory and Simulation of Multipurpose Antenna for Detection and Degrading of Viruses in Times of Pandemic

This paper present a theoretical model that aims to minimize the capabilities of viruses in public places through engineered electromagnetic fields. Thus, the modeling of antenna based at the infinitesimal dipole is used. In addition fields and directivity at the far field region are calculated. This proposal empathizes the fact that the radiated energy will affect the spike protein of viruses. In this manner the functionality of virus as to produce infection would be minimized. Simulations of the radiate electric field are presented. © 2022 IEEE.

Analysis of the Use of Robots for the Second Year of the COVID-19 Pandemic

This article examines 152 reports the use of robots explicitly due to the COVID-19 pandemic reported in the science, trade, and press from 24 Jan 2021 to 23 Jan 2022 (Year 2) and compares with the previously published uses from 24 Jan 2020 to 23 Jan 2021 (Year 1). Of these 152 reports, 80 were new unique instances documented in 25 countries, bringing the total to 420 instances in 52 countries since 2020. The instances did not add new work domains or use cases, though they changed the relative ranking of three use cases. The most notable trend in Year was the shift from a) government or institutional use of robots to protect healthcare workers and the Public to b) personal and business use to enable the continuity of work and education. In Year 1, Public Safety, Clinical Care, and Continuity of Work and Education were the three highest work domains but in Year 2, Continuity of Work and Education had the highest number of instances. © 2022 IEEE.

A Silicon-Based Radio Platform for Integrated Edge Sensing and Communication Toward Sustainable Healthcare

Faced with COVID-19 and the trend of aging, it is demanding to develop an online health metrics sensing solution for sustainable healthcare. An edge radio platform owning the function of integrated sensing and communications is promising to address the challenge. Radar demonstrates the capability for noncontact healthcare with high sensitivity and excellent privacy protection. Beyond conventional radar, this article presents a unique silicon-based radio platform for health status monitoring supported by coherent frequency-modulated continuous-wave (FMCW) radar at Ku-band and communication chip. The radar chip is fabricated by a 65-nm complementary metal–oxide–semiconductor (CMOS) process and demonstrates a 1.5-GHz chirp bandwidth with a 15-GHz center frequency in 220-mW power consumption. A specific small-volume antenna with modified Vivaldi architecture is utilized for emitting and receiving radar beams. Biomedical experiments were implemented based on the radio platform cooperating with the antenna and system-on-chip (SoC) field-programmable gate array (FPGA) edge unit. An industrial, scientific, and medical (ISM)-band frequency-shift keying (FSK) communication chip in 915-MHz center frequency with microwatt-level power consumption is used to attain communications on radar-detected health information. Through unified integration of radar chip, management software, and communication unit, the integrated radio platform featuring −72-dBm sensitivity with a 500-kb/s FSK data rate is exploited to drastically empower sustainable healthcare applications.

IoT Based Intelligent System for Covid - 19 hotspot detection by CNN Crowd Density Algorithm

The worldwide health crisis is caused by the widespread of the Covid-19 virus. The virus is transmitted through droplet infection and it causes the common cold, coughing, sneezing, and also respiratory distress in the infected person and sometimes becomes fatal causing death. As the world battles against covid-19, the proposed approach can help to contain the clustering of covid hotspot areas for the treatment of over a million affected patients. Drones/ Unmanned Aerial Vehicles (UAVs) offer a great deal of support in this pandemic. As suggested in this research, they can also be used to get to remote places more quickly and efficiently than with conventional means. In the hospital's control room, there would be a person in command of the ambulance drone. For hotspot area detection, the drone would be equipped with FLIR camera and for detection and recognition of face the video transmission is used by raspberry pi camera. The detection of face is done by Haar cascade Classifier and recognition of the face with LBPH algorithm. This is used for identify the each individual's medical history or can be verified by Aadhar Card. Face recognition between still and video photos was compared, and the average accuracy of still and video images was 99.8 percent and 99.57 percent, respectively. To find the hotspot area is to use the CNN Crowd counting algorithm. If the threshold value is less than equal to 0.5 than it is hotspot area , if it is greater than 0.5 and less than equal to 0.75 than it is semi-normal area , if it is greater than 0.75 and less than equal to 1 than it is normal area. © 2022 IEEE.

RF Coverage Design for the Implementation of a Broadband Monitoring Service in the Context of 5G-Enabled Smart Cities

As the recent COVID-19 pandemic has aptly demonstrated, emergency scenarios concerning public health and safety may require citizens to remain at home even as patients, potentially in the context of a municipal or national lockdown. Homestay patients may require real-time monitoring, which will offer not only communication but also empirical data and will contribute to developing their personalized electronic health record in knowledge bases. Our paper features an extensive RF coverage design for such a municipally deployed and administered 5G-enabled smart city network, supporting a broadband monitoring service. The antenna deployment for the outdoor urban topology is analytically described (for the downlink channel), and the intrinsic indoor propagation characteristics are considered for the uplink channel. A digital baseband signaling scheme is assumed on the basis of a user-customized health-related monitoring service. Path loss and fading calculations consider the potential worst-case propagation conditions so that the RF coverage will be reliable, leading to a resilient city-wide municipal network. © 2023 by the authors.

Hand Gesture-based Control of Autonomous UAV for Mobile Disinfectant Dispenser

Autonomous unmanned aerial vehicles (UAVs) have witnessed a rapid increase in their utilization in various applications and will continue to do so in the coming decades. These UAVs, also known as drones, are designed to either assist humans or perform tasks that involve people. Drones of today have grown to be faster and less expensive by integrating several technologies, supported by hybrid algorithms, and perform various tedious, challenging, filthy and hazardous tasks. The deployment of machine learning and other AI-based algorithms enhances drones' autonomous and vision capabilities. Today, part of an effort to curtail the spread of COVID-19, this research has designed, developed and built a mobile disinfectant dispenser based on autonomous quadrotor UAV. It is a 'flying dispenser', able to detect a person's hand gestures from afar, based on machine learning (ML), to fly and maneuver towards the person and finally spray disinfectant on his/her hand. In order to identify various hand motions for maneuvering, this research studies and improves the ML algorithms and carries out various experiments to improve the drones' response time and maneuvering performance, for the final objective of taking precautions to protect humans from Covid-19. © 2022 IEEE.

Semantic Segmentation Algorithms for Ground AGV and UAV Medical Transport Scenes

The outbreak of the Covid-19 pandemic in recent years and the epidemics of infectious diseases that have occurred around the world over the years, there are problems of lack of medical supplies and difficulties in personnel scheduling. Intelligent medical transportation through modern technology is an effective means to solve this problem. AGV(Automated Guided Vehicle) transportation and UAV(Unmanned Aerial Vehicle) transportation are important ways for intelligent transportation of medical materials. This paper investigates semantic segmentation as a key technology for AGV transport and UAV transport. This paper compares other traditional semantic segmentation networks, and at the same time considers the characteristics of all-weather, all-terrain, and complex transportation of materials in medical transportation, and proposes SSMMTNet(Semantic segmentation of medical material transportation Net). Among them, we propose a Scaling Transformer Block that can extract depth features of point clouds to enrich contextual information. At the same time, the network is validated on the benchmark Semantic3D dataset, obtaining 71.5% mIoU and 90.6% OA. © 2022 IEEE.

Design and Performance Analysis of Compact Coronavirus-Shaped Microstrip Patch Antenna for Wireless Applications †

The paper proposes a compact-sized coronavirus-shaped Microstrip Patch Antenna (MPA) for wireless communication. A 15-20 GHz band of frequency is employed to analyze the effect of the shape on antenna's performance and characteristics. A low-cost FR4 dielectric substrate is used in the design and implementation of the coronavirus-shaped antenna, with suitable dimensions. The proposed antenna has six patterns depending upon the band of frequencies, and the same have been analyzed. The results show that the realized gain is better than -15 dB when using frequencies around 17 GHz, and total efficiency is about 70%. CST microwave software is used for designing and analysis.

Sensorized Facemask With Moisture-Sensitive RFID Antenna.

Due to the ongoing COVID-19 pandemic, the use of filtering facepiece respirators (FFRs) is increasingly widespread. Since the masks' wetness can reduce its filtering capabilities, the World Health Organization advises to replace the FFRs if they become too damp, but currently, there is no practical way to monitor the masks' wetness. A low-cost moisture sensor placed inside the FFRs could discriminate a slightly damp mask from a wet one, which must be replaced. In this letter, a radio frequency identification (RFID) tag exploiting an auto-tuning microchip for humidity sensing is designed and tested during an ordinary working day and a physical exercise. The tag returns about 1 unit of the digital metric every 3 mg of water generated by breathing and sweating, and it can identify excessively wet masks from commonly used ones.

Smart Visual Sensing for Overcrowding in COVID-19 Infected Cities Using Modified Deep Transfer Learning

Currently, COVID-19 is circulating in crowded places as an infectious disease. COVID-19 can be prevented from spreading rapidly in crowded areas by implementing multiple strategies. The use of unmanned aerial vehicles (UAVs) as sensing devices can be useful in detecting overcrowding events. Accordingly, in this article, we introduce a real-time system for identifying overcrowding due to events such as congestion and abnormal behavior. For the first time, a monitoring approach is proposed to detect overcrowding through the UAV and social monitoring system (SMS). We have significantly improved identification by selecting the best features from the water cycle algorithm (WCA) and making decisions based on deep transfer learning. According to the analysis of the UAV videos, the average accuracy is estimated at 96.55%. Experimental results demonstrate that the proposed approach is capable of detecting overcrowding based on UAV videos' frames and SMS's communication even in challenging conditions. © 2005-2012 IEEE.

Development of Pandemic Monitoring System Based on Constellation of Nanosatellites

Covid-19 is a global crisis and the greatest challenge we have faced. It affects people in different ways. Most infected people develop a mild to moderate form of the disease and recover without hospitalization. This presents a problem in spreading the pandemic with unintentionally manner. Thus, this paper provides a new technique for COVID-19 monitoring remotely and in wide range. The system is based on satellite technology that provides a pivotal solution for wireless monitoring. This mission requires a data collection technique which can be based on drones' technology. Therefore, the main objective of our proposal is to develop a mission architecture around satellite technology in order to collect information in wide range, mostly, in areas suffer network coverage. A communication method was developed around a constellation of nanosatellites to cover Saudi Arabia region which is the area of interest in this paper. The new proposed architecture provided an efficient monitoring application discussing the gaps related to thermal imaging data. It reached 15.8 min as mean duration of visibility for the desired area. In total, the system can reach a coverage of 5.8 h/day, allowing to send about 21870 thermal images. © 2023 CRL Publishing. All rights reserved.

Dual-Polarized COVID-19 Microstrip Antenna Array for 5G Applications

This paper presents a novel unique single-layer dual-polarized microstrip patch antenna array with a COVID-19 shape designed for building a Base Station (BS) for sub-6 GHz applications at the resonant frequency 3.16 GHz. Furthermore, it is easy to fabricate and compact, which makes it suitable for 5G applications. Firstly, a single-element fractal shape antenna with a gain of 3 dB is discussed. Secondly, an 8-element 2x4 antenna array is designed with a gain of 8 dB. The antenna is fabricated using an FR4-epoxy double-sided copper board with a thickness of 1.6 mm. It is optimized by performing parametric studies of the dimensions using the finite element method (FEM) software program HFSS. The printed prototype measurements including S-parameters, polarization, and radiation pattern show a good agreement with simulation results. © 2022 IEEE.

To IEEE Antennas and Propagation Society Members [President's Message]

It is my deep honor and pleasure to serve as the 2023 president of the IEEE Antennas and Propagation Society (AP-S). I would like to thank all IEEE AP-S members for their support for my election. After the difficult period of COVID-19, the situation is gradually returning to normality. We are again back to conferences in person and live meetings. This simplifies my job with respect to the one of my predecessors, Prof. Yahia Antar (president in 2021) and Gianluca Lazzi (president in 2022). They have done an incredible job in the past years leading the Society during an anomalous period. I thank Yahia for his encouragement and advice and for the work he is continuing to do in promoting the Society all over the world through new initiatives. A special thanks to Gianluca for his outstanding leadership, for his work and service, for the excellent ideas and initiatives he carried out during his term, and mostly for helping me in understanding the various aspects of the Society. I am very thankful for his support, suggestions, and friendship.

TRANSLATED SKIP CONNECTIONS - EXPANDING THE RECEPTIVE FIELDS OF FULLY CONVOLUTIONAL NEURAL NETWORKS

The effective receptive field of a fully convolutional neural network is an important consideration when designing an architecture, as it defines the portion of the input visible to each convolutional kernel. We propose a neural network module, extending traditional skip connections, called the translated skip connection. Translated skip connections geometrically increase the receptive field of an architecture with negligible impact on both the size of the parameter space and computational complexity. By embedding translated skip connections into a benchmark architecture, we demonstrate that our module matches or outperforms four other approaches to expanding the effective receptive fields of fully convolutional neural networks. We confirm this result across five contemporary image segmentation datasets from disparate domains, including the detection of COVID-19 infection, segmentation of aerial imagery, common object segmentation, and segmentation for self-driving cars. © 2022 IEEE.

Study on the Simultaneous Measurement of Multiple Positions of the Human Body Using Two-Dimensional Millimeter-Wave Array Radar

Radar-based non contact measurement of physiological signals and vital signs has been of great interest, partly because of the COVID-19 pandemic. Existing studies reported that different physiological signals can be extracted from different positions of the human body. In this study, we demonstrate the measurement of multiple positions of the human body using a radar system with a two-dimensional antenna array. Using a 79-GHz 48-channel multiple-input multiple-output antenna array, we image multiple body parts of participants and separate the echoes using array signal processing. We present experimental results to show the feasibility of the proposed approach. © 2022 The Institute of Electronics Information and Communication Engineers (IEICE) of Japan.

Simulation and Development of an Autonomous Drone for Delivery of Medicines during COVID-19

The main goal of this research paper is to develop an autonomous medicine delivery quadcopter and validate a simulator model for it. It is intended to use this drone in crisis of COVID-19 due to restriction of social distancing and unavailability of regular hospital facilities. A simulator is then modified and used as a pre-mission tool to predict mission outcome and after validation, it will be used to predict complex missions without actually risking the expensive drone. An efficient payload system is designed and constructed for the quadcopter to fulfill its delivery purpose. Once the drone is assembled along with the payload mechanism, its physical parameters are calculated using SolidWorks. The same parameters such as performance coefficients and moments of inertia are then updated in the simulator's quadcopter properties. The equations of motions model used is improved by including physical theoretical effects. In the end, same autonomous delivery mission tests have been done for the real quadcopter and the simulator in order to compare the results and show the effect of improved equations of motion and physical parameters. © 2022 IEEE.