A Smart Social Distance Monitoring System

The entire world is affected by Covid-19 pandemic. One of the major reasons is that it is contagious and a minimum distance should be maintained to stay safe. Social distancing might be a difficult task to implement effectively. Social distancing plays a pivotal role in curbing diseases that are contagious like Covid-19.Now that situations are returning to normal, the risk of getting infected is still high. Governments are deciding to ease lockdown regulations, as part of the unlocking public places, workspaces and educational institutions started to resume their activities. Considering the current scenario, the public has to strictly follow all the necessary Covid-19 protocols to reduce the spike in the number of Covid cases. This project aims to develop a prototype device that helps in implementing social distancing using Ultra-Wide Band (UWB) wireless technology based solution. Prototype issues an alert signal when the distance between individuals is less than the prescribed threshold distance. If the protocol is breached, the user is alarmed through an LED. UWB is known for its advantages as it has greater signal strength compared to Bluetooth. The design of the prototype enables implementation as wearable such as an ID card. © 2022 IEEE.

Autonomous Flight Using UWB-Based Positioning System with Optical Flow Sensors in a GPS-Denied Environment

This study presents the positioning method and autonomous flight of a quadrotor drone using ultra-wideband (UWB) communication and an optical flow sensor. UWB communication obtains the distance between multiple ground stations and a mobile station on a robot, and the position is calculated based on a multilateration method similar to global positioning system (GPS). The update rate of positioning using only UWB communication devices is slow;hence, we improved the update rate by combining the UWB and inertial measurement unit (IMU) sensor in the prior study. This study demonstrates the improvement of the positioning method and accuracy by sensor fusion of the UWB device, an IMU, and an optical flow sensor using the extended Kalman filter. The proposed method is validated by hovering and position control experiments and also realizes a sufficient rate and accuracy for autonomous flight.

Design of antennas for microwave imaging techniques

The present epidemic of coronavirus (COVID-19) was originated in Wuhan, China, on 31 December 2019. After that, it spread worldwide, and continues to this day. Its affects are deadly and keeps all countries around the world in lockdown. Countries are fighting with it by keeping lockdown and by developing vaccines to save human life. Due to this pandemic situation, people who have other diseases are in fear to go to hospitals because of infections. Many medical devices are available to monitor ourselves at home itself, like oximeters, thermometer, blood pressure monitoring devices, and blood sugar monitoring devices. If similar devices were available for breast cancer detection, it would help many women to save their lives and get treatment in time. This chapter focuses on such technology that is known as microwave imaging technology, where wideband antennas play a vital role. The design of such antennas is a challenge for researchers;here, few of the designs of ultra-wideband antenna are presented. © 2022 Scrivener Publishing LLC.

Proximity Detection During Epidemics: Direct UWB TOA Versus Machine Learning Based RSSI.

In this paper, we compare the direct TOA-based UWB technology with the RSSI-based BLE technology using machine learning algorithms for proximity detection during epidemics in terms of complexity of implementation, availability in existing smart phones, and precision of the results. We establish the theoretical limits on the precision and confidence of proximity estimation for both technologies using the Cramer Rao Lower Bound (CRLB) and validate the theoretical foundations using empirical data gathered in diverse practical operating scenarios. We perform our empirical experiments at eight distances in three flat environments and one non-flat environment encompassing both Line of Sight (LOS) and Obstructed-LOS (OLOS) situations. We also analyze the effects of various postures (eight angles) of the person carrying the sensor, and four on-body locations of the sensor. To estimate the range with BLE RSSI, we use 14 features for training the Gradient Boosted Machines (GBM) learning algorithm and we compare the precision of results with those obtained from memoryless UWB TOA ranging algorithm. We show that the memoryless UWB TOA algorithm achieves 93.60% confidence, slightly outperforming the 92.85% confidence of the BLE RSSI with more complex GBM machine learning (ML) algorithm and the need for substantial training. The training process for the RSSI-based BLE social distance measurements involved 3000 measurements to create a training dataset for each scenario and post-processing of data to extract 14 features of RSSI, and the ML classification algorithm consumed 200 s of computational time. The memoryless UWB ranging algorithm achieves more robust results without any need for training in less than 0.5 s of computation time.

Early screening tool for developmental delay in infancy: Quantified assessment of movement asymmetry using IR-UWB radar.

In the untact COVID-19 era, the feasibility of a noncontact, impulse-radio ultrawideband (IR-UWB) radar sensor has important medical implications. Premature birth is a major risk factor for brain injury and developmental delay; therefore, early intervention is crucial for potentially achieving better developmental outcomes. Early detection and screening tests in infancy are limited to the quantification of differences between normal and spastic movements. This study investigated the quantified asymmetry in the general movements of an infant with hydrocephalus and proposes IR-UWB radar as a novel, early screening tool for developmental delay. To support this state-of-the-art technology, data from actigraphy and video camcorder recordings were adopted simultaneously to compare relevant time series as the infant grew. The data from the three different methods were highly concordant; specifically, the ρz values comparing radar and actigraphy, which served as the reference for measuring movements, showed excellent agreement, with values of 0.66 on the left and 0.56 on the right. The total amount of movement measured by radar over time increased overall; movements were almost dominant on the left at first (75.2% of total movements), but following shunt surgery, the frequency of movement on both sides was similar (54.8% of total movements). As the hydrocephalus improved, the lateralization of movement on radar began to coincide with the clinical features. These results support the important complementary role of this radar system in predicting motor disorders very early in life.

Design of Indoor Disinfecting Intelligent Robot Based on ESP32 Chip

Since the outbreak of the COVID-19, comprehensive and thorough environmental disinfection is a very important issue. In order to reduce personnel contact and reduce the risk of cross-infection, this paper designs an indoor disinfecting intelligent robot that can realize large-scale combined disinfection of disinfectant and ultraviolet. The whole system comprises of five main parts: control center, running control module, disinfection module, information processing module, and power module. The control center mainly adopts ESP32micro-controller to achieve the connection and control of all parts of the system. The running control module mainly controls the forward, backward, and rotation of the device and ensures that the system follows the expected path during the disinfection. The disinfection module uses liquid disinfectant and ultraviolet irradiation to inhibit the bacteria and kill COVID-19. Information processing module is responsible for the information interaction between the system and the data center. The proposed system transmits data through Wi-Fi and MQTT protocol, and realizes basic functions such as positioning, path planning, and disinfection. The proposed system can effectively solve the problem of personal contact and infection in the process of manual disinfection and have nice application value. © 2022 IEEE.

A Non-Contact Detection Method for Multi-Person Vital Signs Based on IR-UWB Radar.

With the vigorous development of ubiquitous sensing technology, an increasing number of scholars pay attention to non-contact vital signs (e.g., Respiration Rate (RR) and Heart Rate (HR)) detection for physical health. Since Impulse Radio Ultra-Wide Band (IR-UWB) technology has good characteristics, such as non-invasive, high penetration, accurate ranging, low power, and low cost, it makes the technology more suitable for non-contact vital signs detection. Therefore, a non-contact multi-human vital signs detection method based on IR-UWB radar is proposed in this paper. By using this technique, the realm of multi-target detection is opened up to even more targets for subjects than the more conventional single target. We used an optimized algorithm CIR-SS based on the channel impulse response (CIR) smoothing spline method to solve the problem that existing algorithms cannot effectively separate and extract respiratory and heartbeat signals. Also in our study, the effectiveness of the algorithm was analyzed using the Bland-Altman consistency analysis statistical method with the algorithm's respiratory and heart rate estimation errors of 5.14% and 4.87%, respectively, indicating a high accuracy and precision. The experimental results showed that our proposed method provides a highly accurate, easy-to-implement, and highly robust solution in the field of non-contact multi-person vital signs detection.

UWB Radar Sensing for Respiratory Monitoring Exploiting Time- Frequency Spectrograms

Regarding the health-related applications in infectious respiratory/breathing diseases including COVID-19, wireless (or non-invasive) technology plays a vital role in the monitoring of breathing abnormalities. Wireless techniques are particularly important during the COVID-19 pandemic since they require the minimum level of interaction between infected individuals and medical staff. Based on recent medical research studies, COVID-19 infected individuals with the novel COVID-19-Delta variant went through rapid respiratory rate due to widespread disease in the lungs. These unpleasant circumstances necessitate instantaneous monitoring of respiratory patterns. The XeThru X4M200 ultra-wideband radar sensor is used in this study to extract vital breathing patterns. This radar sensor functions in the high and low-frequency ranges (6.0-8.5 GHz and 7.25-10.20 GHz). By performing eupnea (regular/normal) and tachypnea (irregular/rapid) breathing patterns, the data were acquired from healthy subjects in the form of spectrograms. A cutting-edge deep learning algorithm known as Residual Neural Network (ResNet) is utilised to train, validate, and test the acquired spectrograms. The confusion matrix, precision, recall, F1-score, and accuracy are exploited to evaluate the ResNet model's performance. ResNet's unique skip-connection technique minimises the underfitting/overfitting problem, providing an accuracy rate of up to 97.5%. © 2022 IEEE.

FRAMEWORK FOR TOUCHLESS PATIENT MONITORING SYSTEM INTEGRATING ULTRA-WIDEBAND RADAR AND INTERNET OF THINGS FOR COVID-19 PATIENTS

In recent years, internet of things (IoT) technology has shown great potential in the health care sector through different wearable sensors. Monitoring various health parameters like body temperature, blood pressure, heartbeat, oxygen level, and sugar level is very important for being proactive against chronic and pandemic diseases. Monitoring patients is a great challenge during pandemic diseases since doctors and other medical practitioners are exposed to risk. This paper presents a novel touchless health and patient monitoring system embedding ultra-wideband (UWB) and IoT technolo-gies for effective monitoring of COVID-19 patients. The IoT module is specifically designed for health monitoring whereas UWB radar is designated for effective touchless patient monitoring. The IoT module comprises a temperature sensor, heartbeat sensor, and pulse oximeter, which sense and store the information in the Internet cloud, which can then be accessed through mobile and web applications. UWB radar is integrated with the system for touchless patient monitoring. The proposed system is also embedded with a heath-assisting module that allows patients to interact with doctors after receiving their health parameters through the mobile bot application termed IOT FIT BOT. A mobile application and a web-based graphical user interface are developed to receive sensed data immediately. Thus the proposed system provides effective health monitoring along with live health assistance, and more importantly, the system offers touchless patient monitoring, which will be a promising solution for medical professionals during pandemic situations like COVID-19. © 2022 by Begell House, Inc.

Trajectory and Attitude Measurement of Skier based on MINS/UWB Integration for Indoor Intelligent Skiing System

The 2022 Winter Olympics bid success promoted the development of the ice and snow sports in China. The emergence of indoor skiing system drives the ski and snow sports into a highly developed period especially at the normal prevention and control stage of COVID-19. However, the conventional indoor skiing system is insufficient in sports experience and inability to track the skier trajectory and attitude for training. Fortunately, the Ultra-Wide Band (UWB) and Micro Inertial Navigation System (MINS) are widely used in indoor environments due to high-precision positioning and low-cost priorities. UWB presents high accuracy in positioning, while it is easily to be disturbed by the Non Line of Sight (NLOS) and multipath effects. Meanwhile, the MINS error would accumulate with time. Therefore, this paper proposed a MINS/UWB integration algorithm to implement the trajectory and attitude measurement of the skier with low-cost. Meanwhile, the MINS/UWB based Extended Kalman Filter (EKE) is designed with sequential algorithm for skiing. Finally, both the indoor positioning experiment and the intelligent skiing system verification experiment were carried out to verify the accuracy of MINS/UWB integration system. Experimental results show the MINS/UWB integration technology could locate effectively When the UWB signal is intermittently blocked.

UWB Sensor Assisted Self-Quarantined Person Health Status Monitoring using LSTM

The severe acute respiratory syndrome virus (SARS-CoV-2), known as COVID-19, has brought untold hardship and deaths all over the world. Individuals affected by COVID-19 often experience respiratory difficulties along with fever, cough, and other symptoms. Social distancing and self-quarantine are strongly suggested by researchers to avoid the exponential spread of the disease. The ultra-wideband (UWB) sensor has recently offered remote monitoring and capturing respiratory signs by ensuring privacy. In this work, a UWB sensor is employed to observe the movement and respiration of a home-quarantined person for fourteen days. After collecting the information in real-time, a deep learning (DL) approach, the long-term short memory (LSTM) framework is further applied to detect the breathing and movement patterns. The experimental result depicts that the framework accomplished 99.93% accuracy with 2 misclassification costs. The proposed application shows promising possibilities into the Internet of medical things (IoMT), smart home health care support system (ShHeS), and practical use in COVID-19 pandemic emergency.

Stealth Communication (SC) for 5G/6G Wireless to ensure spectral efficiency and privacy/cybersecurity

This paper presents a review on the state-of-the-art of 'Stealth Communication' (SC), focused on potential applications in 5G/6G. SC is a new wireless system aimed at enhancing spectral efficiency and cybersecurity/privacy based on employing Ultra-Wide-Band (UWB) RF signals that mimic noises in wave form and below-noise-level at the receiver frontend. For 5G/6G applications, Same Frequency (SF) Simultaneous Transmit and Receive (STAR) operating bandwidth covering 400 MHz to 11 GHz, and their Technology Readiness Level, are discussed. Implementation of SC in 5G/6G, held back so far by high costs and Covid-19, should be able to gain enough momentum under the thrusts of rising cyber attacks in 2021. © 2021 IEEE.

Distance Estimation for BLE-based Contact Tracing - A Measurement Study

Mobile contact tracing apps are - in principle - a perfect aid to condemn the human-to-human spread of an infectious disease such as COVID-19 due to the wide use of smartphones worldwide. Yet, the unknown accuracy of contact estimation by onboard wireless technologies in real use hinders their broader employment. We address this challenge by conducting a measurement study with a custom testbed to show the capabilities and limitations of Bluetooth Low Energy (BLE) in different scenarios. Distance estimation is based on interpreting the signal pathloss with a basic linear and a logarithmic model yielding an accuracy of 2-4 m. Further, we compare our results with accurate ultra-wideband (UWB) distance measurement, which is able to reduce the distance error to 0.9 m. While the BLE distance error may not seem sufficiently accurate, we show that a simple threshold-based contact detector achieves an F1-score accuracy of 64%, which can be improved to 69% when the carrying position of the phone is known. It is further shown that multi-path signal propagation reduces the effect of body shielding and thus increases detection accuracy in indoor scenarios. © 2021 IEEE

Covid-19 Prevention Kit Based on an Infrared Touchless Thermometer and Distance Detector

Temperature is estimated by detecting the infrared radiation emitted by all materials above absolute zero (0°Kelvin) in an infrared temperature test. IR energy is converted to an electrical signal that may be displayed as a temperature reading after being made up for the surrounding temperature range by using a focal point to focus the IR energy on a finder. With this set-up, you can estimate something's temperature from a distance, without having to go close to the thing you're trying to measure. Because thermocouples or other test type sensors cannot be used or do not provide precise information for a variety of reasons, the infrared temperature sensor is useful for estimating temperature. One of the most essential things to do to avoid COVID is to practise social distancing. This device may be used to maintain a gap of at least 6 feet between devices by measuring distance using ultra-wideband (UWB) technology. There are two nodes in an ultrasonic sensor: a transmitter and a receiver. When the transmitter fires, an ultrasonic wave is thrown out, and this wave hits everything in its path before returning to the transmitter. Using the time it takes for the wave to return to the sensor after being bounced, the sensor determines the obstacle's distance from that sensor. In most cases, ultrasonic sensors are used to detect obstacles in the way and to determine how far away they are from the sensor. © 2021 IEEE.

Real-Time People Counting Using IR-UWB Radar

COVID-19 pandemic has introduced social distance regulations which are crucial to be followed by. In order to maintain proper social distancing, it is critical to regulate the number of people in a closed space. In this paper, we propose a people counting system based on Impulse Radio Ultra-Wideband radars for counting people walking through a doorway. The system uses two IR-UWB radars placed horizontally apart to create a lag effect when someone walks by the radars. This enables detection of movement’s direction and subsequently, determination of the number of people in a room. The system proposed can be used for people counting in real-time and also on saved data which offers flexibility for real world applications. Several tests were conducted which shows the accuracy rate of system to be around 90%, validating the system. Contrary to conventional vision based people counting system, the proposed system is not limited by environmental factors such as light and also is privacy oriented. © 2022, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

A survey into COVID-19 Induced Pneumonia Detection and Feasibility of using UWB Medical Imaging

This paper presents a survey into the currently thriving research on using machine learning for COVID-19 induced pneumonia detection through the use of radiographic scans, presents a brief review of the methodologies and assesses the classification results, and finally presents an alternative in the form of ultrawideband (UWB) imaging. Few works on UWB imaging is investigated and used as a source of inspiration for developing an UWB imaging system for detection of accumulation of fluid in lungs. The goal is to extract information about dielectric property variation from backscattered UWB signals to detect pneumonia caused by COVID-19. An edge fed Vivaldi antenna along with a multilayer planar model for lung is simulated in CST microwave studio and subjected to UWB excitation. The backscattered signals in the form of S-parameters are analyzed with various Delay-and-Sum (DAS) algorithms and images are constructed for lung tissues of different permittivity and conductivity, where higher values are supported to allude to the infected lungs. ©AJSE 2021.

Quad-port MIMO Filtenna with High Isolation Employing BPF with High out of Band Rejection

A quad-port multiple-input multiple-output (MIMO) filtenna with compact dimensions of 50 ×50 mm2 are configured, in which each element is placed orthogonally to its adjacent to enhance the isolation. The MIMO element is configured based on the novel COVID-19 virus shape with a co-planar waveguide feeding structure (CPW) and dimensions 17 ×22 mm2. The element bandwidth is ranging from 3.3 GHz to more than 60 GHz. Three frequency notches are designed at 3.5 GHz for WiMAX and 5.5 GHz for WLAN, and 8.5 GHz for X-band applications. A bandpass filter (BPF) with high out of band rejection is used as a decoupling structure (DS) to improve the isolation to more than 30 dB across most of the bandwidth. The equivalent circuit model is scrutinized to investigate the enactment of the decoupling structure. The proposed MIMO filtenna system provides an impedance bandwidth of 2.4–18 GHz, a peak gain of 13.2 dBi, and an envelope correlation coefficient (ECC) less than 0.00021. In turn, channel capacity loss does not exceed 0.2. The MIMO filtenna is fabricated and measured. Good agreement between the measured and simulation results is achieved. Author

CIR-Based Device-Free People Counting via UWB Signals.

The outbreak of COVID-19 has resulted in many different policies being adopted across the world to reduce the spread of the virus. These policies include wearing surgical masks, hand hygiene practices, increased social distancing and full country-wide lockdown. Specifically, social distancing involves keeping a certain distance from others and avoiding gathering together in large groups. Automatic crowd density estimation is a technological solution that could help in guaranteeing social distancing by reducing the probability that two persons in a public area come in close proximity to each other while moving around. This paper proposes a novel low complexity RF sensing system for automatic people counting based on low cost UWB transceivers. The proposed system is based on an ordinary classifier that exploits features extracted from the channel impulse response of UWB communication signals. Specifically, features are extracted from the sorted list of singular values obtained from the singular value decomposition applied to the matrix of the channel impulse response vector differences. Experimental results achieved in two different environments show that the proposed system is a promising candidate for future automatic crowd density monitoring systems.

Contact and Remote Breathing Rate Monitoring Techniques: A Review.

Breathing rate monitoring is a must for hospitalized patients with the current coronavirus disease 2019 (COVID-19). We review in this paper recent implementations of breathing monitoring techniques, where both contact and remote approaches are presented. It is known that with non-contact monitoring, the patient is not tied to an instrument, which improves patients' comfort and enhances the accuracy of extracted breathing activity, since the distress generated by a contact device is avoided. Remote breathing monitoring allows screening people infected with COVID-19 by detecting abnormal respiratory patterns. However, non-contact methods show some disadvantages such as the higher set-up complexity compared to contact ones. On the other hand, many reported contact methods are mainly implemented using discrete components. While, numerous integrated solutions have been reported for non-contact techniques, such as continuous wave (CW) Doppler radar and ultrawideband (UWB) pulsed radar. These radar chips are discussed and their measured performances are summarized and compared.

An Overview of Signal Processing Techniques for Remote Health Monitoring Using Impulse Radio UWB Transceiver.

Non-invasive remote health monitoring plays a vital role in epidemiological situations such as SARS outbreak (2003), MERS (2015) and the recently ongoing outbreak of COVID-19 because it is extremely risky to get close to the patient due to the spread of contagious infections. Non-invasive monitoring is also extremely necessary in situations where it is difficult to use complicated wired connections, such as ECG monitoring for infants, burn victims or during rescue missions when people are buried during building collapses/earthquakes. Due to the unique characteristics such as higher penetration capabilities, extremely precise ranging, low power requirement, low cost, simple hardware and robustness to multipath interferences, Impulse Radio Ultra Wideband (IR-UWB) technology is appropriate for non-invasive medical applications. IR-UWB sensors detect the macro as well as micro movement inside the human body due to its fine range resolution. The two vital signs, i.e., respiration rate and heart rate, can be measured by IR-UWB radar by measuring the change in the magnitude of signal due to displacement caused by human lungs, heart during respiration and heart beating. This paper reviews recent advances in IR- UWB radar sensor design for healthcare, such as vital signs measurements of a stationary human, vitals of a non-stationary human, vital signs of people in a vehicle, through the wall vitals measurement, neonate's health monitoring, fall detection, sleep monitoring and medical imaging. Although we have covered many topics related to health monitoring using IR-UWB, this paper is mainly focused on signal processing techniques for measurement of vital signs, i.e., respiration and heart rate monitoring.