Intelligent Surface-Enhanced Raman Scattering Sensor System for Virus Identification

COVID-19 has devastated the entire world for the past couple of years. Timely and efficient detection and identification of a virus are crucial in preventing the wider virus spread. By using intelligent sensors based on Surface-Enhanced Raman Scattering (SERS), it is possible to detect and identify virus automatically. In this study, we successfully applied the XGBoost Algorithm (Supervised Machine Learning) to classify the type of the virus using the SERS sensor data. The supervised approach has a limitation when a new type of virus arises, whose shape is different from the previously known samples. To tackle this problem, we investigated the unsupervised learning approaches that can cluster the virus data into different groups without labeled data. The unsupervised approach presented in this paper is called k-Shape Clustering. This technique compares the cross-correlation between different samples and then clusters them into similar or different groups. If a subvariant of a virus emerges, it would be clustered into the existing virus groups;if a new type of virus is found, it would be clustered into a new group. Both of the approaches have shown very promising results based on extensive evaluations. © 2022 IEEE.

Demo Paper: A Package Of Objective Measurement Tools For Physical And Social Exertional Activities For Patients With Illness-limiting Capacities

Patients with several incompletely diagnosed and understood chronic diseases suffer from symptoms that limit their functional capacity. In particular, chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME) and long covid syndromes lead to variable fatigue, malaise, poor and unrefreshing sleep, delayed sleep, and post-exertional exacerbation. There are no specific tests for these patients to diagnose their diseases properly. This paper presents a foot-insole sensor system for detecting and measuring physical leg activity, a wrist and arm motion sensor system for dominant arm and hand activity, and a cell phone system for measuring social interaction and noise exposure. © 2022 ACM.

Remote SpO2 Estimation using End-to-End CNN Model

Blood oxygen speed (SpO2) is an indicator of the normal presence or absence of the respiratory function. This is attracting the attention of researchers since it could monitor the patient conditions of the chronic pulmonary diseases and covid-19. Covid-19 patients have the symptom of the significant SpO2 drop. This study tries to develop an early and easy checkup system of the continuous SpO2 using an RGB camera. Unlike the contact SpO2 measurement using the conventional optical sensor on a fingertip, the remote SpO2 sensor system is proposed using the facial video stream. The facial images are trained for the convolutional neural networks to implement the non-contact SpO2 estimation model, which is designed based on the architecture of the conventional remote photoplethysmography model. © 2022 IEEE.

Optimised distributed sensor system for covid protocol monitoring using multiprocessor architecture

Covid Protocol Monitoring with Multiprocessor Architecture (CPMMA) is proposed in this study as an approach for implementing a Distributed Sensor System (DSS) for covid protocol monitoring utilising multiprocessor architecture. OpenMP and MPI were used to implement the distributed system's parallel programmes, with the OpenMP code working best when used with 60–100 threads in use. CPMMA distributed sensor data was efficiently processed by a multiprocessor with 16 cores. According to the results, using a multithreaded-multiprocessing architecture and optimised Support Vector Machine classifier, the proposed design greatly enhances computing efficiency. The results of our experiments suggest that our approach may significantly enhance computing performance while also delivering adequate outcomes in a short period of time.

Covid-19 Interior Security Tracking System Based on the Artificial Intelligence

This article presents an inexpensive artificial intelligence solution aimed at increasing indoor safety of COVID-19, including a number of important aspects: (1) breakdown of the process (2) Method for mask identification (3). Assessment methodology of social distancing The Arduino Uno sensor system uses an infrasound sensor or heat camera, whereas the Raspberry Pi is equipped with computer vision technologies for mask detection and social distance checks. Indoor measures are the most prevalent—people with a high body heat should stay at home, masks should be worn, and their distance should be at least 1.5–2 m. In the first case, the Arduino Uno temperature sensor board is utilized, while we utilize a single-board Pi Raspberry computer coupled with camera for two additional situations, using computer vision techniques. Due to their compact size and cost, we chose to utilize these devices. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

The Evaluation of the Impacts on Traffic of the Countermeasures on Pandemic in Istanbul

Governments have taken various countermeasures to slow down the effect of the Covid-19 virus, which has affected the whole world since the beginning of 2020. This study aims to evaluate the impacts of the countermeasures taken by the government on travel behavior in Istanbul, Turkey, through a large-scale survey (approx. 150.000 respondents), remote traffic microwave sensor (RTMS) and transit system electronic toll collection (ECT) data. The countermeasures have been taken by the governments were all day on weekends and between 9 pm and 5 am on weekdays, closure of the restaurants, cafes except take away, stepwise working hour measure and determination of the working hour between 10 am and 4 pm. The survey was developed to allow electronic surveys to be designed on a word processor, sent to, and conducted on standard entry level mobile phones. As a result of the survey, it is estimated that there is a 9% increase in the use of private vehicles, and the road traffic congestion is expected to be increased accordingly. Despite the stepwise working hour measure of the government, the morning and evening peak hours of the traffic did not change. Also, the number of vehicles before and during the pandemic passing through the Bosporus via two bridges which connect the two continents and are the main transportation corridor of Istanbul, is analyzed. According to the November, 2020 data, the number of the vehicles has decreased by almost 14% on weekdays in comparison with the data of November, 2019 for both bridges. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

A Low-Cost Control Occupancy Solution Using a Time-of-Flight Ranging Sensor Laser

The pandemic situation has driven to several measures to prevent the spread of COVID-19. One of these measures is social distance and, as a consequence, limitation of capacity of indoor closed spaces. This makes necessary the deployment of systems that help to control occupancy of spaces. This work proposes a low-cost system to control access to an indoor closed space with a single door. The system is based in a two laser Time-of-Flight sensors VL53L0X over a HiLetgo UNO R3D1R32 ESP32 micro-controller. The system counts the occupancy of the room and share it with a database and a dashboard, using Node-RED. The tested prototype shows a 86.6% reliability that increases to a 100% reliability when users are informed to enter or exit one by one. The main contributions of this work are: to control capacity of one-entrance indoor closed space with a low cost open system;and to record occupancy of the room in order to analyse it behaviour with time. © 2021 Copyright for this paper by its authors.

Wireless Battery-Free Body Temperature Sensing Device for Key Workers

We propose a battery-free temperature monitoring device that can be fitted inside the ear for an accurate body temperature measurement of a subject. The proposed application consists of two primary systems: 1) a battery-free temperature sensing ultra-high-frequency radio frequency identification sensory tag and 2) an auxiliary energy harvesting system, which enhances the sensing device's measurement accuracy and precision. The system can record changes in the localized body temperature of authenticated users with an average latency of 501 ms. The assembly demonstrated a temperature average accuracy of +/- 0.14 degrees C operating at 866 MHz. The system performance demonstrated high stability and repeatability of reported temperature measurements. The device's dimension is a form factor that can easily fit in a front shirt pocket, with a wire tethered earbud temperature sensor. The system is developed to make sensor measurements without requiring a battery for the device. Measurements are made remotely as users pass by checkpoints installed throughout a building. The device is a cost-effective solution for monitoring body temperature in work environments.