Development of Data Logger for COVID Vaccine Temperature Monitoring System

The Data Logger (DL) is a unique tool created to carry out the typical duty of gathering data in a specific area. This common task can include measuring humidity, temperature, pressure or any other physical quantities. Due to the current pandemic situation, its use in temperature monitoring of Covid vaccine will be crucial. According to World Health Organization (WHO) guidelines, COVID vaccine can be stored and transported at -80 °C, -20°C and +2-8°C and shelf life is reduced as vaccine is transferred from one storage temperature to another. So cost effective, efficient and standalone Data Logger (DL) is the need of the hour. The Data logger is proposed to be developed with the use of ESP8266 Node MCU microcontroller. It takes power from a 5V Battery. DS18B20 sensor will be used for temperature sensing. Here we will use Wi-Fi module of ESP8266 Node MCU to send the temperature data from sensor to the Google Sheet over the internet. This real time data will be stored in the format of time and month/date/year. Data logged in Google Sheet will be displayed to the user with the help of graphical user interface (GUI) which is developed using PYTHON scripting language. GUI will allow user to interact with Data Logger through visual graphs. The Data Logger components are mounted on a double layered PCB. © 2022 IEEE.

A Low-Cost Wireless Body Area Network for Human Activity Recognition in Healthy Life and Medical Applications

Moved by the necessity, also related to the ongoing COVID-19 pandemic, of the design of innovative solutions in the context of digital health, and digital medicine, Wireless Body Area Networks (WBANs) are more and more emerging as a central system for the implementation of solutions for well-being and healthcare. In fact, by elaborating the data collected by a WBAN, advanced classification models can accurately extract health-related parameters, thus allowing, as examples, the implementations of applications for fitness tracking, monitoring of vital signs, diagnosis, and analysis of the evolution of diseases, and, in general, monitoring of human activities and behaviours. Unfortunately, commercially available WBANs present some technological and economic drawbacks from the point of view, respectively, of data fusion and labelling, and cost of the adopted devices. To overcome existing issues, in this paper, we present the architecture of a low-cost WBAN, which is built upon accessible off-the-shelf wearable devices and an Android application. Then, we report its technical evaluation concerning resource consumption. Finally, we demonstrate its versatility and accuracy in both medical and well-being application scenarios. Author

Impact of COVID-19-Related Travel Restrictions on the Environment and Travel Time Reliability

This study analyzes the effect of the restrictions in traffic movement enforced in order to combat the spread of coronavirus on air quality and travel time reliability under heterogeneous and laneless traffic conditions. A comparative analysis was conducted to examine quantity of pollutants, average travel time distributions (TTD), and their associated travel time reliability (TTR) metrics during the COVID-19 pandemic, postpandemic, and during partial restrictions. Pollutants data (PM2.5, NO2, and NOX) and travel time data for selected locations from Chennai City in India were collected for a sample period of one week using Wi-Fi sensors and state-run air quality monitoring stations. It was observed that the average quantity of PM2.5, NO2, and NOX were increased by 433.1%, 681.4%, and 99.2%, respectively, during the postlockdown period. Correlation analysis also indicated that all considered air pollutants are moderately correlated to Wi-Fi hits, albeit to varied degrees. From the analysis, it was also found that average TTD mean and interquartile range values were increased by 47.2% and 105.2%. In addition, the buffer time index, planning time index, travel index, and capacity buffer index associated with these TTD metrics were increased by 148.1%, 63.7%, 42.8%, and 202.9%, respectively, soon after relaxing travel restrictions. © 2023 American Society of Civil Engineers.

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.

CRISIS: Cyber-Physical Social Distancing Based on Multi-Modal Data From Mobile Devices

Multi-modal sensors on mobile devices (e.g., smart watches and smartphones) have been widely used to ubiquitously perceive human mobility and body motions for understanding social interactions between people. This work investigates the correlations between the multi-modal data observed by mobile devices and social closeness among people along their trajectories. To close the gap between cyber-world data distances and physical-world social closeness, this work quantifies the cyber distances between multi-modal data. The human mobility traces and body motions are modeled as cyber signatures based on ambient Wi-Fi access points and accelerometer data observed by mobile devices that explicitly indicate the mobility similarity and movement similarity between people. To verify the merits of modeled cyber distances, we design the localization-free CybeR-physIcal Social dIStancing (CRISIS) system that detects if two persons are physically non-separate (i.e., not social distancing) due to close social interactions (e.g., taking similar mobility traces simultaneously or having a handshake with physical contact). Extensive experiments are conducted in two small-scale environments and a large-scale environment with different densities of Wi-Fi networks and diverse mobility and movement scenarios. The experimental results indicate that our approach is not affected by uncertain environmental conditions and human mobility with an overall detection accuracy of 98.41% in complex mobility scenarios. Furthermore, extensive statistical analysis based on 2-dimensional (2D) and 3-dimensional (3D) mobility datasets indicates that the proposed cyber distances are robust and well-synchronized with physical proximity levels. © 2002-2012 IEEE.

Non-Cooperative Game for Edge Server Placement in Wireless Body Area Network

The outbreak of the coronavirus disease 2019 (COVID-19) has become the worst public health event in the whole world, threatening the physical and mental health of hundreds of millions of people. However, because of the high survivability of the virus, it is impossible for humans to eliminate viruses completely. For this reason, it is particularly important to strengthen the prevention of the transmission of viruses and monitor the physical status of the crowd. Wireless sensors are a key player in the fight against the current global outbreak of the Covid-19 pandemic, where they are playing an important role in monitoring human health. The Wireless Body Area Network (WBAN) composed of these wireless sensor devices can monitor human health data without interference for a long time, and update the data in almost real time through the Internet of Things (IoT). However, because the data monitored by the devices is relatively large and the transmission distance is long, only transmitting the data to medical centers through the personal devices (PB) cannot get feedback in time. We propose a non-cooperative game-based server placement method, which is named ESP-19 to improve the efficiency of transmission data of wireless sensors. In this paper, experimental tests are conducted based on the distribution of Shanghai Telecom's base stations, and then the performance of ESP-19 is evaluated. The results show that the proposed method in this paper outperforms the comparison method in terms of service delay. © 2022 IEEE.

Smart Social Distancing Robot for COVID Safety

Social distancing plays an indispensable part during the ongoing pandemic. In this period, maintaining social distancing standards between people has turned into essential insurance to dial back the spreading of COVID-19. We present an original technique to recognize matches consequently of people in a jam-packed situation individuals do not maintain the social distance restriction, which calls for about 3 ft of space between them. This project assists in restricting the spread of the coronavirus by noticing the distance between disease-spreading people. Presently, it is absurd to expect to station an individual 24 × 7 at each line to screen social separating distance violations. For instance—banks, public offices, malls, schools, theatres, and so forth typically see long lines for hours consistently. To ensure social distancing in lines, this robot aids in monitoring the social distancing. Accordingly, this robot aids in maintaining the social distance between the crowd in a public environment to assist and forestall the spread of the virus. This robot serves to be an economical solution in public places where the gathering of people is significantly high. With appropriate obstacle detection, and crowd monitoring the official are also kept updated due to the Wi-Fi and IoT technology incorporated into a robot. This robot is expected to serve as a good solution in this pandemic time. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Wireless LAN Operation and Behavioral Inferences from Usage Analysis

The majority of network connections on campus is shifting from wired to wireless. Understanding and analyzing the usage of wireless LANs can lead us beyond mere network management to the analysis of users' behavior on campus and the discovery of new insights. In 2022, campus activity has returned to levels seen before the pandemic, but the effects of the COVID-19 disaster remain. Compared to pre-pandemic years, the use of wireless LANs on campus has increased significantly due to high smartphone ownership rates and the promotion of distance learning reliant on personally owned devices (BYOD). The use of multiple devices per person has also increased, creating new issues such as congestion and IP allocation problems. To accurately understand and improve these situations, we are collecting and analyzing connection information of our wireless LAN systems. Interestingly, our analysis of wireless LAN use provides information beyond the mere discovery of technical problems. From the results, we were able to identify ways we might improve the operation of the wireless LAN, as well as information to make inferences about the time spent by students on campus, their flow lines, and their behavior patterns. In this paper, we will report on the current status of the operation of the wireless LAN at Fukuoka University and the behavioral information inferred from our analysis of wireless LAN usage. © 2023 Owner/Author.

That Birdie Feeling: Understanding the Role of LAN Organizers in Maintaining a Gaming Community

This paper presents the initial findings of a longitudinal study examining the role and experiences of LAN organizers in managing player communities pre, during and post the Covid 19 pandemic. Interpretative Phenomenological Analysis was used to analyze interviews with organizers of the Birdie LAN, Sweden's longest running LAN event. Five key themes were identified reflecting the roles of organizers and their experiences pre pandemic. (1) building and maintaining the culture, (2) encouraging inclusivity and community building, (3) negotiating professionalism, (4) learning, adapting and evolving, (5) creating sustainability through a future orientation. This paper presents the results of the first data collection to examine the impacts of the pandemic on grassroots gaming communities. The findings here represent a foundation in understanding the role of community leaders in maintaining a culture around gaming. These initial findings add value to our understanding of grassroots esports and player communities and the social practices of gaming in the modern era. © 2023 IEEE Computer Society. All rights reserved.

Smart Social Distancing Robot for COVID Safety

Social distancing plays an indispensable part during the ongoing pandemic. In this period, maintaining social distancing standards between people has turned into essential insurance to dial back the spreading of COVID-19. We present an original technique to recognize matches consequently of people in a jam-packed situation individuals do not maintain the social distance restriction, which calls for about 3 ft of space between them. This project assists in restricting the spread of the coronavirus by noticing the distance between disease-spreading people. Presently, it is absurd to expect to station an individual 24 × 7 at each line to screen social separating distance violations. For instance—banks, public offices, malls, schools, theatres, and so forth typically see long lines for hours consistently. To ensure social distancing in lines, this robot aids in monitoring the social distancing. Accordingly, this robot aids in maintaining the social distance between the crowd in a public environment to assist and forestall the spread of the virus. This robot serves to be an economical solution in public places where the gathering of people is significantly high. With appropriate obstacle detection, and crowd monitoring the official are also kept updated due to the Wi-Fi and IoT technology incorporated into a robot. This robot is expected to serve as a good solution in this pandemic time. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

IoT-Based E-Parking System for Multiplexes and Shopping Malls

This paper helps in automating process of car parking in shopping malls. It helps in making parking more efficient by burning of less fuel. This system is useful for places with large number of people considering less people-to-people contact considering Covid Pandemic and making a safe system for minimal infection transmission from people to people. This paper aims at developing a IoT-based E-parking system. This project uses Micro-controller (ATtiny85) for controlling of sensors. Set of multiple ultrasonic sensors are put on ceilings per floor with multiple slots for detection of vehicles in parked spaces with threshold set for cars. Multiple Wi-Fi modules are used for wirelessly uploading the values of vehicles parked in different floors to cloud from where the Wi-Fi module at entrance extracts data and displays on central display at entrance for assigning empty parking slots to new vehicles on arrival. Entrance display displays number of empty slots on every floor to new customer entering mall parking system. This project achieved objective of making a system which can be used in times of Covid-19 for better safety of people. This paper has been able to achieve its main objectives of making a safe, affordable, scalable parking system which can be used in shopping malls and multiplexes. It can be scaled to large usable parking systems using better sensors and better computing devices. It can provide means of work or business to youth of city for building and selling smart vehicle parking systems and deploy them to multiple malls and multiplexes using help from staff and sell at affordable rates. It can also help make more customizable and modular smart parking systems tailored to use of system in any buildings. Arduino IDE has been used for uploading code to cloud modules in project. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Smart Energy Meter with Cloud Connectivity

The main tools for allowing customers to communicate openly and transparently with the company and other stakeholders are their electricity bills. However, last year due to pandemics, some residents petitioned the Madras high court claiming TANGEDCO's technique to measure power was arbitrary and unreasonable during the lockdown that COVID provoked. This was done amid complaints about excessive electricity bills. When compared to bills from other states, TANGEDCO's white meter card for energy bills is found to provide insufficient information on use and rates, according to a survey by the certain associations. Power bills urgently need to be redesigned to include comprehensive billing details and accurate assessments of electricity consumption from closed homes or homes in restricted zones. [4] We proposed and designed a Smart Home Energy Meter Monitoring System to solve this crisis. It consists of three systems. First system: Customized built energy meter with LCD. [6] Second system: Wi-Fi module with the Microcontroller (ATMega328P) and an alert system. Third system: Database (MySQL database). [12] The quantity of power used by the device is measured by an energy meter user and every two months, the final reading of the power consumption is taken by the micro controller where the electricity bill calculation program has been pre-programmed to give the value of power consumed during the two months and amount to be paid by the user and [4] It will be shown on the Energy Meter's LCD. The micro controller with a built-in Wi-Fi module (ESP8266) will send these displayed data to the service provider's database. [2] An alert system has been added to counteract the hefty usage and electricity bills to create awareness to the consumer about the slab-wise tariffs increase in the per-unit cost data that has been set by TANGEDCO. [10] The alert has been set in a way that the consumer receives a message for every 200 unit usage of power. The third system is a database created using MySQL database to transport the data to the service provider. © 2022 IEEE.

CoviBand - Wearable Social Distancing and Contact Tracing Device Using Signal Strength Indicator Metrics

The Covid-19 pandemic has grown to be a highly hazardous threat to the survival of most of the human race. It has not only caused prolonged stay-at-home or lockdown policies in many countries but has also been eating away from the global economy. Staying at home for long durations has affected the lives of daily wage workers tremendously and has also had negative consequences on the mental health of many. This paper aims to reduce the risk of contracting the disease when people leave their homes for essential services and during the gradual lift of the lockdown restrictions. This is achieved through a wearable device (wristband) which constantly looks for other wristbands in the vicinity using a WiFi module. This WiFi module is inbuilt into a NodeMCU Amica board and the setup is used in addition to a buzzer which sounds an alarm when two wristbands are dangerously close. In addition to the warning feature using the buzzer, the device would also store the contact history and the duration of contact on a remote server which can then be used for contact tracing in case a person is found to test positive for Covid-19. The interface of the remote server would be such that it gives a detailed list of the other wristbands that came into contact with any particular wristband. This device would also have an edge over some of the contact tracing apps as many people fear that these apps are an invasion of privacy and drain their mobile batteries quickly. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Real-Time Tracking of Health Parameters Using IOT and Data Logger: Application to COVID-19

There is an alarming upward trend in COVID-19 cases, and the existing healthcare system is unable to cater the day-to-day requirements from testing followed by appropriate patient care. The use of monitoring devices has found the importance of detecting the presence of the virus early. In order to expand the exciting monitoring system, every technocrat needed to come forward and donate his money to this. Authors as a responsible persons deemed it proper to work on the development design of multipurpose all in one reliable device to help the front like warriors in identifying persons with COVID-19 symptoms like temperature, heartbeat, humidity and positioning real time. After putting in an extra effort, author has succeeded in translating my idea into action. A device that is so well-designed and will increase the medical brotherhood effort to continue monitoring patient health parameters using a variety of sensors connected to the Arduino board. The generated data is then transmitted via Wi-Fi module to IOT platform, i.e., ThingSpeak and which can be monitored on devices like desktop, laptop or smartphone. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Expert Systems for Improving the Effectiveness of Remote Health Monitoring in COVID-19 Pandemic: A Critical Review

COVID-19 is an infectious disease caused by SARS-CoV-2 virus. It has disrupted the normal life of people, medical infrastructure, and economy globally. Remote health monitoring is a better option in pandemic diseases such as COVID and Ebola virus. Remote health monitoring can be enhanced by effectively using various recent advancements in technology. Technological advancements such as Wireless Body Area Networks (WBAN), Internet of Things (IoT), Artificial Intelligence (AI), and medical robotics for improving the effectiveness of remote health monitoring in COVID-19 pandemic are reviewed and presented in this chapter. Building expert systems using WBAN, IoT, AI, and robotics is an optimal choice to remote monitor COVID and reduce infection spread and mortality. Detailed architecture, use cases, impacts, workflow, applications, and future directions toward building a better expert system is highlighted in this chapter. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

Monitoring Engagement in Online Classes Through WiFi CSI

Due to the Covid-19 pandemic, people have been forced to move to online spaces to attend classes or meetings and so on. The effectiveness of online classes depends on the engagement level of students. A straightforward way to monitor the engagement is to observe students' facial expressions, eye gazes, head gesticulations, hand movements, and body movements through their video feed. However, video-based engagement detection has limitations, such as being influenced by video backgrounds, lighting conditions, camera angles, unwillingness to open the camera, etc. In this work, we propose a non-intrusive mechanism of estimating engagement level by monitoring the head gesticulations through channel state information (CSI) of WiFi signals. First, we conduct an anonymous survey to investigate whether the head gesticulation pattern is correlated with engagement. We then develop models to recognize head gesticulations through CSI. Later, we plan to correlate the head gesticulation pattern with the instructor's intent to estimate the students' engagement. © 2023 IEEE.

Wi-Fi Based Touchless Bell Ringing System for Temples

Due to the dread of the pandemic Covid-19 spreading, everyone is staying away from public properties in today's situation. People are even afraid of ringing temple bells, which is a gesture of devotion. Even if they desire to ring the bell, the pandemic prevents them from doing so. The people will be able to ring the temple bell without having to touch it at all owing to this project. The main components employed in this project are an Arduino UNO R3 and ESP8266 boards. An ultrasonic sensor is linked to one ESP8266 board, and it identifies persons when they come within the designated distance range. A relay is attached to the Arduino UNO, which is then connected to a motor. When a person enters the range of the ultrasonic sensor, the ultrasonic sensor sends a message to the relay via the Wi-Fi connection created between the ESP8266 1 and ESP8266 2. As the temple bell is connected to the motor, it will ring automatically after the relay and motor work in sequence. This effort will assist people in fulfilling their religious obligations without constraint. © 2022 IEEE.

A Large-Scale IoT-Based Scheme for Real-Time Prediction of Infectious Disease Symptoms

In recent decades, many infectious diseases have appeared that have negatively affected life in general and people in particular, causing many economic and human losses. Recently, many attempts have emerged to confront these diseases using computer-based technology for diagnosis, prediction, and data analysis using various techniques, the most important of which is deep learning. Previous research relied primarily on a set of images taken from the patient's body while he was in a healthcare facility, and this is the main weakness of these studies. Not all people go to a doctor or hospital when they feel the symptoms of a disease. Hence, people moving in crowded places without knowing their health status can contribute to spreading infectious diseases quickly, and this is the issue that should be confronted. Therefore, this paper presents a people-monitoring scheme, which is based on the internet of things (IoT) technology, to predict infectious disease symptoms through people's behavior as well as through a wireless body area network (WBAN). This scheme can predict the spread of disease by tracking the movements of infected persons. Additionally, a simple methodology for processing the data extracted from the monitoring process across a range of different computing centers is introduced. Moreover, to ensure the monitoring scheme operates in real-time, it was necessary to provide a powerful coverage model for its objects. Also, a simple COVID-19 case study is presented. Finally, the performance of the prediction model is measured using images, sounds and videos files. Furthermore, the performance of the data computing and coverage methodologies is measured using an intensive simulation environment for the IoT that was constructed using NS3 package. The results showed that the proposed scheme is able to predict the symptoms of disease and its spread with accepted level of accuracy. In addition, using a mixture of coverage tools and computing techniques is recommended. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Behaviour Analysis of Izmir Residents Using Public Wi-Fi Access Point Usage

The wide distribution of access points in Izmir allows the collected information to be employed in smart city algorithms. In this study, we analyze the information that has been made publicly available by Izmir Metropolitan Municipality. We first show that the data is reliable, then analyze it from the perspectives of holidays, seasonal trends, and the COVID-19 pandemic. The study also shows that the information can be used for crowd analysis and forecasting, using K-means and SARIMA algorithms, respectively. © 2022 IEEE.

Solving resource forecasting in WiFi Network by NeuralProphet

Time series forecasting needs several approaches such as data pretreatment, model construction, etc. During the covid 19 outbreak, the data is very dynamic, therefore data processing and appropriate modeling are worried. Identifying patterns, recognizing abnormal data points, is one of the first stages to enhancing forecast outcomes. A point is considered an anomalous point when it is far distant from the mean of the data series. In this research, we deploy an automated anomaly detection approach that incorporates data preparation of neuralprophet library. After that, we design a model via neuralprophet to predict data after preprocessing data. The strategy is evaluated on a dataset of the times that public wifi was used every day with the purpose of forecasting the value of the following 30 days. The anticipated outcome is compared with that of Prophet, hybrid AR-LSTM, consequently indicating that the suggested technique in the study offers the best outcomes. © 2022 ACM.