ABSTRACT
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.
ABSTRACT
COVID-19 has influenced the way we utilise the radio spectrum in terms of increasing data rates, the localisation of usage, and the transfer of traffic from urban to rural areas. Most regulators have shown sympathy towards operator requirements, stipulating a range of mitigation actions including allowing technology neutrality and temporary assignments. Internationally, the ITU-R suspended all physical meetings and launched a new global network resiliency platform named 'REG4COVID' to share experiences including those related to spectrum management. It is argued in this chapter that the pandemic has supported the calls for additional unlicensed spectrum for Wi-Fi in the 6 GHz and accelerated the rollout of 5G. Moreover, despite of increasing use of streaming, it is quite difficult to assume that traditional linear TV will be replaced, at least in the near future for a variety of reasons. The pandemic has also raised the question as to whether an innovative assignment model could be used to assign the spectrum instead of auctions, and whether, in some countries where temporary assignments were made, frequencies are kept unutilised or reserved. Concerning international spectrum management, it is expected that WRC-23 will be held on time though there will be some implications for issues such as the regulatory time-limits for bringing into use satellite networks frequency assignments. Finally, it is argued that the pandemic has also demonstrated the importance of flexibility and agility in national spectrum management, and placed spectrum managers in a new position where they were forced to be proactive instead of their traditional reactive role. © 2023 the authors.
ABSTRACT
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.
ABSTRACT
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.
ABSTRACT
The COVID-19 pandemic has caused significant changes in many aspects of daily life, including learning, working, and communicating. As countries aim to recover their economies, there is an increasing need for smart city solutions, such as crowd monitoring systems, to ensure public safety both during and after the pandemic. This paper presents the design and implementation of a real-time crowd monitoring system using existing public Wi-Fi infrastructure. The proposed system employs a three-tiered architecture, including the sensing domain for data acquisition, the communication domain for data transfer, and the computing domain for data processing, visualization, and analysis. Wi-Fi access points were used as sensors that continuously monitored the crowd and uploaded data to the server. To protect the privacy of the data, encryption algorithms were employed during data transmission. The system was implemented in the Sri Chiang Mai Smart City, where nine Wi-Fi access points were installed in nine different locations along the Mekong River. The system provides real-time crowd density visualizations. Historical data were also collected for the analysis and understanding of urban behaviors. A quantitative evaluation was not feasible due to the uncontrolled environment in public open spaces, but the system was visually evaluated in real-world conditions to assess crowd density, rather than represent the entire population. Overall, the study demonstrates the potential of leveraging existing public Wi-Fi infrastructure for crowd monitoring in uncontrolled, real-world environments. The monitoring system is readily accessible and does not require additional hardware investment or maintenance. The collected dataset is also available for download. In addition to COVID-19 pandemic management, this technology can also assist government policymakers in optimizing the use of public space and urban planning. Real-time crowd density data provided by the system can assist route planners or recommend points of interest, while information on the popularity of tourist destinations enables targeted marketing.
ABSTRACT
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.
ABSTRACT
The concept of IoT in the current world where speed, accuracy and efficiency are of a high importance, can do wonders if implemented in a structured manner, into a machine, project, hardware, idea which can improve technology. So, IoT has its application in the Events. Events can be of many types and there is a need of man power to handle the events efficiently. People gather in huge numbers if there is a political event, whereas there is limited audience in a cultural show or less people in a marriage function. Any of such events, if handled smartly, can ease the tasks of humans, as well as provide speed and accuracy and ensure proper event management and organization. This project demonstrates a hardware for the entry-exit of people for any event, through the technology of Radio Frequency Identification (RFID), Wireless Fidelity (Wi-Fi), and main heart as ESP 8266 Controller. The software simulation in Cisco Packet Tracer shows a general event organization related to a hotel or government-based area, where different sections are integrated to control and handle the event in a smart way. The use of RFID indicates the contactless operation for monitoring the attendee entry-exit, due to the current COVID-19 protocols. So, such systems are safe and smart to execute. © 2022 IEEE.
ABSTRACT
With the outbreak and normal development of COVID-19, the effective detection and recording of body temperature has become a new focus of our attention. At present, there is no complete system to measure temperature, automatic record and specific information at home and abroad. To this end, combined with professional knowledge, our team designed a two-dimensional code scanning and human body temperature automatic recording device with STM32F1 as the core. The device STM32F1 development board is the main control chip. By connecting the WIFI module through the serial port, STM32F1 uses the function of wireless communication. Through the communication protocol, the link between the router and the ESC cloud server of Ali Cloud is utilized. The router or mobile data is transmitted to the user side (APP, applets) according to the specified communication protocol. Inside the development board, the code of each part is written to complete the device integrating code scanning and temperature measurement, which can be displayed and alarm through the node (OLED display screen). This will play a good role in preventing the spread of COVID-19. The system can be used in hospitals, communities, railway stations, shopping malls and many other public places. © 2022 IEEE.
ABSTRACT
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.
ABSTRACT
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.
ABSTRACT
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.
ABSTRACT
Travel restrictions have been imposed among countries since the outbreak of the COVID-19 pandemic. Time delays, budget issues, and poor-quality control in construction projects due to the pandemic have severely affected the construction industry. To reduce the influence of the pandemic, the paper introduces an offshore construction site progress management system with a real case study. With the integration of indoor location-based service technology and image processing method, site superintendents (architect, project director, site manager, engineer) can monitor the site progress easily and pinpoint defects for further investigation and measurement. The visualization of site images together with BIM provides a digital twin platform that can help senior management quickly review the site progress, perform quality checks, and resolve discrepancies in early phases. Positioning of workers and equipment with the adoption of digital maps is a further step in sustainable management. The proposed integration provides a new concept for construction site management during a pandemic and supports the post-COVID-19 new normal in the construction industry. © 2022 International Conference on Construction in the 21st Century. All rights reserved.
ABSTRACT
This article presents the design of an Application in Android operating system, with the aim of monitoring movements in real time through a 2D graphic representation system for a group of Mobile Robots with medical assistance capabilities, in a portable and economical way. In addition, to provide information about the robots positioning in Cartesian coordinates, percentage of current battery and state of operation during their navigation. The robots are link to an Android mobile device through wireless communication in MQTT or WiFi protocol, depending on the technical case available. As a basis of application there is in the first instance a Covid hospital, the need arises as a means of medical assistance between the patient with Covid symptoms and the doctor, nurses and support staff in their treatment and isolation, in order to avoid contact, contagion and the additional expense of wearing special clothing to treat the patient. © 2022 IEEE.
ABSTRACT
BACKGROUND: The COVID-19 pandemic transformed healthcare delivery with the expansive use of telemedicine. However, health disparities may result from lower adoption of telehealth among African Americans. This study examined how under-resourced, older African Americans with chronic illnesses use telehealth, including related sociodemographic and COVID-19 factors. METHODS: Using a cross-sectional design, 150 middle-aged and older African Americans were recruited from faith-based centers from March 2021 to August 2022. Data collected included sociodemographics, comorbidities, technological device ownership, internet usage, and attitudes toward COVID-19 disease and vaccination. Descriptive statistics and multivariable regression models were conducted to identify factors associated with telehealth use. RESULTS: Of the 150 participants, 32% had not used telehealth since the COVID-19 pandemic, with 75% reporting no home internet access and 38% having no cellular/internet network on their mobile device. Age, access to a cellular network on a mobile device, and wireless internet at home were significantly associated with the utilization of telehealth care. Higher anxiety and stress with an increased perceived threat of COVID-19 and positive attitudes toward COVID-19 vaccination were associated with telehealth utilization. DISCUSSION: Access and integration of telehealth services were highlighted as challenges for this population of African Americans. To reduce disparities, expansion of subsidized wireless internet access in marginalized communities is necessitated. Education outreach and training by healthcare systems and community health workers to improve uptake of telehealth currently and post-COVID-19 should be considered.
Subject(s)
COVID-19 , Telemedicine , Middle Aged , Humans , Aged , COVID-19/epidemiology , Black or African American , COVID-19 Vaccines , Cross-Sectional Studies , Los Angeles , PandemicsABSTRACT
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.
ABSTRACT
Sensing passersby and detecting crowded locations is a growing area of research and development in the last decades. The COVID-19 pandemic compelled authorities and public and private institutions to monitor access and occupancy of crowded spaces. This work addresses the detection of crowds in points of interest (POI) by using a territory grid analysis categorizing POIs by the services available in each location and comparing data gathered from a community passive Wi-Fi infrastructure against mobile cellular tower association data from telecom companies. In Madeira islands (Portugal), we used data from the telecom provider NOS for the timespan of 4 months as ground truth and found a strong correlation with sparse passive Wi-Fi. An official regional mobile application shows the occupancy data to end-users based on the territory categorization and the passive Wi-Fi infrastructure in POIs. Occupancy data shows historical hourly trends of each location, and the real-time occupation, helping visitors and locals plan their commutes better to avoid crowded spaces.
ABSTRACT
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.
ABSTRACT
Our research deals with creating a suitable and sufficiently reliable methodology to use for evaluating the movement of passengers in public transport or pedestrians. The goal is to design crowds ensing-based methods that provide a quick alternative to large-scale evaluations. It is the settings, the number of installed elements, parameters, and possibly other attributes enabling an increase in quality and reliability in real city conditions. The methodology must comply with GDPR. We also deal with the possibility of evaluating the behavior of people in case of restrictions due to disease spreading (nowadays, for example, COVID19). Our goal is to find methods using wireless technology and their generally little-described features for evaluating the movement of people. The usability of these technologies extends to some branches of logistics or organizations of larger cultural or sporting events. © 2022 IEEE.
ABSTRACT
COVID-19 virus is a source of concern and hazard in modern times. With a huge population moving about and an insufficient task force and resources to administer them, manual monitoring of social distance standards is impossible. As a result, this research work attempts to develop a smart electronic mask to maintain social distance while monitoring other health markers. Healthcare has received a lot of research attention in recent years. Several human instances of new coronavirus infection were verified during the end of 2019 and the beginning of 2020. As a result of the outbreak of covid-19, wearing a face mask has become required in several nations, and its effectiveness in preventing the pandemic has been demonstrated. During interactions, wearing a mask accidentally draws individuals closer together. Even if you wear a mask, it will not be enough to protect you from the corona virus. Even when wearing a mask, social distance should be maintained. The developed smart mask includes different functions such as social distancing, health monitoring, and mask hygiene monitoring. If someone comes too close, the distance sensor linked to the mask will alert the individuals. This will be linked to a little buzzer for alerting purposes. Temperature calculation is critical for COVID-19 detection, and many nations still employ it as a quick test to determine whether visitors or persons are infected. In the case of a pandemic, our project has designed a smart and hygienic mask that may be utilized. The corona virus is protected with this reusable and sanitary Covid- 19 mask. The health monitoring and warning system will be activated while you are wearing the mask. Bluetooth will be used to see the biosensor information. To keep the mask clean, sensors on the mask will detect any wetness or strange odour. © 2022 IEEE.
ABSTRACT
Coronaviruses are a group of viruses from the subfamily Orthocronavirinae in the Coronaviridae family and the order Nidovirales. In general, the transmission of this virus occurs through droplets or body fluids splashed on someone or objects around them within 1-2 meters' distance away through coughing and sneezing. Office buildings, cafes, and shopping areas are one of the clusters for spreading the coronavirus because the following places lack awareness of health protocols. This research will create a healthy and Smart Building system where this system consists of two devices from the following problems. The first device is a health procedures checker system where using an ultrasonic sensor as an automatic switch can provide a hand sanitizer as the first step to kill viruses. The GY609 sensor is used, which can measure the temperature of visitors without touching it. The second system is the Smart Switch;the doors and lights can control using voice using google assistant to minimize the doorknob's touch or the light switch. The healthy and Smart building test results are for the intelligent, healthy procedures system, 3-7 cm is the optimal distance from the hand to the sensor, 5cm is the distance from the hand to the temperature sensor, and the motor working time is 1 second. For the Smart switches, the recommended network system is 3G, 4G, or Wi-Fi to avoid excessive delays. © 2022 IEEE.