ABSTRACT
In the recent times it is found that there is a growing interest in the field of controlling the contagious diseases, especially after the outbreak of the novel COVID-19 (coronavirus). It still remains to be one of the biggest threats to humanity and people are dying and getting infected on a daily basis. Governments across the globe are trying their level best to contain the virus. They are also taking the necessary steps (e.g., travel bans, suspension of recreational and outdoor activities concerning mass audiences or public, isolation and contact tracing, social distancing, etc.). There are many patients who are undocumented just because they have coronavirus in their systems but they show no symptoms. Around 79% patients come under this category. It is to be noted that the total count of the number of cases at present in several countries differ from the actual people who are infected at present. This is because in the maj ority of cases, the symptoms show after a certain period of days and not just instantly. Also testing the whole population of a country in such a limited time is simply not possible. The World Health Organization recommended COVID-19 patients to isolate themselves from the healthy individuals in order to stop the spread of the disease. In order to ensure that this happens more efficiently and smoothly, in this paper an IoT based wearable band called QuArm band (i.e) Quarantine Arm band, which the patient can wear on his/her arm for tracking the real-time location of the patient to ensure that the quarantine rules are being followed is designed. This band is made keeping in mind the requirements of the public and the cost is set accordingly. Web interface alongside the band is made to retrieve the information. Notification on band tampering is also enabled. © 2022 IEEE.
ABSTRACT
The COVID-19 pandemic has spread all over the world. People go to public or crowded areas (i.e., schools, universities, hospitals, and government agencies), they take a lot of time to be checked the fever symptoms because of coronavirus. Therefore, this paper presents a method to automatically detect the body temperature by distance based on the recursive least square estimation. An infrared thermal camera is utilized to measure both human and environmental temperatures in real-time within a two-meter distance. The recursive least square approach is applied to estimate parameters for these correct temperatures. A microcontroller is integrated to read, compute, and send the measured temperatures to both web browsers and smartphones using the message queuing telemetry protocol. Moreover, the module of radio frequency identification is utilized for identification of the personal information. To validate our proposed temperature measurement system, fifteen male healthy students are invited to record their body temperature. The experimental result showed that our proposed approach was the correct temperature compared with the commercial device (37 ± 0.17 ° C). However, our proposed system is more stable than the commercial device: the standard deviation of the commercial device and ours is 0.41 C and 0.09°C, respectively. The measured temperature of each person is monitored and stored in the cloud. It is easily accessed by web browsers and smartphones. In addition, our proposed system can show a warning if the measured temperature is greater than the threshold. This work promises to automatically initial selection for suspected cases of COVID-19 disease to reduce the infection of this pandemic. © 2022 IEEE.
ABSTRACT
In this project the system has been designed in the manner to detect the body temperature and oxygen saturation level (SpO2) of the person. To detect the body temperature and oxygen pulses we are using the respective sensors. The sensors we are using in this project is MLX90614 ESF thermometer and MAX30100 is integrated with the pulse oximeter. Here we have used the two Node MCU (ESP 32) for the different sensors, one Node MCU is connected to the temperature sensor and another Node MCU is connected to the pulse oximeter. The components we are using in this project is Eco friendly. The software we are using in this project is ARDUINO UNO R3 IDE (Integrated development board) and To show the results we are making use of Blynk app. The maximum errors we get in this project is about 2%. When it comes to health monitoring, it has shown the good results. This is the best way to minimize the spread of the COVID-19. It is a low cost and high functionality which makes it use in the different places like Hospitals, Malls, Sports etc. © 2022 IEEE.
ABSTRACT
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.
ABSTRACT
We are proposing an IoT-based social distancing device as a preventive measure to COVID-19. It uses NodeMCU in conjunction with ultrasonic sensor temperature sensor, while vibrator buzzer is used for an alarming mechanism. The ultrasonic sensor is used to obtain higher accuracy as it uses LOS principle to measure the distance. The alarm will be raised whenever measured distance is found to be less than six feet. Temperature sensor is used to alert the user to isolate them if their body temperature goes above 102 °F, thereby decreasing the transmission possibility of virus in case he is infected with the virus. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
The planet earth has been facing COVID-19 epidemic as a challenge in recent time. It is predictable that the world will be fighting the pandemic by taking precautions steps before an operative vaccine is found. The IoT produces huge data volumes, whether private or public, through the invention of IoT devices in the form of smart devices with an improved rate of IoT data generation. A lot of devices interact with each other in the IoT ecosystem through the cloud or servers. Various techniques have been presented in recent time, using data mining approach have proven help detect possible cases of coronaviruses. Therefore, this study uses machine learning technique (ABC and SVM) to predict COVID-19 for IoT data system. The system used two machine learning techniques which are Artificial Bee Colony algorithm with Support Vector Machine classifier on a San Francisco COVID-19 dataset. The system was evaluated using confusion matrix and had a 95% accuracy, 95% sensitivity, 95% specificity, 97% precision, 96% F1 score, 89% Matthews correlation coefficient for ABC-L-SVM and 97% accuracy, 95% sensitivity, 100% specificity, 100% precision, 97% F1 score, 93.1% Matthews correlation coefficient for ABC-Q-SVM. In conclusion, the system shows that the process of dimensionality reduction utilizing ABC feature extraction techniques can boost the classification production for SVM. It was observed that fetching relevant information from IoT systems before classification is relatively beneficial. [ FROM AUTHOR] Copyright of Computing is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
ABSTRACT
Since the end of 2019, the world has been reeling with the COVID-19 pandemic. The drastic and dramatic spread has affected human lives and livelihoods as well as businesses across the world. Organizations across the world are uniting and coming forward to minimize the seriousness of healthcare. The survival of the human community should be the top priority during this time. To control spread, respective higher authorities impose restrictions on public gatherings, with strict action taken against those who exceed the maximum allowed people in public gatherings. Our IOT-based project aims to limit the number of people entering the academic blocks during COVID-19 in order to monitor overcrowding in these buildings. Our electrical circuit or device will monitor the number of people entering the academic blocks, and once the maximum allowed number of people is reached, the next person will not be allowed to enter the building, and the electrical circuit will ring a siren. This will also ensure that social distancing is maintained. Our project is based on Arduino. Several electrical components, such as an Arduino Uno, a prototype, a breadboard, a piezo-buzzer, ultraviolet sensors, and jumper wires, were used. Software simulations were carried out in the well-known online electrical circuit compiler, Tinkercad. A hardware simulation of our project was also made. © Este es un artículo en acceso abierto,.
ABSTRACT
Internet of Things (IoT) has gained popularity since last recent years and applied in wide variety of applications including education, homes, offices and healthcare industry. IoT field changing the healthcare system by considering factors like economy, technology and social by which patients can be diagnose, treat or monitored in effective way. The world is facing current global challenge which can severe the respiratory syndrome Covid-19 which leads to serious health issues and even huge mortality. There are more than 31 cr. of people around the world suffering from Covid-19 with more than 5 cr. of mortality, when this paper was written. Since the pandemic started, several researchers put their efforts to use technologies to save world from effects of this virus. IoT plays a major role during this pandemic. IoT-enabled devices or applications helps to reduce the chances of virus spread of Covid-19 by early diagnose, monitoring of patients during active or recovery phase. This paper discusses the role of IoT during Covid-19 and how IoT implementation in healthcare helps in the phases of diagnosis, isolation and recovery. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
Internet of Things (IoT) has gained popularity since last recent years and applied in wide variety of applications including education, homes, offices and healthcare industry. IoT field changing the healthcare system by considering factors like economy, technology and social by which patients can be diagnose, treat or monitored in effective way. The world is facing current global challenge which can severe the respiratory syndrome Covid-19 which leads to serious health issues and even huge mortality. There are more than 31 cr. of people around the world suffering from Covid-19 with more than 5 cr. of mortality, when this paper was written. Since the pandemic started, several researchers put their efforts to use technologies to save world from effects of this virus. IoT plays a major role during this pandemic. IoT-enabled devices or applications helps to reduce the chances of virus spread of Covid-19 by early diagnose, monitoring of patients during active or recovery phase. This paper discusses the role of IoT during Covid-19 and how IoT implementation in healthcare helps in the phases of diagnosis, isolation and recovery. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
COVID-19 contact tracing, maintaining social distance from an infected person, and spotting the hotspots is a difficult and time taking process. Many traditional methods can be used for this purpose but these methods have limited capabilities. Using these methods the process becomes more complex, slower, and difficult. This process involves the storage and sharing of personal data that requires security and privacy. To address these issues, we have proposed a blockchain, AI, and IoT-based framework for COVID-19 contact tracing and distancing. In this framework, Every user registers on the blockchain and gets public and private key pairs, the access level of every user is defined in the smart contract. The activity data of the user is collected using the smartwatch, which ensures real-time and accurate data collection. The data is encrypted with the keys of the data owner and stored on the cloud. So in case of data leakage, no one can decrypt the data without keys, so in this way, the secure data storage issue is resolved. Every transaction is recorded on the blockchain, it makes auditing easy in case of any malicious data transaction. Every user can access data according to its access level defined in the smart contract, it ensures the security of data. By the analysis of data, the ML model predicts the infected person and spot the COVID-19 hotspot areas. © 2021 IEEE.
ABSTRACT
Due to the increasing number of infected people and the number of deaths from COVID-19 over the world, there is a big challenge towards finding a radical solution to reduce the spread of disease and infection. The early detection, isolating the infected persons and tracing possible contacts are very critical. This paper presents an integrated approach that connects hospitals/laboratories, COVID-19 negative persons, positive persons, and contact persons to a cloud-based consortium blockchain system to guarantee reliable secured COVID-19 spread control. The proposed model guarantees a real time monitoring, tracking, and updating to persons status whether normal, contact, or positive COVID-19 case, and the related updates are done in the blockchain based on the results of execution of the blockchain smart contract rules. Tracking infected persons and their contacts is implemented using IoT sensors to determine contact time and spatial distances between them. The GPS/Bluetooth/UWB was used as IoT sensors technologies to determine the distances between the infected people and those in contact. The proposed blockchain Ethereum system smart contract was implemented by solidity programming language through the Remix IDE. The proposed approach was tested and successfully detected the contact cases and managed the different persons states on the cloud based blockchain system applying the smart contract rules accurately. As the calculated distances using the proposed model in the distance of one meter do not exceed the error rate of 11 cm. © 2021 Little Lion Scientific