Internet of Medical Thing (IoMT) is the most emerging era of the Internet of Thing (IoT), which is exponentially gaining researchers' attention with every passing day because of its wide applicability in Smart Healthcare systems (SHS). Because of the current pandemic situation, it is highly risky for an individual to visit the doctor for every small problem. Hence, using IoMT devices, we can easily monitor our day-to-day health records, and thereby initial precautions can be taken on our own. IoMT is playing a crucial role within the healthcare industry to increase the accuracy, reliability, and productivity of electronic devices. This research work provides an overview of IoMT with emphasis on various enabling techniques used in smart healthcare systems (SHS), such as radio frequency identification (RFID), artificial intelligence (AI), and blockchain. We are providing a comparative analysis of various IoMT architectures proposed by several researchers. Also, we have defined various health domains of IoMT, including the analysis of different sensors with their application environment, merits, and demerits. In addition, we have figured out key protocol design challenges, which are to be considered during the implementation of an IoMT network-based smart healthcare system. Considering these challenges, we prepared a comparative study for different data collection techniques that can be used to maintain the accuracy of collected data. In addition, this research work also provides a comprehensive study for maintaining the energy efficiency of an AI-based IoMT framework based on various parameters, such as the amount of energy consumed, packet delivery ratio, battery lifetime, quality of service, power drain, network throughput, delay, and transmission rate. Finally, we have provided different correlation equations for finding the accuracy and efficiency within the IoMT-based healthcare system using artificial intelligence. We have compared different data collection algorithms graphically based on their accuracy and error rate. Similarly, different energy efficiency algorithms are also graphically compared based on their energy consumption and packet loss percentage. We have analyzed our references used in this study, which are graphically represented based on their distribution of publication year and publication avenue.

/pdf/internet-of-medical-things-iomt-based-smart-healthcare-2bpkpqro.pdf

Internet of Medical Things (IoMT)-Based Smart Healthcare System: Trends and Progress

In late 2019, a new genre of coronavirus (COVID-19) was first identified in humans in Wuhan, China. In addition to this, COVID-19 spreads through droplets, so quarantine is necessary to halt the spread and to recover physically. This modern urgency creates a critical challenge for the latest technologies to detect and monitor potential patients of this new disease. In this vein, the Internet of Things (IoT) contributes to solving such problems. This paper proposed a wearable device that utilizes real-time monitoring to detect body temperature and ambient conditions. Moreover, the system automatically alerts the concerned person using this device. The alert is transmitted when the body exceeds the allowed temperature threshold. To achieve this, we developed an algorithm that detects physical exercise named “Continuous Displacement Algorithm” based on an accelerometer to see whether a potential temperature rise can be attributed to physical activity. The people responsible for the person in quarantine can then connect via nRF Connect or a similar central application to acquire an accurate picture of the person’s condition. This experiment included an Arduino Nano BLE 33 Sense which contains several other sensors like a 9-axis IMU, several types of temperature, and ambient and other sensors equipped. This device successfully managed to measure wrist temperature at all states, ranging from 32 °C initially to 39 °C, providing better battery autonomy than other similar devices, lasting over 12 h, with fast charging capabilities (500 mA), and utilizing the BLE 5.0 protocol for data wireless data transmission and low power consumption. Furthermore, a 1D Convolutional Neural Network (CNN) was employed to classify whether the user is feverish while considering the physical activity status. The results obtained from the 1D CNN illustrated the manner in which it can be leveraged to acquire insight regarding the health of the users in the setting of the COVID-19 pandemic.

/pdf/wearable-device-for-observation-of-physical-activity-with-1csw731c.pdf

Wearable Device for Observation of Physical Activity with the Purpose of Patient Monitoring Due to COVID-19

https://doi.org/10.1016/j.artmed.2022.102288

Artificial intelligence-inspired comprehensive framework for Covid-19 outbreak control

Since 2019, the COVID-19 pandemic has had an extremely high impact on all facets of the society and will potentially have an everlasting impact for years to come. In response to this, over the past years, there have been a significant number of research efforts on exploring approaches to combat COVID-19. In this paper, we present a survey of the current research efforts on using mobile Internet of Thing (IoT) devices, Artificial Intelligence (AI), and telemedicine for COVID-19 detection and prediction. We first present the background and then present current research in this field. Specifically, we present the research on COVID-19 monitoring and detection, contact tracing, machine learning based approaches, telemedicine, and security. We finally discuss the challenges and the future work that lay ahead in this field before concluding this paper.

/pdf/a-survey-of-covid-19-detection-and-prediction-approaches-2sctua92.pdf

A survey of COVID-19 detection and prediction approaches using mobile devices, AI, and telemedicine

In recent years, due to the rise in the number of novel coronaviruses across the globe nations step forward to stop the crisis. With guidelines of the WHO many methodologies came into existence to prevent the spreading of coronavirus. My SD: A Smart Social distance and Monitoring System takes advantage of the features of the smartphone’s hardware which usually has Bluetooth transmitter-receiver, like GPS to determine the safe distance and required level of compliance. Through artificial intelligence, this new smart device helps maintain uniform social distance and detect COVID 19 patients. In these COVID 19 environments, everyone knows how safe they are. In this paper, we have automated the process whereby the layman can control himself without any priming which makes the system more user-friendly for the public. The user himself or herself can monitor body temperature, social distancing and get an alert in abnormal selfisolation conditions using contactless thermometer, ultrasonic sensors, and GSM modules.

Covid-19 Vest for Social distancing and Monitoring

There is a rapid increase in the spread of the Covid Virus. This has resulted in serious health issues among people. There is a dire need for a proper system to detect COVID symptoms and Alert Officials. The proposed solution is an IoT based multiple Health Monitoring System to detect symptoms of COVID and alert officials. It consists of a contactless temperature sensor, Oximeter, Automatic Hand Sanitizer, Camera module, Room Occupancy limiter and a Social Distancing module. It is a contactless method for patient evaluation. The Internet of Things enables devices to connect to the internet and communicate with each other. Data from these IoT-connected devices will help to identify the scenario and take necessary action. Contactless Temperature Sensor, Oximeter, and Heartbeat rate sensors are used to measure temperature, Oxygen level, and Heart rate respectively. NodeMCU reads sensor values, ESP32 camera module capture picture, and stores for future reference. The sensors measure the data. Normal temperature reading is from 97°F to 99°F and normal SpO2 reading is at least 95% [1]. If the measured value crosses the normal value, those details are immediately sent to health workers with a picture of the individual. The proposed solution also consists of a module to maintain Social Distancing and also an automatic Hand Sanitizing module. As the entire setup is automated, it reduces time and labour and also ensures satisfactory results.

Anjali K

Papers

IoT based Smart Healthcare System to Detect and Alert Covid Symptom