TABLE 1.
Contribution of digital technologies in COVID‐19 pandemic
| Authors | Year | Key technology addressed | The role played by the technology in addressing the COVID‐19 pandemic |
|---|---|---|---|
| Rajvikram et. al. (2020) | 2020 | AI, ML, IoT, drone and robotics, mobile applications |
Predicting and predicting infection rates, as well as disease diagnosis Providing high‐quality treatment (e.g. drug delivery at home) Transportation and surveillance, eliminating labour‐intensive tasks such as nursing and tracking infected individuals Providing medical assistance ubiquitously |
| Pratap et al. (2020) | 2020 | IoMT | Remote monitoring of patients suffering from orthopaedic problems |
| Vaishya et al. (2020) | 2020 | AI |
Detection and diagnosis of infection in its early stages Treatment monitoring Individuals' contacts are traced Case and mortality projections Drug and vaccine production Streamlining the workload of healthcare professionals Disease prevention |
| Javaid et al. (2020) | 2020 | Industry 4.0 technologies (IIoT) |
Telemedicine service for effective virus prevention and control Predicting outbreaks and containing or even preventing the virus's spread Surveillance to ensure the quarantine and mask‐wearing procedures are followed |
| Pratap et al. (2020) | 2020 | IoT |
Discussed hospital with Internet access Consultation via telehealth Rapid examination Intelligent monitoring of infected individuals Virus forecasting Real‐time data on the infection's spread |
| Iyengar et. al. (2020) | 2020 | Mobile apps |
Clinical assessment Disease diagnosis Appropriate advice and prescription Patients are monitored from their homes and in remote areas. |
| Mohanty et al. (2020) | 2020 | IoMT |
Monitoring in real time Patient monitoring via remote access Rapid diagnostic evaluation Tracing of contacts Examination and surveillance Disease prevention and control |
| Chamola et al. (2020) | 2020 | IoMT AI Robots and Drones 4. Mobile Apps Blockchain 5G |
Remote monitoring of patients Keeping track of prescription orders Wearable devices that relay health data to the appropriate health care professionals. Disease surveillance, risk assessment, medical diagnosis and screening, and curative research Treatment of patients and reduction of healthcare workers' stress levels Noncontact ultraviolet (UV) surface disinfection methods operated by a robot Tracing of contacts Increasing the frequency of testing and reporting Providing supporters with a secure donation platform Keeping supply chain disruptions to a minimum Recording of patient information in a secure manner Virus tracking, patient management, data collection, and interpretation have also been enhanced. |
| Rahman et al. (2020) | 2020 | IoT |
Surveillance in real time via wearable health monitoring devices Remote health testing via the cloud Data processing in real time Utilizing travel history data to rapidly diagnose infected patients and forecast the possibility of disease transmission to other locations |
| Kumbhar et al. (2020) | 2020 | IoT and deep learning |
Detection of violations of social distance using CNN. Tracking by area dependent on the user's cellular activity Detection of infected individuals within a geographic region. Identification of individuals with serious symptoms by the use of wearable devices Contact tracing of individuals in high‐risk areas Appropriate acts and alerts against isolation |
| Yang et al. (2020) | 2020 | IoMT |
Implemented point‐of‐care (POC) diagnostics and the IoMT to build a network that enables patients to access proper healthcare at home and a disease management database for government and healthcare organizations. Monitoring disease progression and administering appropriate medical treatment while avoiding the spread of the viral infection to others. |
| Singh et al. (2020) | 2020 | IoT | Developed an IoT‐enabled wearable quarantine band capable of detecting and tracking absconders in real time |
| Lin & Wu (2020) | 2020 | IoMT |
Distribution of critical drug products efficiently Monitoring of medical supply production and demand |
| Ding et al. (2020) | 2020 | Wearable sensors and telehealth |
Various parameters such as Oxygen saturation, respiratory rate, and others are monitored in the general population and quarantined patients. Unobtrusive sensing systems for detecting the disease and tracking patients with relatively mild symptoms whose clinical condition may deteriorate unexpectedly Telehealth technologies for remote monitoring and diagnosis of COVID‐19 and related diseases |
| Ahmed et al. (2020) | 2020 | Mobile apps | Attributes and examples of contact tracing applications |
| Nasajpour et al. (2020) | 2020 | IoT, robots, drone, intelligent apps | Early detection, quarantine period, and post‐recovery. |
| Kamal et al. (2020) | 2020 | IoT |
Deployment and organizational difficulties, as well as future opportunities for more pandemic control Ambulances equipped with the Internet of Things, and wearable health tracking devices Artificial intelligence‐assisted forecasting and social distancing education and conferencing through the internet |
| Ye et al. (2020) | 2020 | 5G‐based robotic technology | Cardiopulmonary examinations of COVID‐19 patients |
| Rahman et al. (2020) | 2020 | B5G (beyond 5G) and DL | Remote monitoring and diagnosis by the use of mobile edge devices equipped with deep learning models |
| Soldani (2020) | 2020 | 5G |
To enhance diagnostic capabilities in high‐risk areas by identifying infected subjects as soon as possible Tracing their contacts and determining the source of the infection as soon as possible |
| Yu et al. (2020) | 2020 | 5G |
Two cases of SARS‐CoV‐2 infection were evaluated using remote robotic ultrasound operated by 5G, and the benefits of 5G were discussed. COVID‐19 case diagnosis and monitoring in clinical practice. |
| Tuli et al. (2020) | 2020 | ML and cloud computing |
Proactively forecasting the epidemic's development Predicting the potential threat posed by COVID‐19 and deploying on a cloud‐computing platform to allow more precise and real‐time forecasting of the epidemic's growth activity. |
| Lalmuanawma (2020) | 2020 | ML and AI | SARS‐CoV‐2 and its associated epidemics: screening, prediction, forecasting, touch tracking, and drug creation |
| Ghoshal & Tucker (2020) | 2020 | DL | Detecting COVID‐19 in X‐ray images |
| Narinv et al. (2020) | 2020 | DL | Detection of a patient with Corona virus pneumonia using a chest X‐ray radiograph |
| Punn et al. (2020) | 2020 | ML and DL | Prediction of the COVID‐19's potential reachability using real‐time data from the Johns Hopkins dashboard. |
| Hussain (2020) | 2020 | AI and DL |
Early warnings and alerts about COVID‐19 COVID‐19 prediction and monitoring in its early stages. Prognosis and diagnosis in the early stages. Distancing and regulation on a social level. Early diagnosis and care. |
| Naudé (2020) | 2020 | AI |
Tracking and forecasting the spread of COVID‐19 Disease diagnosis and prognosis |
| Alimadadi et al. (2020) | 2020 | AI and ML |
Classifying and predicting individuals according to their susceptibility or resistance to COVID‐19 infection Detection and tracking of COVID‐19 patients automatically over time Rapid development of automated diagnostic systems in order to improve predictive, diagnostic, and therapeutic methods for possible pandemics such as COVID‐19. |
| Pham et al. (2020) | 2020 | AI and big data |
Developing effective diagnostic and treatment approaches, as well as early detection and prediction of infection, in order to determine the magnitude of COVID‐19, COVID‐19 detection and diagnosis, and detecting, monitoring, and predicting the outbreak Outbreak prediction: to forecast outbreaks using large‐scale data analytics, to monitor the spread of COVID‐19, and to assist in the diagnosis and treatment of COVID‐19. Discovery of vaccines/drugs |
| Pratap et al. (2020) | 2020 | VR |
Pain management by physical therapy Patients that need prolonged in‐hospital care will benefit from a VR‐based stay. Medical personnel education Patient care Medical marketing Public understanding of disease |
| Proniewska et al. (2020) | 2020 | AR (holography) | Using augmented reality lenses, displaying patient details and confidential information just in front of the doctor's eyes |
| Woolliscroft (2020) | 2020 | AR and VR |
Virtual medical Hospital in own house Diagnostic and therapeutic advancements, Virtual health education for authorities, academic medical centres, faculty, and students |
| Imperatori et al. (2020) | 2020 | VR | Treatment of psychopathological symptoms associated with stress, as well as trauma associated with the effects of the COVID‐19 pandemic, both in health care staff and the general population |
| Gao et al. (2020) | 2020 | VR | Determine the feasibility of using virtual reality exercise as a coping strategy for the promotion of health and wellness in older adults during the COVID‐19 pandemic. |
| Ecclestona et al. (2020) | 2020 | VR and AR |
The public health implications of COVID‐19 for patients with chronic pain are discussed. The repercussions of failing to treat these patients during the pandemic's uncertain period are illustrated. Remote evaluation and management options are demonstrated. Additionally, clinical evidences demonstrating the efficacy of remote therapies are discussed. |
| Bragazzi (2020) | 2020 | Big data |
In real time, reconstructing the outbreak's early epidemiological history, spreading the outbreak, and preventing and controlling infectious diseases Identification of possible therapeutics and vaccine candidates Facilitating the application of interventions in public health. |
| Wang (2020) | 2020 | Big data | Real‐time warnings during a hospital visit based on travel history and clinical symptoms to assist with case detection QR code scanning and online monitoring of travel history and health symptoms to identify travellers' infectious threats based on origin and recent travel history. |
| Lin & Houc (2020) | 2020 | Big data and AI |
Tracing the person who has come into contact with infected individuals COVID‐19 epidemic risk management using self‐reported health status and travel history from aviation, railway, and land transportation networks, as well as social media, contact tracking, and strict quarantine compliance |
| Ienca & Vayena (2020) | 2020 | Big data |
Identifying individuals who have travelled to places where the disease has spread through prediction and surveillance. Identifying and isolating contaminated people's contacts |
| Zhou (2020) | 2020 | Big data |
Rapid aggregation of multi‐source big data for disease knowledge visualization Cases that have been verified are being tracked in space. Transmission forecasting in the area |
| Torky & Ella (2020) | 2020 | Blockchain | Detecting unknown contaminated cases, as well as predicting and measuring the COVID‐19 epidemic's contagion risk for populations in real time. |
| Xu et al. (2020) | 2020 | Blockchain | Tracing knowledge sharing in order to reduce the harm COVID‐19 causes humanity and to save lives and money without infringing on fundamental human rights to privacy. |
| Bansal et al. (2020) | 2020 | Blockchain |
“Immunity certificates” or “Immunity licences” i.e. document that certifies an individual has been infected and is immune to coronavirus disease 2019 Combating two challenges while using immunity certificates namely the falsification of information and people seeking out for COVID‐19 infection |
| Nguyen et al. (2020) | 2020 | Blockchain |
User privacy is protected when monitoring outbreaks. Day‐to‐day activities, such as medical supply chain and donation monitoring, must be kept secure. |
| Chang & Park (2020) | 2020 | Blockchain | Infectious disease reporting systems, as well as the rapid and reliable exchange of patients' medical information in a safe manner. |
| Mashamba‐Thompson & Crayton (2020) | 2020 | Blockchain | Low‐cost blockchain and AI‐connected mHealth connected self‐testing and monitoring systems are being developed and deployed. |
| Khatoon (2020) | 2020 | Blockchain | Encourage patients to share their medical records freely and securely with physicians, hospitals, research agencies, and other stakeholders while maintaining complete control of their medical data's privacy. |
| Alam (2020a) | 2020 | Blockchain | Four‐layer architecture that uses IoT and Blockchain to detect and prevent the spreading of COVID‐19 infection |
| Warren & Skillman (2020) | 2020 | Cloud | Using cloud computing services, analysed a publicly accessible mobile device location dataset and discovered drastic improvements in mobility due to COVID‐19. |
| Gong et al. (2020) | 2020 | Cloud |
A cloud‐based hardware to solve the problems unique to the COVID‐19 epidemic A data model has been developed to store the data on the cloud and to provide different levels of access to the data, data security and privacy protection |
| Maghdid et al. (2020) | 2020 | Cloud |
Using built‐in smartphone sensors, a new AI system is proposed to detect COVID‐19. The developed Artificial Intelligence AI‐enabled system reads the signal measurements from smartphone sensors to predict the severity of pneumonia as well as the disease's outcome. The proposed system gathers data from a variety of users or patients, allowing the dataset to expand and form a broad data set. The registered data as well as the prediction's outcome are saved in the cloud. |
| Bai et al. (2020) | 2020 | Cloud |
The COVID‐19 Intelligent Diagnosis and Care Assistant Program (nCapp) has been suggested as a way to detect COVID‐19 sooner and improve treatment. COVID‐19 is better managed, regulated, and diagnosed with the help of nCapp. In real‐time online contact with the cloud, the following functions are introduced. Patient registration: the patient's basic information is entered into an online database. Start consultation. Diagnosed with intelligent assistance; treated with intelligent assistance. A treatment recommendation is provided depending on the seriousness of the disease. Self‐control: this section contains useful knowledge on self‐control. Information about COVID‐19 cases in the user's area is given through a map. |
| Bogue (2020) | 2020 | Robots |
Reducing the risk of infection transmission by limiting inter‐personal communication By performing such regular teaks, you can free up medical professionals. Aid and expedite the delivery of food and medical supplies. Keep an eye on public areas. Educating the public about the importance of social distance Enable those who are alone to communicate with friends and family. |
| Jaiswal et al. (2020) | 2020 | Robots, Drones |
Thermal imaging is used to determine the temperature using a thermal camera. To avoid the danger, keep a social distance near the affected area by using a loudspeaker‐equipped drone system. For the containment of COVID‐19, assistance in quarantine and a variety of other functions are needed. |
| Tavakoli et al. (2020) | 2020 | Robots | Reduce the risk of infectious disease transmission to frontline healthcare workers by allowing them to triage, assess, track, and treat patients safely from a distance. |
| Zeng et al. (2020) | 2020 | Robots |
The roles of various types of robots are illustrated. Described how robotic technology can be useful in a variety of settings such as hospitals, airports, transportation, recreation and scenic areas, hotels, and communities in general. |
| Khan et al. (2020) | 2020 | Robots | The roles of various types of robots such as receptionist, washing, disinfecting, nursing, ambulance, and telemedicine robots are presented. These robots can help with effective COVID‐19 management and reducing the number of infected patients and casualties. |
| Gore (2020) | 2020 | Robots, drones, mobile apps |
Assistive hospital care robotic devices are intended to assist frontline soldiers in keeping a safe distance from Corona virus‐infected patients. Teleoperated robots to navigate the quarantine zone and distribute food, water, medication, and other necessities to anyone in need. Robots are now being developed that can be used at the entrances to office buildings and other public places to dispense hand sanitizer and send public health messages about the virus. Robots may also be used to transport drugs and food in hospital isolation wards. Drones help to clean public spaces, hospitals, and tall buildings. Mobile apps for monitoring social distancing, conveying COVID‐19 information, and patient tracking are discussed. |
| Aymerich‐Franch (2020) | 2020 | Robots | Reduce the disadvantages of separation by facilitating physical distancing. |
| Malik et al. (2020) | 2020 | Robots | The role of cobots in the pandemic, specifically increasing ventilator output, repurposing existing non‐ventilator (e.g. car) production to ventilator production, and maintaining social distancing, is addressed. |
| Vafea et al. (2020) | 2020 | AI, big data, IoT, robots, drones |
Predict the outcome of COVID‐19 infections in order to predict the mortality risk of a COVID‐162 patient. Predict and assist in the early detection of critically ill patients Execute efficient clinical techniques Using COVID‐19, take regular temperature measurements in inpatients. Distribute medical supplies and test kit equipment to hard‐to‐reach locations. |
| Zampolli & Rodriguez (2020) | 2020 | Robots | In urology surgery, robots are used to prevent viral transmission. |
| Ruiz Estrada (2020) | 2020 | Drone |
Aerial monitoring of the impact of post‐epidemic infectious diseases Infectious disease epidemics have hampered logistics and freight distribution. Post‐aerial evaluation of major epidemic infectious diseases |
| Kumar et al. (2020) | 2020 | Drones |
Simulated a drone‐based device for surveillance, control, thermal imaging, sanitization, social distancing, medicine, data analytics, and statistics generation. In COVID‐19 hotspots, a real‐time drone‐based framework for sanitization, tracking, vigilance, face recognition, thermal scanning, and other purposes were implemented. |
| Parker et al. (2020) | 2020 | Mobile apps | The ethical consequences of using cell phone applications to combat the COVID‐19 pandemic are discussed. |
| Oliver et al. (2020) | 2020 | Mobile apps | Discussed how mobile phone data will assist government and public health officials in deciding the best course of action to contain the COVID‐19 pandemic and evaluating the efficacy of control measures such as physical separation. |
| Banskota et al. (2020) | 2020 | Mobile apps | During COVID‐19, various forms of apps such as social networking apps, prescription management and telemedicine apps, health and wellness apps, food and drink apps, and apps for visual and hearing disability are addressed. |
| Javid & Khan (2021) | 2021 | IoT |
To track and regulate all medical temperature, sugar level, blood pressure, and information about COVID‐19 patient health clinical operations, drug distribution, patient care, laboratory testing, and medication management During the COVID‐19 Pandemic, various IoT technologies for use in healthcare were also discussed. |
| Filho et al (2021) | 2021 | IoT | PAR, a network for remote patient and environment monitoring, patient healthcare data management, patient health condition management, and emergency and crisis management, was created. |
| Dong & Yao (2021) | 2021 | IoT | COVID‐19 symptom diagnosis, quarantine monitoring, contact tracing & social distancing, COVID‐19 outbreak forecasting, and SARS‐CoV‐2 mutation tracking were all demonstrated as part of a potential fog‐cloud combined IoT network for COVID‐19 prevention and control. |
| Rathee et al. (2021) | 2021 | IoT | Developed an AI‐based device to diagnose COVID‐19 symptoms such as fever, bleeding, and sore throat, among other things. |
| Wang et al. (2021) | 2021 | AI | In order to rapidly diagnose COVID‐19 pneumonia, an AI system that analyzes CT images automatically and measures the risk of infection was deployed. |
| Chassagnon et al. (2021) | 2021 | DL | Artificial intelligence and medical imaging are being used to study disease quantification, staging, and outcome prediction. |
| Mushtaq et al. (2021) | 2021 | AI | COVID‐19 CXR results were classified and quantified, the relationship between initial CXR severity and clinical outcomes was examined, and the use of an AI system as an initial COVID‐19 prognostic method was evaluated. |
| Abdel‐Basset et al. (2021) | 2021 | AI, IoT, VR, big data, 5G, robots and drones, blockchain |
proposed an intelligent framework to reduce COVID‐19 outbreaks Keeping the medical teams safe, maintaining the patients physical and psychological healthcare conditions; managing a severe shortage of PPE for the medical team; reducing the massive pressure on hospitals Tracking recovered patients to treat COVID‐19 patients. |
| Christopher & Valérie (2021) | 2021 | Drones and robots | Demonstrated that mobile remote presence systems (MRP), also known as telepresence robots, can be used effectively in some forms of medical consultations, such as remote consultations with nursing home residents. |
| Huang et al. (2021) | 2021 | AI | Discussed clinical applications of machine learning and deep learning, such as clinical features, electronic medical records, and medical images (CT, X‐ray, ultrasound images, and so on). |