Artificial Intelligence and Internet of Things (AI-IoT) Technologies in Response to COVID-19 Pandemic: A Systematic Review

Khan, Junaid Iqbal; Khan, Jebran; Ali, Furqan; Ullah, Farman; Bacha, Jamshid; Lee, Sungchang

doi:10.1109/access.2022.3181605

Cited by 29 publications

(12 citation statements)

References 416 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Both the general SmartThings market and our specially created IOTBENCH application corpus were used to evaluate SAINT. In order to establish the value of SAINT and understand how the market normally functions, initial research focused on the SmartThings sector [ 71 ]. The second analysis used the IOTBENCH app corpus from the first one.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The devices may have features in common, but they are made by different companies and run on different operating systems. Hadoop has trouble dealing with data sources that might carry out comparable operations but have wildly dissimilar data formats [ 71 ]. This lack of consistent standardization is summarized by the phrase “The Internet of Things May Never Speak a Single Language”.…”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Analysis of IoT Security Challenges and Its Solutions Using Artificial Intelligence

Mazhar

Talpur

Shloul³

et al. 2023

Brain Sciences

View full text Add to dashboard Cite

The Internet of Things (IoT) is a well-known technology that has a significant impact on many areas, including connections, work, healthcare, and the economy. IoT has the potential to improve life in a variety of contexts, from smart cities to classrooms, by automating tasks, increasing output, and decreasing anxiety. Cyberattacks and threats, on the other hand, have a significant impact on intelligent IoT applications. Many traditional techniques for protecting the IoT are now ineffective due to new dangers and vulnerabilities. To keep their security procedures, IoT systems of the future will need AI-efficient machine learning and deep learning. The capabilities of artificial intelligence, particularly machine and deep learning solutions, must be used if the next-generation IoT system is to have a continuously changing and up-to-date security system. IoT security intelligence is examined in this paper from every angle available. An innovative method for protecting IoT devices against a variety of cyberattacks is to use machine learning and deep learning to gain information from raw data. Finally, we discuss relevant research issues and potential next steps considering our findings. This article examines how machine learning and deep learning can be used to detect attack patterns in unstructured data and safeguard IoT devices. We discuss the challenges that researchers face, as well as potential future directions for this research area, considering these findings. Anyone with an interest in the IoT or cybersecurity can use this website’s content as a technical resource and reference.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Analysis of IoT Security Challenges and Its Solutions Using Artificial Intelligence

Mazhar

Talpur

Shloul³

et al. 2023

Brain Sciences

View full text Add to dashboard Cite

show abstract

“…It provides insight into the spread pattern of COVID-19 by visualizing its spread graph, it also helps policymakers to determine the best policies that are helpful in improving the accuracy of forecast and is meaningful for the control of COVID-19. To forecast the growth rate of COVID-19, researchers have used various approaches to obtain the best accuracy [15] . Amar et al.…”

Section: Literature Reviewmentioning

confidence: 99%

COVID-19 spread control policies based early dynamics forecasting using deep learning algorithm

Ali

Ullah

Khan

et al. 2023

Chaos, Solitons & Fractals

Self Cite

View full text Add to dashboard Cite

“…This evolution has been significantly propelled by technological advancements such as the internet, mobile technology, digital imaging, and, more recently, artificial intelligence (AI) and the Internet of Things (IoT). These technologies have expanded the scope and capabilities of telemedicine, enabling services ranging from remote patient monitoring to virtual consultations and tele-surgery (Banerjee, Chakraborty, & Rathi Sr, 2020;Khan et al, 2022). The relevance of telemedicine in modern healthcare cannot be overstated.…”

Section: Introductionmentioning

confidence: 99%

A Comprehensive Review of Telemedicine Technologies: Past, Present, and Future Prospects

Toritsemogba Tosanbami Omaghomi,

Oluwafunmi Adijat Elufioye,

Opeoluwa Akomolafe

et al. 2024

imsrj

View full text Add to dashboard Cite

This comprehensive review explores telemedicine technologies' past, present, and future. Telemedicine has evolved significantly, providing healthcare services and exchanging medical information remotely. The historical overview traces its roots from early experiments to its current state, marked by advanced technology, diverse applications, and increased adoption, especially during the COVID-19 pandemic. Emerging technologies like AI, VR, IoT, and blockchain promise to revolutionize telemedicine, enhancing diagnostics, patient monitoring, and personalized treatment. Potential applications range from chronic disease management to tele-ICUs and global health initiatives. To maximize telemedicine's benefits, healthcare providers, technology developers, policymakers, and researchers are offered recommendations. Telemedicine's potential to transform healthcare delivery is profound, fostering accessibility, efficiency, and improved patient outcomes. While challenges exist, addressing them will help create a future where telemedicine is central to delivering equitable and patient-centred healthcare. Keywords: Telemedicine, Healthcare Technology, Remote Healthcare, Emerging Technologies, Healthcare Access, Telehealth Trends.

show abstract

Artificial Intelligence and Internet of Things (AI-IoT) Technologies in Response to COVID-19 Pandemic: A Systematic Review

Cited by 29 publications

References 416 publications

Analysis of IoT Security Challenges and Its Solutions Using Artificial Intelligence

Analysis of IoT Security Challenges and Its Solutions Using Artificial Intelligence

COVID-19 spread control policies based early dynamics forecasting using deep learning algorithm

A Comprehensive Review of Telemedicine Technologies: Past, Present, and Future Prospects

Contact Info

Product

Resources

About