Role of Artificial Intelligence of Things (AIoT) to Combat Pandemic COVID-19

2021 ◽  
pp. 117-128
Author(s):  
Arti Jain ◽  
Rashmi Kushwah ◽  
Abhishek Swaroop ◽  
Arun Yadav
Keyword(s):  
Artificial Intelligence ◽  
Data Privacy ◽  
Data Exchange ◽  
Analytical Tool ◽  
Technological Solution ◽  
Global Pandemic ◽  
Huge Data ◽  
Outlier Data ◽  
Iot Devices

COVID-19 is caused by virus called SARS-CoV-2, which was declared by the WHO as global pandemic. Since the outbreak, there has been a rush to explore Artificial Intelligence (AI) and Internet of Things (IoT) for diagnosing, predicting, and treating infections. At present, individual technologies, AI and IoT, play important roles yet do not impact individually against the pandemic because of constraints like lack of historical data and the existence of biased, noisy, and outlier data. To overcome, balance among data privacy, public health, and human-AI-IoT interaction is must. Artificial Intelligence of Things (AIoT) appears to be a more efficient technological solution that can play a significant role to control COVID-19. IoT devices produce huge data which are gathered and mined for actionable effects in AI. AI converts data into useful results which are utilized by IoT devices. AIoT entails AI through machine learning and decision making to IoT and renovates IoT to add data exchange and analytics to AI. In this chapter, AIoT will serve as a potential analytical tool to fight against the pandemic.

Artificial Intelligence Applications for Industry 4.0: A Literature-Based Study

2021 ◽  
pp. 1-29
Author(s):  
Mohd Javaid ◽  
Abid Haleem ◽  
Ravi Pratap Singh ◽  
Rajiv Suman
Keyword(s):  
Artificial Intelligence ◽  
Industry 4.0 ◽  
Decisive Role ◽  
Vital Role ◽  
Data Types ◽  
Process Data ◽  
Automation Systems ◽  
Recent Developments ◽  
Iot Devices

Artificial intelligence (AI) contributes to the recent developments in Industry 4.0. Industries are focusing on improving product consistency, productivity and reducing operating costs, and they want to achieve this with the collaborative partnership between robotics and people. In smart industries, hyperconnected manufacturing processes depend on different machines that interact using AI automation systems by capturing and interpreting all data types. Smart platforms of automation can play a decisive role in transforming modern production. AI provides appropriate information to take decision-making and alert people of possible malfunctions. Industries will use AI to process data transmitted from the Internet of things (IoT) devices and connected machines based on their desire to integrate them into their equipment. It provides companies with the ability to track their entire end-to-end activities and processes fully. This literature review-based paper aims to brief the vital role of AI in successfully implementing Industry 4.0. Accordingly, the research objectives are crafted to facilitate researchers, practitioners, students and industry professionals in this paper. First, it discusses the significant technological features and traits of AI, critical for Industry 4.0. Second, this paper identifies the significant advancements and various challenges enabling the implementation of AI for Industry 4.0. Finally, the paper identifies and discusses significant applications of AI for Industry 4.0. With an extensive review-based exploration, we see that the advantages of AI are widespread and the need for stakeholders in understanding the kind of automation platform they require in the new manufacturing order. Furthermore, this technology seeks correlations to avoid errors and eventually to anticipate them. Thus, AI technology is gradually accomplishing various goals of Industry 4.0.

Data Security for Connected Governments and Organisations

2021 ◽  
pp. 229-251
Author(s):  
Heru Susanto ◽  
Leu Fang Yie ◽  
Didi Rosiyadi ◽  
Akbari Indra Basuki ◽  
Desi Setiana
Keyword(s):  
Artificial Intelligence ◽  
Early Warning ◽  
Data Security ◽  
Data Privacy ◽  
Government Agencies ◽  
Security Measures ◽  
Security Issues ◽  
The Impact ◽  
Distributed Technologies

Digital ecosystems have grown rapidly over the years, and governments are investing in digital provision for their processes and services. Despite the advantages of distributed technologies, there are many security issues as well that result in breaches of data privacy with serious impact including legal and reputational implications. To deal with such threats, government agencies need to thoughtfully improve their security defences to protect data and systems by using automation and artificial intelligence (AI), as well as easing the data security measures including early warning of threats and detection. This study provides a comprehensive view of AI and automaton to highlight challenges and issues concerning data security and suggests steps to combat the issues. The authors demonstrate the role of AI-driven security tools and automation to mitigate the impact of data breaches to also propose recommendations for government agencies to enhance their data security protection.

IoT ecosystem faces fragmented future

2019 ◽  
Keyword(s):  
Artificial Intelligence ◽  
Cloud Computing ◽  
Supply Chain ◽  
Internet Of Things ◽  
Data Privacy ◽  
The Internet ◽  
Privacy And Security ◽  
Content Type ◽  
Iot Devices ◽  
The Internet Of Things

Subject IoT ecosystem. Significance The market for the Internet of Things (IoT) or connected devices is expanding rapidly, with no manufacturer currently forecast to dominate the supply chain. This has fragmented the emerging IoT ecosystem, triggering questions about interoperability and cybersecurity of IoT devices. Impacts Firms in manufacturing, transportation and logistics and utilities are expected to see the highest IoT spending in coming years. The pace of IoT adoption is inextricably linked to that of related technologies such as 5G, artificial intelligence and cloud computing. Data privacy and security will be the greatest constraint to IoT adoption.

scholarly journals A Research on Encryption Methods and Account Security

2020 ◽  
Vol 3 (1) ◽  
pp. 385-394
Author(s):  
Rıdvan Yayla ◽  
Hakan Üçgün ◽  
Sefa Tunçer
Keyword(s):  
Virtual World ◽  
Data Privacy ◽  
Robot Control ◽  
Cyber Attacks ◽  
Global Pandemic ◽  
Encryption Algorithms ◽  
Asymmetric Encryption ◽  
Authentication Security ◽  
Current Systems

Nowadays, the virtual world is widely used by increasing of the precautions for the global pandemic. Therefore, the membership systems that are created on the basis of the user accounts have an important role in order to meet the increasing requirements. The most important requirements of the current systems are privacy and delivering of the datas as seamlessly for sending of the datas as security and receiving of the end users datas. The security of an account is enhanced by additional measures such as sms systems, authentication, security question, and robot control along with password complexity to prevent cyber attacks. Symmetric and asymmetric encryption algorithms are composed of easy and convenient methods for data privacy and integrity. In this study, the validity of the used encryption methods in today for the security of user accounts, which are becoming widespread in every field, is analyzed and the role of password complexity in account security is investigated.

scholarly journals Android Based Expert System Application for Diagnose COVID-19 Disease: Cases Study of Banyumas Regency

2020 ◽  
Vol 1 (2) ◽  
pp. 26
Author(s):  
Rosyid Ridlo Al Hakim ◽  
Erfan Rusdi ◽  
Muhammad Akbar Setiawan
Keyword(s):  
Artificial Intelligence ◽  
Expert System ◽  
Expert Systems ◽  
System Application ◽  
Confidence Level ◽  
Certainty Factor ◽  
Global Pandemic ◽  
Android Os ◽  
The Status

Since being confirmed by WHO, the status of COVID-19 outbreak has become a global pandemic, the number of cases has been confirmed positive, cured, and even death worldwide. Artificial intelligence in the medical has given rise to expert systems that can replace the role of experts (doctors). Tools to detect someone affected by COVID-19 have not been widely applied in all regions. Banyumas Regency, Indonesia is included confirmed region of COVID-19 cases, and it’s difficult for someone to know the symptoms that are felt whether these symptoms include indications of someone ODP, PDP, positive, or negative COVID-19, and still at least a referral hospital handling COVID-19. Expert system with certainty factor can help someone make a self-diagnose whether including ODP, PDP, positive, or negative COVID-19. This expert system provides ODP diagnostic results with a confidence level of 99.96%, PDP 99.99790%, positive 99.9999997%, negative 99.760384%, and the application runs well on Android OS

scholarly journals Artificial intelligence and machine learning in dynamic cyber risk analytics at the edge

2020 ◽  
Vol 2 (11) ◽  
Author(s):  
Petar Radanliev ◽  
David De Roure ◽  
Rob Walton ◽  
Max Van Kleek ◽  
Rafael Mantilla Montalvo ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Academic Literature ◽  
The Past ◽  
Technological Advances ◽  
New Process ◽  
Technical Systems ◽  
Iot Devices ◽  
Cyber Risk

AbstractWe explore the potential and practical challenges in the use of artificial intelligence (AI) in cyber risk analytics, for improving organisational resilience and understanding cyber risk. The research is focused on identifying the role of AI in connected devices such as Internet of Things (IoT) devices. Through literature review, we identify wide ranging and creative methodologies for cyber analytics and explore the risks of deliberately influencing or disrupting behaviours to socio-technical systems. This resulted in the modelling of the connections and interdependencies between a system's edge components to both external and internal services and systems. We focus on proposals for models, infrastructures and frameworks of IoT systems found in both business reports and technical papers. We analyse this juxtaposition of related systems and technologies, in academic and industry papers published in the past 10 years. Then, we report the results of a qualitative empirical study that correlates the academic literature with key technological advances in connected devices. The work is based on grouping future and present techniques and presenting the results through a new conceptual framework. With the application of social science's grounded theory, the framework details a new process for a prototype of AI-enabled dynamic cyber risk analytics at the edge.

Data Security for Connected Governments and Organisations

2022 ◽  
pp. 191-213
Author(s):  
Heru Susanto ◽  
Leu Fang Yie ◽  
Didi Rosiyadi ◽  
Akbari Indra Basuki ◽  
Desi Setiana
Keyword(s):  
Artificial Intelligence ◽  
Early Warning ◽  
Data Security ◽  
Data Privacy ◽  
Government Agencies ◽  
Security Measures ◽  
Security Issues ◽  
The Impact ◽  
Distributed Technologies

Digital ecosystems have grown rapidly over the years, and governments are investing in digital provision for their processes and services. Despite the advantages of distributed technologies, there are many security issues as well that result in breaches of data privacy with serious impact including legal and reputational implications. To deal with such threats, government agencies need to thoughtfully improve their security defences to protect data and systems by using automation and artificial intelligence (AI), as well as easing the data security measures including early warning of threats and detection. This study provides a comprehensive view of AI and automaton to highlight challenges and issues concerning data security and suggests steps to combat the issues. The authors demonstrate the role of AI-driven security tools and automation to mitigate the impact of data breaches to also propose recommendations for government agencies to enhance their data security protection.

Analysis of Privacy Preservation Techniques in IoT

2019 ◽  
Vol 10 (3) ◽  
pp. 27-33
Author(s):  
Ravindra Sadashivrao Apare ◽  
Satish Narayanrao Gujar
Keyword(s):  
Artificial Intelligence ◽  
Time Series ◽  
Data Privacy ◽  
Privacy Preservation ◽  
Time Series Data ◽  
Low Cost ◽  
Series Data ◽  
Automation System ◽  
Sensing Technology ◽  
Iot Devices

IoT (Internet of Things) is a sophisticated analytics and automation system that utilizes networking, big data, artificial intelligence, and sensing technology to distribute absolute systems for a service or product. The major challenges in IoT relies in security restrictions related with generating low cost devices, and the increasing number of devices that generates further opportunities for attacks. Hence, this article intends to develop a promising methodology associated with data privacy preservation for handling the IoT network. It is obvious that the IoT devices often generate time series data, where the range of respective time series data can be extremely large.

Analysis of Privacy Preservation Techniques in IoT

2021 ◽  
pp. 1343-1351
Author(s):  
Ravindra Sadashivrao Apare ◽  
Satish Narayanrao Gujar
Keyword(s):  
Artificial Intelligence ◽  
Time Series ◽  
Data Privacy ◽  
Privacy Preservation ◽  
Time Series Data ◽  
Low Cost ◽  
Series Data ◽  
Automation System ◽  
Sensing Technology ◽  
Iot Devices

IoT (Internet of Things) is a sophisticated analytics and automation system that utilizes networking, big data, artificial intelligence, and sensing technology to distribute absolute systems for a service or product. The major challenges in IoT relies in security restrictions related with generating low cost devices, and the increasing number of devices that generates further opportunities for attacks. Hence, this article intends to develop a promising methodology associated with data privacy preservation for handling the IoT network. It is obvious that the IoT devices often generate time series data, where the range of respective time series data can be extremely large.

scholarly journals Operationalizing Critical Race Theory in the Marketplace

2020 ◽  
pp. 074391562096411
Author(s):  
Sonja Martin Poole ◽  
Sonya A. Grier ◽  
Kevin D. Thomas ◽  
Francesca Sobande ◽  
Akon E. Ekpo ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Critical Race Theory ◽  
Critical Theory ◽  
Paradigm Shift ◽  
Analytical Tool ◽  
Critical Race ◽  
Race Theory ◽  
Systemic Oppression ◽  
The Way

Race is integral to the functioning and ideological underpinnings of marketplace actions yet remains undertheorized in marketing. To understand and transform the insidious ways in which race operates, the authors examine its impact in marketplaces and how these effects are shaped by intersecting forms of systemic oppression. They introduce critical race theory (CRT) to the marketing community as a useful framework for understanding consumers, consumption, and contemporary marketplaces. They outline critical theory traditions as utilized in marketing and specify the particular role of CRT as a lens through which scholars can understand marketplace dynamics. The authors delineate key CRT tenets and how they may shape the way scholars conduct research, teach, and influence practice in the marketing discipline. To clearly highlight CRT’s overall potential as a robust analytical tool in marketplace studies, the authors elaborate on the application of artificial intelligence to consumption markets. This analysis demonstrates how CRT can support an enhanced understanding of the role of race in markets and lead to a more equitable version of the marketplace than what currently exists. Beyond mere procedural modifications, applying CRT to marketplace studies mandates a paradigm shift in how marketplace equity is understood and practiced.

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