Faculty of Technoscience

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https://dir.muni.ac.ug/handle/20.500.12260/2

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Browsing Faculty of Technoscience by Author "Bala, Indu"

Now showing 1 - 3 of 3
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    Analysing the connection between ai and industry 4.0 from a cybersecurity perspective: defending the smart revolution
    (Mesopotamian Journal of Big Data, 2023-05-05) Bala, Indu; Mijwil, Maad M.; Ali, Guma; Sadıkoğlu, Emre
    In recent years, the significance and efficiency of business performance have become dependent heavily on digitization, as jobs in companies are seeking to be transformed into digital jobs based on smart systems and applications of the fourth industrial revolution. Cybersecurity systems must interact and continuously cooperate with authorized users through the Internet of Things and benefit from corporate services that allow users to interact in a secure environment free from electronic attacks. Artificial intelligence methods contribute to the design of the Fourth Industrial Revolution principles, including interoperability, information transparency, technical assistance, and decentralized decisions. Through this design, security gaps may be generated that attackers can exploit in order to be able to enter systems, control them, or manipulate them. In this paper, the role of automated systems for digital operations in the fourth industrial revolution era will be examined from the perspective of artificial intelligence and cybersecurity, as well as the most significant practices of artificial intelligence methods. This paper concluded that artificial intelligence methods play a significant role in defending and protecting cybersecurity and the Internet of Things, preventing electronic attacks, and protecting users' privacy.
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    The effect of human-computer interaction on new applications by exploring the use case of ChatGPT in healthcare services. In modern technology in healthcare and medical education: Blockchain, IoT, AR, and VR
    (IGI Global, 2024) Mijwil, Maad M.; Naji, Aseel Shakir; Doshi, Ruchi; Hiran, Kamal Kant; Bala, Indu; Ali, Guma
    Human-Computer interaction (HCI) is a domain that focuses on growing the interaction between humans and computer systems by designing and developing user interfaces that are efficient and delightful to use. In this chapter, the authors focus on the importance of deep human-computer interaction on new applications with an emphasis on using ChatGPT applications in the health services domain. This chapter provides full details on the importance of executing ChatGPT in various health-related scenarios while highlighting the importance of HCI to enhance user interactions in personalized medical advice in a ChatGPT application. This chapter concludes that the capabilities of ChatGPT and artificial intelligence applications can revolutionize the healthcare industry by enhancing the accessibility and effectiveness of new media communications between the user and applications while creating innovative resolutions to improve healthcare services.
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    Sensing of type 2 diabetes patients based on Internet of Things solutions: An Extensive survey
    (IGI Global, 2024) Mijwil, Maad M.; Bala, Indu; Ali, Guma; Aljanabi, Mohammad; Abotaleb, Mostafa; Doshi, Ruchi; Hiran, Kamal Kant; El-Kenawy, El-Sayed M.
    Internet of things solutions have brought about a significant revolution in the development of healthcare by providing remote monitoring capabilities and providing doctors with reports on patients in real-time, which leads to developing the care of patients with type 2 diabetes and enhancing their health condition. Through several sensors, IoT devices can collect patients' health data, such as glucose level, blood pressure, heart rate, and physical activity, so that healthcare workers can assess patients' health status and disease development within the body. These devices contribute to saving patients' lives by providing continuous monitoring of vital signs and disease management by physicians and healthcare workers. In this context, this article contributes to reviewing the development of IoT solutions in providing information and mechanisms adopted in monitoring patients with type 2 diabetes, data security issues, privacy concerns, and interoperability.