Data Science and AI in IoT Based Smart Healthcare: Issues, Challenges and Case Study

Saif, Sohail; Datta, Debabrata; Saha, Anindita; Biswas, Suparna; Chowdhury, Chandreyee

doi:10.1007/978-3-030-52067-0_19

Cited by 7 publications

(4 citation statements)

References 36 publications

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“…Additionally, ethical considerations encompass the responsible use of data, protection against algorithmic discrimination, and the potential impact on healthcare disparities. Striking a balance between leveraging the benefits of nature‐inspired algorithms for improved healthcare outcomes and upholding ethical principles is essential for fostering trust among patients, healthcare providers, and the broader community, ultimately contributing to the responsible and ethical deployment of IoT‐based healthcare services 142 …”

Section: Open Issuesmentioning

confidence: 99%

The applications of nature‐inspired algorithms in Internet of Things‐based healthcare service: A systematic literature review

Amiri,

Heidari,

Zavvar

et al. 2024

Trans Emerging Tel Tech

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Nature‐inspired algorithms revolve around the intersection of nature‐inspired algorithms and the IoT within the healthcare domain. This domain addresses the emerging trends and potential synergies between nature‐inspired computational approaches and IoT technologies for advancing healthcare services. Our research aims to fill gaps in addressing algorithmic integration challenges, real‐world implementation issues, and the efficacy of nature‐inspired algorithms in IoT‐based healthcare. We provide insights into the practical aspects and limitations of such applications through a systematic literature review. Specifically, we address the need for a comprehensive understanding of the applications of nature‐inspired algorithms in IoT‐based healthcare, identifying gaps such as the lack of standardized evaluation metrics and studies on integration challenges and security considerations. By bridging these gaps, our paper offers insights and directions for future research in this domain, exploring the diverse landscape of nature‐inspired algorithms in healthcare. Our chosen methodology is a Systematic Literature Review (SLR) to investigate related papers rigorously. Categorizing these algorithms into groups such as genetic algorithms, particle swarm optimization, cuckoo algorithms, ant colony optimization, other approaches, and hybrid methods, we employ meticulous classification based on critical criteria. MATLAB emerges as the predominant programming language, constituting 37.9% of cases, showcasing a prevalent choice among researchers. Our evaluation emphasizes adaptability as the paramount parameter, accounting for 18.4% of considerations. By shedding light on attributes, limitations, and potential directions for future research and development, this review aims to contribute to a comprehensive understanding of nature‐inspired algorithms in the dynamic landscape of IoT‐based healthcare services.

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Section: Open Issuesmentioning

confidence: 99%

The applications of nature‐inspired algorithms in Internet of Things‐based healthcare service: A systematic literature review

Amiri,

Heidari,

Zavvar

et al. 2024

Trans Emerging Tel Tech

View full text Add to dashboard Cite

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“…Table 7. Various algorithms and their applications in data analysis for health sciences [136][137][138][139][140][141].…”

Section: Artificial Intelligence (Ai) and Machine Learning (Ml) Appli...mentioning

confidence: 99%

Exploring the Intersection of Geophysics and Diagnostic Imaging in the Health Sciences

Singh,

Nayak,

Behl

et al. 2024

Diagnostics

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To develop diagnostic imaging approaches, this paper emphasizes the transformational potential of merging geophysics with health sciences. Diagnostic imaging technology improvements have transformed the health sciences by enabling earlier and more precise disease identification, individualized therapy, and improved patient care. This review article examines the connection between geophysics and diagnostic imaging in the field of health sciences. Geophysics, which is typically used to explore Earth’s subsurface, has provided new uses of its methodology in the medical field, providing innovative solutions to pressing medical problems. The article examines the different geophysical techniques like electrical imaging, seismic imaging, and geophysics and their corresponding imaging techniques used in health sciences like tomography, magnetic resonance imaging, ultrasound imaging, etc. The examination includes the description, similarities, differences, and challenges associated with these techniques and how modified geophysical techniques can be used in imaging methods in health sciences. Examining the progression of each method from geophysics to medical imaging and its contributions to illness diagnosis, treatment planning, and monitoring are highlighted. Also, the utilization of geophysical data analysis techniques like signal processing and inversion techniques in image processing in health sciences has been briefly explained, along with different mathematical and computational tools in geophysics and how they can be implemented for image processing in health sciences. The key findings include the development of machine learning and artificial intelligence in geophysics-driven medical imaging, demonstrating the revolutionary effects of data-driven methods on precision, speed, and predictive modeling.

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“…They emphasize the significance of NLP in facilitating smart healthcare and its potential to revolutionize how healthcare is delivered and improve patient outcomes. S. Saif et al [187] explored the role of the IoT and AI in smart healthcare. They review recent developments in the field, including case studies on drug discovery and predicting chronic diseases such as heart disease and kidney-related ailments using ML and DL techniques.…”

Section: Smart Healthcarementioning

confidence: 99%

Integration of IoT-Enabled Technologies and Artificial Intelligence (AI) for Smart City Scenario: Recent Advancements and Future Trends

Alahi

Sukkuea

Tina

et al. 2023

Sensors

147

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As the global population grows, and urbanization becomes more prevalent, cities often struggle to provide convenient, secure, and sustainable lifestyles due to the lack of necessary smart technologies. Fortunately, the Internet of Things (IoT) has emerged as a solution to this challenge by connecting physical objects using electronics, sensors, software, and communication networks. This has transformed smart city infrastructures, introducing various technologies that enhance sustainability, productivity, and comfort for urban dwellers. By leveraging Artificial Intelligence (AI) to analyze the vast amount of IoT data available, new opportunities are emerging to design and manage futuristic smart cities. In this review article, we provide an overview of smart cities, defining their characteristics and exploring the architecture of IoT. A detailed analysis of various wireless communication technologies employed in smart city applications is presented, with extensive research conducted to determine the most appropriate communication technologies for specific use cases. The article also sheds light on different AI algorithms and their suitability for smart city applications. Furthermore, the integration of IoT and AI in smart city scenarios is discussed, emphasizing the potential contributions of 5G networks coupled with AI in advancing modern urban environments. This article contributes to the existing literature by highlighting the tremendous opportunities presented by integrating IoT and AI, paving the way for the development of smart cities that significantly enhance the quality of life for urban dwellers while promoting sustainability and productivity. By exploring the potential of IoT, AI, and their integration, this review article provides valuable insights into the future of smart cities, demonstrating how these technologies can positively impact urban environments and the well-being of their inhabitants.

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Data Science and AI in IoT Based Smart Healthcare: Issues, Challenges and Case Study

Cited by 7 publications

References 36 publications

The applications of nature‐inspired algorithms in Internet of Things‐based healthcare service: A systematic literature review

The applications of nature‐inspired algorithms in Internet of Things‐based healthcare service: A systematic literature review

Exploring the Intersection of Geophysics and Diagnostic Imaging in the Health Sciences

Integration of IoT-Enabled Technologies and Artificial Intelligence (AI) for Smart City Scenario: Recent Advancements and Future Trends

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