https://ijsdcs.com/index.php/TLIoT/issue/feedTransactions on Latest Trends in IoT2023-12-10T08:23:11+00:00Rita Sahaniijsdcs@gmail.comOpen Journal Systems<p>The Transactions on Latest Trends in IoT(TLIoT) welcomes papers on broad aspects of IoT that constitute advances in the overall field including, but not limited to, cognition and AI, automated reasoning and inference, case-based reasoning, commonsense reasoning, computer vision, constraint processing, ethical AI, heuristic search, human interfaces, intelligent robotics, knowledge representation, machine learning, multi-agent systems, natural language processing, planning and action, and reasoning under uncertainty. The journal reports results achieved in addition to proposals for new ways of looking at IoT problems, both of which must include demonstrations of value and effectiveness.</p><p>Papers describing applications of IoT are also welcome, but the focus should be on how new and novel IoT methods advance performance in application areas, rather than a presentation of yet another application of conventional IoT methods. Papers on applications should describe a principled solution, emphasize its novelty, and present an indepth evaluation of the IoT techniques being exploited.</p><p>Apart from regular papers, the journal also accepts Research Notes, Research Field Reviews, Position Papers, and Book Reviews . The journal will also consider summary papers that describe challenges and competitions from various areas of IoT. Such papers should motivate and describe the competition design as well as report and interpret competition results, with an emphasis on insights that are of value beyond the competition itself.</p><p>From time to time, there are special issues devoted to a particular topic. Such special issues must always have open calls-for-papers.</p><p>The issue is released end of the year i.e December (Yearly) </p><p> </p><p>TLIoT is a double-blind peer-reviewed journal indexed in several databases like google scholar, Wos, Dooj, EI </p><p><span>Note: If your article is selected, there is an open access fee of $2100 USD, which may be waived based on the paper's quality.</span></p><p> JCR Impact Factor : 1.65 (2019)</p><p> JCR Impact Factor : 1.93 (2020)</p><p> JCR Impact Factor : 2.05 (2021)</p><p> JCR Impact Factor : 3.3 (2022)</p><p>JCR Impact Factor : Under Evaluation (2023)</p>https://ijsdcs.com/index.php/TLIoT/article/view/315Empowering Diabetes Management through IoT: A Comprehensive Research Study on Diabetic Health Monitoring and Control2023-12-10T08:23:11+00:00Priyanka Kumaripriyanka123@gmail.com<p>The prevalence of diabetes has reached epidemic proportions worldwide, necessitating innovative and effective approaches for its management. The integration of Internet of Things (IoT) technology with diabetic care holds great promise in revolutionizing the way diabetes is monitored and controlled. This research paper presents a comprehensive study that explores the potential of IoT-based solutions for diabetes management.</p><p>The objective of this research is to evaluate the impact of IoT on various aspects of diabetic health, including real-time monitoring of blood glucose levels, insulin administration, dietary management, physical activity tracking, and patient-doctor communication. The study also investigates the potential benefits of incorporating wearable devices, continuous glucose monitoring (CGM) systems, and smart insulin pumps into diabetes care routines.</p><p>To conduct this research, a sample group of diabetic patients is recruited, and IoT-enabled devices are deployed to monitor their health parameters over an extended period. Data collected from these devices are analyzed, and their impact on diabetes management outcomes is assessed. Furthermore, the research explores the integration of artificial intelligence and machine learning algorithms to provide personalized insights and predictive capabilities, enhancing the overall efficacy of diabetes care.</p><p>The paper also addresses potential challenges related to data security, privacy concerns, and interoperability of various IoT devices and proposes strategies to mitigate these issues. Additionally, it highlights the importance of user-friendly interfaces and seamless integration of IoT devices with existing healthcare systems to encourage widespread adoption among both patients and healthcare providers.</p>2023-08-01T10:11:01+00:00Copyright (c) 2023 Transactions on Latest Trends in IoThttps://ijsdcs.com/index.php/TLIoT/article/view/345Unraveling the Complexities of Data Governance with Strategies, Challenges, and Future Directions2023-12-10T08:23:11+00:00Ronak Pansararonakpansara95@gmail.com<p>Data governance is a critical component of modern data management, ensuring data integrity, security, and compliance. This research paper delves into the multifaceted landscape of data governance, exploring strategies for establishing effective governance frameworks, addressing the inherent challenges, and charting the future directions of this evolving field. The paper examines the key principles and practices of data governance, highlighting the role of data stewards, access controls, and compliance monitoring. It delves into the challenges organizations face in implementing robust data governance, including issues related to data privacy, organizational culture, and technology integration. Additionally, the paper explores emerging trends in data governance, such as the impact of artificial intelligence and the evolving regulatory landscape. By providing a comprehensive overview of data governance, this research contributes to a deeper understanding of how organizations can harness the power of their data assets while ensuring responsible and compliant data management practices.</p>2023-10-18T00:00:00+00:00Copyright (c) 2023 Transactions on Latest Trends in IoThttps://ijsdcs.com/index.php/TLIoT/article/view/316Revolutionizing Cancer Research: Leveraging AI for Precision Diagnosis, Personalized Treatment, and Novel Therapeutic Discoveries2023-12-10T08:23:11+00:00pankaj jlotapankaj23@gmail.com<div class="flex-1 overflow-hidden"><div class="react-scroll-to-bottom--css-sfsjw-79elbk h-full dark:bg-gray-800"><div class="react-scroll-to-bottom--css-sfsjw-1n7m0yu"><div class="flex flex-col text-sm dark:bg-gray-800"><div class="group w-full text-gray-800 dark:text-gray-100 border-b border-black/10 dark:border-gray-900/50 bg-gray-50 dark:bg-[#444654]"><div class="flex p-4 gap-4 text-base md:gap-6 md:max-w-2xl lg:max-w-[38rem] xl:max-w-3xl md:py-6 lg:px-0 m-auto"><div class="relative flex w-[calc(100%-50px)] flex-col gap-1 md:gap-3 lg:w-[calc(100%-115px)]"><div class="flex flex-grow flex-col gap-3"><div class="min-h-[20px] flex items-start overflow-x-auto whitespace-pre-wrap break-words"><div class="markdown prose w-full break-words dark:prose-invert light"><p>In recent years, cancer has emerged as a formidable global health challenge, necessitating innovative approaches to enhance early detection, precise diagnosis, and effective treatment strategies. Artificial Intelligence (AI) has emerged as a game-changing technology with the potential to revolutionize cancer research. This research paper explores the transformative role of AI in cancer research, focusing on its application in data-driven analysis of vast genomics and clinical datasets to identify biomarkers, predict treatment responses, and develop personalized therapies. Additionally, it delves into the integration of AI-powered imaging techniques to improve tumor detection and classification, enabling early intervention. The paper also sheds light on AI-enabled drug discovery, accelerating the identification of novel therapeutic targets and repurposing existing drugs for cancer treatment. Despite the numerous benefits, ethical considerations, data privacy concerns, and the need for seamless integration of AI in clinical practice are discussed. By presenting a comprehensive overview of AI's contributions to cancer research, this paper highlights the immense potential of AI in advancing the fight against cancer and improving patient outcomes.</p></div></div></div><div class="flex justify-between lg:block"> </div></div></div></div></div></div></div></div><div class="absolute bottom-0 left-0 w-full border-t md:border-t-0 dark:border-white/20 md:border-transparent md:dark:border-transparent md:bg-vert-light-gradient bg-white dark:bg-gray-800 md:!bg-transparent dark:md:bg-vert-dark-gradient pt-2 md:pl-2 md:w-[calc(100%-.5rem)]"> </div>2023-08-01T10:11:01+00:00Copyright (c) 2023 Transactions on Latest Trends in IoThttps://ijsdcs.com/index.php/TLIoT/article/view/317A Comprehensive Research Study on Eye Flu - Causes, Contagion, and Control Strategies2023-12-10T08:23:11+00:00priya Makanpriya34@gmail.com<p>Eye flu, also known as conjunctivitis or pink eye, is a highly contagious ocular infection that affects millions of people worldwide each year. Despite its prevalence and potential impact on public health, there is a significant gap in our understanding of the underlying causes, modes of transmission, and effective control strategies for this ailment. This research paper aims to address these knowledge gaps by conducting a systematic investigation into various aspects of eye flu.</p><p>The primary objectives of this study are to identify the causative agents responsible for eye flu, analyze the modes of transmission, assess the risk factors that contribute to its spread, and evaluate existing preventive and treatment measures. A comprehensive literature review is conducted to collate and synthesize the latest findings from peer-reviewed journals, health agencies, and clinical reports.</p><p>The paper also presents the results of an original research survey that was designed to gauge the public's awareness, perception, and adherence to preventive measures concerning eye flu. Through statistical analysis, this study aims to provide insights into the public's knowledge gaps and attitudes, helping to inform the development of more effective public health campaigns.</p><p>Furthermore, the research delves into the challenges faced by healthcare professionals in diagnosing and managing eye flu cases, particularly during outbreaks. By analyzing the shortcomings in the existing diagnostic tools and treatment options, this paper proposes innovative approaches for accurate and timely detection, as well as the development of more targeted therapies.</p>2023-08-01T10:11:01+00:00Copyright (c) 2023 Transactions on Latest Trends in IoThttps://ijsdcs.com/index.php/TLIoT/article/view/334Unlocking the Potential of IoT: Innovations, Challenges, and Future Horizons2023-12-10T08:23:11+00:00Madhu kapoorMadhu97@gmail.com<p>This paper provides a comprehensive exploration of the Internet of Things (IoT) landscape, focusing on its transformative impact, evolving technologies, and future prospects. It delves into the diverse applications of IoT in domains such as smart cities, industrial automation, healthcare, and agriculture. The paper highlights the critical role of IoT in data-driven decision-making, efficiency improvements, and sustainable practices.</p><p>Moreover, it addresses the challenges faced by IoT, including security, privacy, and interoperability issues, and presents insights into potential solutions. The paper envisions a future where IoT reshapes industries, creating interconnected ecosystems that enhance productivity, resource management, and quality of life.</p><p>As the world continues its journey into the IoT era, this paper serves as a valuable resource for researchers, engineers, policymakers, and organizations seeking to harness the full potential of IoT technologies for a more connected and intelligent future.</p>2023-10-11T00:00:00+00:00Copyright (c) 2023 Transactions on Latest Trends in IoThttps://ijsdcs.com/index.php/TLIoT/article/view/348Navigating Data Management in the Cloud - Exploring Limitations and Opportunities2023-12-10T08:23:11+00:00Ronak Pansararonakpansara95@gmail.com<p>This research paper delves into the realm of data management in the cloud, shedding light on the challenges and possibilities within this transformative landscape. As organizations increasingly migrate their data to cloud environments, understanding the intricacies of cloud-based data management becomes essential. We explore the limitations that can impede efficient data management in the cloud, including security concerns, data transfer bottlenecks, and regulatory compliance. Simultaneously, we uncover the opportunities offered by cloud-based data management, such as scalability, cost-efficiency, and enhanced data analytics. By examining case studies and empirical data, we provide valuable insights into real-world implementations of cloud data management. This paper aims to equip organizations with a nuanced understanding of the cloud's potential, enabling them to navigate the skies of data management effectively.</p>2023-11-01T00:00:00+00:00Copyright (c) 2023 Transactions on Latest Trends in IoThttps://ijsdcs.com/index.php/TLIoT/article/view/335Edge Computing in IoT: Enhancing Scalability, Efficiency, and Real-Time Decision-Making2023-12-10T08:23:11+00:00Navneet Kapoornavneet@gmail.com<p>This paper explores the paradigm of edge computing within the Internet of Things (IoT) ecosystem, with a focus on its transformative influence on IoT systems. Edge computing brings computation and data processing closer to the data source, allowing for real-time decision-making, reduced latency, and enhanced scalability.</p><p>The paper discusses the applications of edge computing in various IoT domains, including smart cities, industrial automation, and autonomous vehicles. It highlights how edge computing is revolutionizing data analytics and enabling efficient resource management.</p><p>Challenges associated with edge computing in IoT, such as security, device constraints, and interoperability, are also addressed.</p><p>The paper foresees a future where edge computing becomes a central component of IoT architectures, fostering a new era of real-time, data-driven applications and services.</p><p>As the convergence of edge computing and IoT continues to shape the technological landscape, this paper offers insights for researchers, engineers, and policymakers aiming to harness the full potential of edge-based IoT systems.</p>2023-10-16T00:00:00+00:00Copyright (c) 2023 Transactions on Latest Trends in IoThttps://ijsdcs.com/index.php/TLIoT/article/view/355Digital Disruption in Transforming AgTech Business Models for a Sustainable Future2023-12-10T08:23:11+00:00Ronak Pansararonakpansara95@gmail.com<p>The digital transformation of business models in the agricultural technology (AgTech) landscape represents a paradigm shift in the agriculture sector. This research paper explores the multifaceted impact of digital technologies on AgTech, focusing on the innovative ways in which it is reshaping traditional agricultural practices and enabling sustainable, data-driven solutions. From precision agriculture to supply chain optimization, this study delves into the key drivers and challenges of this transformation, offering insights into the dynamic AgTech ecosystem. It also highlights the potential benefits, risks, and the imperative for stakeholders to embrace digital strategies for a more efficient, productive, and environmentally friendly agriculture industry.</p>2023-12-16T00:00:00+00:00Copyright (c) 2023 Transactions on Latest Trends in IoThttps://ijsdcs.com/index.php/TLIoT/article/view/406Framework Development for Artificial Intelligence Integration in Healthcare: Optimizing Patient Care and Operational Efficiency2023-12-10T08:23:11+00:00Balaram Yadav Kasulakramyadav446@gmail.com<p>The integration of Artificial Intelligence (AI) in healthcare presents a promising avenue for revolutionizing patient care and operational processes. This paper presents a comprehensive theoretical framework aimed at facilitating the seamless integration of AI technologies within the healthcare sector. The development of this framework involved an extensive synthesis of existing literature encompassing AI applications in healthcare, technology integration frameworks, and operational strategies. Leveraging insights from established practices and emerging trends, the framework devised offers a structured approach elucidating the strategic incorporation of AI in diverse healthcare domains. The proposed framework emphasizes personalized patient care, clinical decision support, predictive analytics, and operational streamlining through AI adoption. Key considerations such as ethical guidelines, regulatory compliance, interoperability, and scalability are integrated into the framework to ensure successful AI implementation in healthcare settings. Furthermore, the framework delineates implementation strategies, stakeholder engagement models, and a roadmap for the adoption and iterative refinement of AI-driven solutions within healthcare institutions. This research contributes a comprehensive theoretical framework tailored to optimize the assimilation of AI technologies in healthcare, aiming to enhance patient outcomes, operational efficiency, and pave the way for future advancements in AI-enabled healthcare systems.</p>2023-11-14T00:00:00+00:00Copyright (c) 2023 Transactions on Latest Trends in IoT