International Journal of Computing and Related Technologies

A Review of the Importance of Digital Signal Processing in the Medical field

Junid Ahmed Ansari — 2024-04-26

A paradigm change in healthcare has been sparked by recent advances in medical technology and the growth of digital health data. This research explores the critical role that data signal processing (DSP) plays in the medical field and how it might transform treatment options, diagnostics, and the standard of care in general. An overview of the growing amount of healthcare data gathered from several sources, such as wearable technology, digital medical records, medical imaging, and continuous patient monitoring devices, is given in the first part. It draws attention to the difficulties presented by the sheer volume, velocity, and diversity of data related to health, which need complex processing techniques to obtain useful insights. Moreover, DSP is essential to the creation of state-of-the-art medical devices, including wearable and implantable health monitoring ones. DSP makes a major contribution to personalized medicine in clinical settings by improving medication techniques. The findings emphasize how crucial DSP is for obtaining relevant patient information from complex biological signals. It looks at how signal processing methods—from simple methods to sophisticated machine learning algorithms—are used to improve signal quality, reduce noise, and reveal patterns in medical data. This study highlights the critical role that DSP plays in the medical industry, especially when it comes to managing digital health records, Internet of Things (IoT) devices, health-related data, prescription methods, and improving healthcare as a whole.

A Comprehensive Review of 5G Technology and Beyond

Rooh ul Hasnain — 2024-04-26

The advent of 5G technology marks a transformative phase in wireless communication, promising unprecedented advancements in data speed, low latency, and connectivity. This research paper delves into the profound implications of 5G on next-generation wireless communication systems. Beginning with an exploration of the evolutionary trajectory of wireless technologies, the study provides an in-depth overview of 5G, elucidating its key features and architecture, including the Radio Access Network (RAN), Core Network (CN), and Network Slicing. The paper scrutinizes the multifaceted impacts of 5G on next-gen wireless communication, ranging from enhanced data speeds and real-time communication to the proliferation of Internet of Things (IoT) devices. Additionally, it assesses the diverse applications of 5G across sectors such as healthcare, smart cities, automotive, industrial IoT, and entertainment. Amidst these promising prospects, the research critically examines challenges such as security concerns, infrastructure requirements, and spectrum allocation. Looking ahead, the study anticipates future trends in 5G and beyond, including the emergence of 6G and advanced use cases. Through case studies, the paper analyzes successful 5G deployments and extracts valuable lessons for future implementations. In conclusion, the findings contribute to the understanding of 5G's transformative potential, offering recommendations for future research and considerations for the global adoption of this groundbreaking technology.

IoT in Industry 4.0: Applications and challenges

Dua Noor — 2024-04-26

The Internet of Things (IoT) enabled devices involve different types of data. These devices named as sensors are responsible for generating real world data based on the physical properties they measure. For example, temperature sensor produced temperature readings. Sensor collects data continuously or periodically, providing a stream of information that reflects changes in environment or conditions. Relating to the IoT, data from sensors transmitted to the central system usually through wireless communication protocols. The collected data can be utilized for various purposes such as monitoring, analysis and decision making or triggering actions. This study provides a review of IoT and industrial IoT (IIoT). Further, this paper highlights Applications, challenges and tools in detail.

Internet of Medical Things (IoMT) for Remote Healthcare Monitoring Using Wearable Sensors

S M Nazmuz Sakib — 2024-04-26

In the healthcare industry, the most recent innovations and developments in communication and informational technique play a critical role. These developments paved the mode for the IoMT (Internet of Medical Things), which allows for persistent, distant, and genuine patient monitoring. The capacity, connectivity protocols, big data and volume of data, adaptability, durability, data processing, data acquisition system, data handling, and analytics accessibility, economic viability, privacy and security, and power efficiency are all problems that IoMT architectures confront. The basic aim of his research is to employ remote health monitoring (RHM) and IoMT to identify health monitor easy approach to improve medical residing conditions. Moreover, the use of IoMT and Medical knowledge RHM to strengthen the protection, diagnosis, prognosis, and therapeutic capacities of the Internet of medical things is addressed. The IoMT (Internet of Medical Things) involves a network of health care devices and individuals that exchange medical data via wireless communications. With the rising expansion of the population and the use of advanced technology, medical expenses and medical cost has significantly increased. The coupling of IoMT with medical healthcare has the potential to increase people's lives, deliver effective medical therapy, and establish pocket-friendly approaches. This study discusses the current state of IoT in the medical business, as well as plans for development and innovation strategies and implementations. The adoption of IoT in the medical sector has evolved worldwide, but it still encounters numerous architectural and technological hurdles. To find a solution to the mentioned problems, current research illustrates a basic IoMT design that comprises 3 foundational pillars: data gathering, connection gateways, and servers/cloud. Ultimately, this article examined the possibilities and potential of IoMT in practice, as well as the associated remarkable research concern.

Relating different Artificial Intelligence approaches for Animals disease outbreak detection

Hamza Ahmed — 2024-04-26

The past two years have witnessed a worrying surge in animal disease outbreaks, with African swine fever, foot-and-mouth disease, and bird flu wreaking havoc on animal populations and human livelihoods. Millions of animals have succumbed to these highly contagious diseases, causing severe economic losses, disrupting livestock industries, and threatening global food security. Data reveals the alarming occurrence, distribution, and impact of these outbreaks, while highlighting the challenges in controlling them and the potential public health risks. Innovative approaches like AI-powered disease models and international cooperation are crucial to tackle this crisis and mitigate future threats. The abstract is about finding disease outbreak of different natures, so we can predict it before it is going to hit in future. By integrating existing information with the potential of cutting-edge solutions of Artificial Intelligence and Machine learning, our models of SVM with accuracy and precision of 0.9041%, recall 1.0 and ROC AUC of 0.05. The confusion matrix indicates 0 true positive predictions and 0 false negative predictions. These are the models used and results are mentioned respectfully. KNN with accuracy of 99%, precision of 1.0, Recall 0.99% and ROC AUC of 0.99%. The confusion matrix indicates 489 true positive predictions and 4 false negative predictions Naive Bayes with accuracy of 0.99, precision of 1.0, recall and ROC AUC 0.99. The confusion matrix indicates 489 true positive predictions and 37 false negative predictions.