Journal of Information Technology and Sciences

Supply Chain Management Benefits from the Internet of Things (IoT)

Parul Kashyap — 2024-01-19

To give a thorough analysis of the many advantages and difficulties related to the integration of the Internet of Things, this research paper explores the significant impact of the IoT on the field of supply chain management. IoT emerges as a transformative force, providing real-time visibility, predictive analytics, and improved operational efficiency as businesses navigate the complexity of contemporary supply chains. Through an examination of these aspects, the study clarifies how IoT helps businesses streamline decision-making procedures, cut lead times, and enhance overall cost-effectiveness.

Nevertheless, there are obstacles in the way of IoT integration, and issues like data security, interoperability, and resistance to change must be carefully considered. This paper presents real-world examples of successful IoT implementations in supply chain management, drawing on a methodical research methodology that included case studies, surveys, and interviews. The examples highlight the tangible benefits achieved, the challenges faced, and the lessons learned. The research provides insightful information for companies considering or undergoing IoT adoption in their supply chain processes through these case studies. The paper also discusses new developments and prospects, offering an outlook on how the Internet of Things will continue to change supply chain management in the future.

Software Reliability Trends and Mechanism: A Conceptual Framework

Arpita Tewari — 2024-02-12

Software Reliability is an intra-disciplinary research area that paves the way for finding a perspective that prioritizes the needs and satisfaction of customers about software quality. This paper attempts to establish practical and useful capabilities of software reliability in boisterous paradigms, with a focus on reliability improvement that has a direct bearing on the software's caliber. This paper observes the denotation of software reliability and reviews reliability analysis techniques, where the design process is recognized as the primary origin of software defects. The emergence of various design methodologies for reliability models has been a direct consequence of this phenomenon. A comprehensive framework has been presented in this study for the selection of a reliability growth model. The framework proposed in this study aims to tackle the challenge of determining and effectively utilizing qualitative information for reliability analysis. The framework utilized in this study is founded upon the review of the literature approach. Its purpose is to augment the effectiveness of reliability prediction in addressing qualitative processes.

The present paper suggests the extraction of information from diverse literature reviews, design tools, and databases, which will then be integrated into this framework. Through the review of the literature, the writer has recognized a structure comprising qualitative components that can be utilized to assess, understand, and ultimately improve the degree of dependability in a versatile manner.

Advancements and Applications of Generative Artificial Intelligence

Dattatray G. Takale — 2024-03-14

As a transformative technology, generative artificial intelligence (AI) has emerged in a variety of fields such as image synthesis, text generation, music composition and creative design with diverse applications. The purpose of this paper is to provide a comprehensive overview of recent advances in generative AI techniques. To begin with, we examine the evolution of generative models from traditional methods to state-of-the-art deep learning approaches like Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Transformers. During the following part of the paper, we discuss generative AI and its wide-ranging applications across a wide range of sectors, such as creating realistic images, writing natural language texts, composing music, and enabling creative design tasks. Our discussion also includes potential future research and development directions along with the challenges and ethical considerations associated with generative AI. A comprehensive overview of generative AI is provided in this review for researchers, practitioners, and enthusiasts.

Academic AI: Your Personal Educational AI Companion for Academic Excellence

Shravani Khot — 2024-03-22

This ambitious project delves into the pressing research challenge of augmenting students’ access to valuable information by harnessing the capabilities of an AI-powered chatbot that draws upon professors’ meticulously curated notes. The methodological approach employed for this endeavour is a comprehensive one, entailing the development of a sophisticated chatbot application. This application seamlessly integrates the prowess of ChatGPT’s natural language API, utilizes Firebase to establish a robust backend infrastructure, and adopts React Native to craft an intuitive and user-friendly interface. The outcomes of this undertaking are nothing short of remarkable. The project has given birth to an innovative application that proficiently ingests notes furnished by professors. Leveraging the unparalleled natural language processing capabilities of ChatGPT, it deftly generates responses to the myriad inquiries posed by inquisitive students, all while drawing upon the rich repository of professors’ notes. In essence, this extensive and groundbreaking project stands as a testament to the fusion of state-of-the-art AI and mobile development technologies. It has ushered in a transformative paradigm, presenting a novel avenue for students to effortlessly access the invaluable materials meticulously curated by their educators. This, in turn, holds great promise for enhancing the quality of learning and boosting overall student engagement.

IoT-Enabled Systems for Automated Detection and Rescue of Vehicle Accidents

S. Sajithabanu — 2024-04-03

Accident Detection and Rescue Systems (ADRSs) are crucial in mitigating the consequences of accidents by promptly responding to incidents, thereby averting injuries, losses, damages, and property destruction. With the persistent occurrence of fatal and costly accidents in daily life, the necessity for efficient ADRSs cannot be overstated. This study presents a novel approach to augment existing ADRSs by integrating advanced technologies and optimizing communication channels. By incorporating state-of-the-art embedded systems and leveraging cloud technology, the proposed system aims to expedite recovery efforts and enhance overall effectiveness. The integration of cutting-edge embedded systems enhances the capability of the ADRS to swiftly detect and report accidents. These systems can utilize various sensors such as accelerometers, gyroscopes, and GPS modules to accurately identify incidents. Once an accident is detected, the system triggers an automated response mechanism to alert emergency services and relevant authorities. This rapid notification facilitates quicker response times, thereby reducing the severity of injuries and minimizing property damage. Furthermore, by harnessing cloud technology, the proposed ADRS can store and process vast amounts of data collected from accident scenes in real-time. This enables comprehensive analysis of the situation, aiding emergency responders in making informed decisions and deploying appropriate resources effectively. Moreover, cloud-based storage ensures that critical information is accessible remotely, allowing for seamless coordination between different stakeholders involved in the rescue operation. One of the key features of the system is its seamless integration with medical evacuation services. Upon detecting an accident, the ADRS automatically initiates a request for medical assistance, providing precise location data and relevant information about the nature of the incident. This ensures that injured individuals receive prompt medical attention, potentially saving lives in critical situations. By integrating advanced technologies and optimizing communication channels, the proposed ADRS aims to significantly improve response times, mitigate the impact of accidents, and ultimately save lives.