Authors: Mr. Mayank Arora, Nupur

Abstract: The rapid expansion of digital technologies has transformed the landscape of contemporary journalism, bringing data-driven reporting to the forefront of news production. In India, the rise of data journalism—an approach that integrates statistical analysis, visualization tools, and storytelling—has opened new possibilities for accuracy, depth, and transparency in media reporting. Yet, the adoption of data journalism remains uneven, complicated by structural issues within Indian newsrooms, limited technological expertise, and the pressures of fast-paced news cycles. This paper investigates how Indian news organizations understand, adopt, and implement data journalism practices. It explores the professional, infrastructural, and ethical challenges that constrain data-driven reporting, while also identifying opportunities created by digital literacy, open-data movements, and audience demand for evidence-based journalism. Through a review of scholarly literature, industry reports, and comparative perspectives, the study highlights how data journalism in India stands at a critical intersection of innovation and limitation. The paper argues that although data journalism has the potential to strengthen public discourse and democratic accountability, its growth depends on sustained investment in training, technological resources, and editorial vision. Ultimately, the study positions data journalism as an evolving journalistic paradigm that can contribute significantly to India’s media ecosystem if supported by a culture of transparency, collaboration, and professional development.

Published by: vikaspatanker

Authors: Sameer Agarwal, Vaibhav Kalukar

Abstract: Human–Robot Interaction (HRI) is an interdisciplinary field that examines how humans communicate, collaborate, and coexist with robotic systems. With major advancements in artificial intelligence, sensor technologies, and automation, robots are increasingly becoming interactive partners in healthcare, manufacturing, education, and personal assistance. This research investigates current trends in HRI, emphasizing the shift from traditional command-based systems to socially aware, adaptive, and collaborative robots. A qualitative review methodology is used to analyze studies published between 2015 and 2024, focusing on social robots, industrial cobots, healthcare and assistive robotics, and service-oriented systems. Findings reveal rapid growth in socially interactive robots, widespread adoption of collaborative robots in industry, and enhanced communication through AI-driven speech, gesture, and emotion recognition. Despite challenges such as limited emotional intelligence, ethical concerns, and high costs, the increasing integration of robots into human environments highlights significant potential for future development. The study concludes that HRI will play a crucial role in shaping intelligent, human-centric robotic systems, requiring continued research in transparency, trust, and ethical design.

DOI: https://doi.org/10.5281/zenodo.17670137

Published by: vikaspatanker

Authors: Mr. Karthiban R, Tharun S, Naveen B, Yuvaraj S, Pragathiswaran G

Abstract: Urban site visitors congestion has come to be one of the most critical challenges confronted via cutting-edge towns. Emergency automobiles, wi-fi ambulances, enjoy frequent delays due to traffic wireless indicators and roadblocks, which may be deadly in lifestyles-threatening conditions. This paper proposes a smart visitors control device that mixes automatic wide variety Plate recognition (ANPR) and ambulance signal detection to make sure actual-time prioritization of ambulances. The proposed system makes use of digicam-primarily based vehicle identity, an IoT-enabled site visitors manage network, and adaptive sign timing to create a “inexperienced corridor” for emergency automobiles. Experimental simulations imply that the device can reduce ambulance waiting time at intersections via extra than 60%, improving the wi-fi of emergency reaction services. the combination of ANPR era permits automatic detection of ambulances without counting on guide systems or wireless tags, making it scalable and price-effective for clever city deployment.

Published by: vikaspatanker

Authors: Dhyanesh M, Dharshini S, Deepak P, Aisha Amna A, Mr. S. Dhinakaran

Abstract: EduHelm is an intelligent AI-driven career and learning platform designed to personalize and optimize student growth through dynamic learning paths, adaptive projects, and real-time skill tracking. The system leverages machine learning and large language models to recommend personalized roadmaps, micro-projects, and certification-based goals aligned with each user’s academic profile and aspirations. EduHelm integrates AI mentorship, progress analytics, and gamified challenges to foster continuous improvement and engagement. It also enables students to upload learning journals and research patterns, automatically analyzing them for feedback and improvement suggestions. Developed using a React frontend, Flask backend, and PostgreSQL database, with AI modules powered by OpenAI and Hugging Face, EduHelm delivers a seamless and intelligent experience that empowers learners to take control of their career growth in the digital age.

Published by: vikaspatanker

Authors: Professor Kavita Singh

Abstract: The electronic monitoring of biomedical devices has revolutionized healthcare delivery by enabling real-time diagnostics, continuous physiological tracking, and rapid response mechanisms. This study reviews the technological advances underpinning electronic biomedical monitoring systems, describes key classes of devices, and discusses engineering challenges and prospects for future developments

Published by: vikaspatanker

Authors: M. Venkataravanappa, K.N. Venkatachalaiah

Abstract: Combustion synthesis method was used to prepare Europium doped Barium silicate nanophosphors. The crystalline structure from PXRD profiles showed that the fabricated sample have orthorhombic phase [JCPDS Card No. 78-1371] with a face group Pb nm- 62, with no variation in the diffraction profiles because of the inclusion of the Eu2+ions. The images are regular and irregular shapes with smooth surface were observed from SEM. The photometric spectra were studied for optimized nanophosphor displays green emission at ~ 505 nm due to the presence of Eu2+ ions corresponds to 5D07F2 transition. The CIE arrangement was green spread, which are basically near to the standard characteristics and Correlated Color Temperature (CCT) was acquired 12236K. These outcomes showed that the fabricated NPs can be viably utilized as green color part in the fabrication of white light emitting diodes.

DOI: https://doi.org/10.5281/zenodo.17660524

Published by: vikaspatanker

Authors: Sagar Gupta, Vikas kumar

Abstract: Hospitals often face immense challenges related to resource utilization and managing these resources efficiently in light of increasing demands from patients and the volume of data. The use of traditional centralized healthcare computing systems introduces latency and inefficiencies related to real-time decision-making. This chapter reviews how Edge AI can transform hospital resource utilization. By processing data closer to its source using edge devices, Edge AI allows for real-time analytics, proactive resource allocation, and responsiveness of operations. This chapter details the current challenges in hospital resource management, the architecture of an Edge AI-driven resource management system, and also discusses the case studies for their implementation. Quantitative evaluation regarding improved performances such as reduced wait time for patients and improvement in the bed occupancy rate is discussed. Integration of Edge AI with IoT and other emerging technologies such as 5G and federated learning is also considered as future work. Our analysis further shows that Edge AI increases not only hospital efficiency but also better patient outcomes through intelligent and timely interventions.

Published by: vikaspatanker

Authors: Kashish Aggarwal, Mr.Vikas kumar

Abstract: One of the most powerful and ethically debatable technologies of the 21 st century are Facial Recognition Tech- nology (FRT), which is also driven by Artificial Intelligence (AI). FRT can be used to automate the identification and verification of individual persons under different conditions, such as law enforcement, border control, and digital authentication, by relying on machine learning and deep neural networks. Even though the technology has a positive impact on reducing safety and efficiency, it poses significant ethical issues concerning privacy, data protection, bias, consent, and responsibility. The paper is a thorough overview of the ethical aspects of AI-driven facial recognition, the benefits that it has, and the vulnerabilities of this technology. It studies the problem of algorithmic bias, data governance, and ethical dimensions of surveillance-based applications. Global regulatory reactions to the subject, including the European Union General Data Protection Regulation (GDPR), the suggested AI Act, and other upcoming data protection regulations in the United States and India are discussed to point out differences in regulation. In addition, the paper explains mitigation measures such as fairness-conscious algorithms, transparency, and privacy- sensitive methods to encourage the responsible use of AI. This research highlights the importance of balancing between innova- tion and accountability as a means of seeking to fulfill societal needs without infringing on human rights by critically analyzing and conducting case-based reviews that conclude that facial recognition can be used to the benefit of society without taking away the rights of the people.

Published by: vikaspatanker

Authors: Reeva Rawat, Ronit Roy, Vivek Sharma, Soham Andhyal, Dr. Ravi Rai Chaudhari

Abstract: The UNI Verse platform is designed to create a more intelligent, engaged campus and digital learning environment. It provides a single platform for all organizational, informational, and engagement needs of students and faculty to facilitate their learning and academic experience. It gives students a centralized location to learn about their academic engagement, course schedule, office hours of professors, assignment due dates, and upcoming campus activities. UNI Verse will even offer reminders, to help keep students informed about deadlines & updates on campus. In addition to the academic purpose, UNI Verse allows students and faculty to have more substantive communications with the real-time direct messaging and meeting scheduling options. It even provides tools to navigate campus or even journal or share notes digitally, all to foster collaboration with classmates and engage as a learning community outside and inside of the classroom. Ultimately, UNI verse is a hub and usable system for productive, engaged, interactive, and organized campus life.

DOI: https://doi.org/10.5281/zenodo.17657734

Published by: vikaspatanker

Authors: Saransh Khanna, Mr. Ritesh Kumar Chandel

Abstract: This research investigates the development of an intelligent expense tracking system powered by Retrieval-Augmented Generation (RAG). Traditional expense tracking tools rely on structured inputs and static categorizations, creating friction for users who log expenses in natural language. The proposed system uses a hybrid architecture of vector retrieval and generative reasoning to extract accurate financial insights from unstructured text, improving reliability while reducing hallucinations commonly seen in standalone LLMs.

Published by: vikaspatanker