Category Archives: Uncategorized

Authors: S. Surendar Raj, K. Sai varsha

Abstract: Chat applications have emerged as indispensable tools on smartphones, offering users the ability to exchange text messages, images, and files at no cost. However, ensuring the security of these communications is paramount. This paper proposes a secure chat application that implements End-to-End encryption, safeguarding private information exchanged between users and providing robust data protection. The application also addresses storage security concerns. By outlining a set of requirements for a secure chat application, this paper informs the design process. The proposed application is evaluated against these requirements and compared with existing popular alternatives to assess its security features. Furthermore, the application under goes rigorous.

Published by: vikaspatanker

Authors: Krishna Wable, Bhumika Raut, Radhika Ware, Achal Patil, Prof.Vrushali Channe

Abstract: Maintaining a healthy lifestyle often becomes diffi- cult due to generic advice and delayed health insights. Health- Sync: SmartCare Companion is an AI-driven system designed to offer personalized, adaptive, and culturally relevant healthcare support. It integrates BioMistral-7B for medical text understand- ing and ResNet for food and symptom image recognition. Using fuzzy logic with TOPSIS/AHP, the system estimates personalized daily nutrient and calorie needs, supported by an ontology-based food graph linking Indian dishes, nutrients, and diseases. With time-series tracking and reinforcement learning, HealthSync continuously refines recommendations based on user progress. Trained on Indian food and lifestyle datasets, it delivers accurate, real-time, and inclusive wellness guidance—transforming preven- tive healthcare into a smarter, more user-focused experience.

Published by: vikaspatanker

Authors: Vasudev Sharma

Abstract: The proliferation of enterprise data across multi-cloud infrastructures has intensified the complexity of managing data integrity, regulatory compliance, and interoperability in distributed ecosystems. This study introduces a cognitive data governance pipeline designed to autonomously orchestrate, monitor, and optimize governance functions across heterogeneous enterprise platforms such as SAP HANA, Oracle Autonomous Database, and cloud-native storage systems. Unlike conventional rule-based frameworks, the proposed model leverages deep learning, semantic reasoning, and federated policy orchestration to build adaptive feedback loops that detect inconsistencies, predict compliance deviations, and self-correct data governance pathways in real time. The architecture integrates an explainable intelligence layer that interprets anomaly behaviors, traces root causes, and supports transparent auditability without human intervention. Through simulated deployments in hybrid cloud environments, the framework demonstrates measurable improvements in compliance latency, metadata synchronization, and decision throughput, achieving over 35 percent higher efficiency in governance verification and 25 percent reduction in manual remediation efforts. The cognitive design transforms governance from a static, policy-driven function into a dynamic, self-learning system capable of aligning continuously with regulatory and operational shifts. The findings advance the notion of autonomous governance intelligence as a foundational component of modern multi-cloud data ecosystems, offering enterprises a sustainable pathway toward resilient, compliant, and self-regulating digital operations.

DOI: https://doi.org/10.5281/zenodo.17637615

Published by: vikaspatanker

Authors: Arpita Sahu, Dr. Waris Patel

Abstract: The rapid digital transformation in the food and beverage industry has created a demand for efficient, customizable, and user-friendly ordering solutions. Tra- ditional restaurant operations often face challenges such as order inaccuracies, long wait times, dependency on labor, and inefficient payment systems. To ad- dress these issues, we propose Swift Kiosk, a digital kiosk application designed specifically for caf´es and restaurants. Built using the MEARN stack (MongoDB, Express.js, Angular, React, and Node.js), Swift Kiosk enhances the food ordering experience by allowing customers to customize their meals, process cashless trans- actions, and reduce dependency on manual labor. This innovation streamlines restaurant operations while delivering a seamless and engaging customer experi- ence. One of the core functionalities of Swift Kiosk is food customization, allowing users to personalize their meals and beverages with ease. Customers can select portion sizes, ingredients, dietary preferences (vegan, gluten-free, keto, etc.), and cooking methods, ensuring a tailor-made dining experience. The application pro- vides a real-time preview of the customized meal, ensuring accuracy before order placement. Swift Kiosk leverages MongoDB as the database to efficiently store and manage user preferences, order details, and restaurant menu configurations. With Node.js and Express.js powering the backend, the system ensures fast and scalable pro- cessing of customer orders, reducing wait times and improving order accuracy. To enhance user interaction, the application is designed using React.js for the frontend, offering a responsive and visually appealing interface. For businesses, an Angular-based admin panel allows restaurant owners to manage menus, track sales, and analyze customer behavior in real time. This combination of technolo- gies ensures a smooth and dynamic user experience. Swift Kiosk automates the order-taking process, reducing the reliance on hu- man staff and increasing efficiency. Customers can place their orders directly through the kiosk interface, which sends requests instantly to the restaurant’s kitchen system. The application supports multiple payment options, including UPI, digital wallets, credit/debit cards, and QR-based transactions, ensuring se- cure and hassle-free payments. By integrating Express.js and MongoDB, transaction data is stored securely, and real-time payment confirmations ensure a frictionless checkout process. This automated system eliminates long queues, minimizes order miscommunication, and enhances customer satisfaction. By digitizing order placement and payment, Swift Kiosk reduces labor depen- dency, allowing restaurant staff to focus more on food preparation and service rather than manual order management. The application also provides data ana- lytics using MongoDB’s aggregation framework, helping restaurant owners analyze customer preferences, order trends, and peak business hours. These insights assist in optimizing menu offerings, pricing strategies, and targeted promotions, enhanc- ing overall profitability. Swift Kiosk, powered by the MEARN stack, presents a modern, scalable, and efficient solution for caf´es and restaurants. By allowing customers to customize their food, automating the ordering and payment process, and reducing opera- tional inefficiencies, Swift Kiosk transforms traditional restaurant operations into a tech-driven, customer-centric model. As the food service industry continues to embrace digital transformation, Swift Kiosk stands as a pioneering step towards enhancing efficiency, reducing operational costs, and improving the overall dining experience.

DOI: http://doi.org/10.5281/zenodo.17637230

Published by: vikaspatanker

Authors: Anish Mukhiya, Raushan Kumar Ram, Anuraj Chaudhary, Omkar Mahto

Abstract: Background: Personal Desktop Voice Assistants (PDVAs) represent a significant advancement in human-computer interaction, offering intuitive voice-based control of desktop environments. Meth- ods: This study employed Python programming language with integrated speech recognition, natural language processing, and text-to-speech technologies to develop an accessible PDVA. The system archi- tecture incorporates wake word detection, intent recognition, and task execution modules. Results: The developed PDVA successfully executes diverse commands including web searching, media control, system management, and information retrieval. The system demonstrates particular effectiveness for visually impaired users, providing multimodal feedback through synthesized speech and on-screen text. Conclu- sion: The research confirms that Python-based PDVAs can significantly enhance desktop accessibility while highlighting the importance of addressing privacy concerns and interaction limitations in future developments.

Published by: vikaspatanker

Authors: Isha V Solanki, Preet Darji, Jainil Parmar, Manush Desai, Prof. Garima Sharma

Abstract: The paper addresses an in-depth review of over 60 peer-reviewed studies that deal with canine health and welfare and their proponents and cons on both conventional and emerging strategies. The review encompasses topics of behavioral assessment, vaccination, dental hygiene, population management, diagnosis of allergies and the introduction of artificial intelligence into veterinary medicine, aligning clinical science and technology and ethics. It is worth noting that it determines the vital areas of investigation of behavioral and dental diagnostics, issues of population affected by stray populations, and lack of standardiza- tion in the implementation of preventive care despite its evident usefulness. In contrast to the previous reviews, the given study is rather multi-dimensional, as it links welfare and innovation to each other. The paper can be reproducible because it adheres to PRISMA standards on the selection of studies. Conclusions will target both the veterinarians, the pet owners, researchers, and policymakers by promoting evidence-based models of care. In the perspective, the paper highlights the necessity of standard behaviors and tools, available AI-aided diagnosing, and more significant public education so as to drive international levels of canine well-being.

DOI: https://doi.org/10.5281/zenodo.17636958

Published by: vikaspatanker

Authors: Logeshwaran V, Bhuvaneswari B

Abstract: In recent years, the exponential growth of dataintensive applications and cloud-based services has drastically increased energy consumption in data centers worldwide. This surge poses significant challenges, including high operational costs, carbon emissions, and sustainability concerns. To address these issues, this paper proposes a comprehensive AI-based framework for energyefficient data center optimization. The approach integrates intelligent control algorithms, predictive analytics, and adaptive resource allocation mechanisms that dynamically manage workloads, cooling systems, and server utilization. Using techniques such as machine learning (ML), reinforcement learning (RL), and neural network-based control, the proposed model achieves significant energy savings while maintaining service-level agreements (SLAs). The research demonstrates how AI- driven systems can autonomously predict server loads, optimize cooling parameters, and minimize idle energy consumption. The findings contribute to the design of sustainable, selfoptimizing data centers for the next generation of green computing infrastructure.

Published by: vikaspatanker

Authors: G Vishal, G K Sharath Kumar, Karthik N Ganiga,, Sanjay Kumar, Prof. Merlin B

Abstract: An important factor in a nation's economic development is the agricultural sector. In particular, it provides millions of people in rural India with a vital source of income. One of the major issues influencing the agriculture industry is plant disease. Diseases can infect plants for a variety of reasons, such as synthetic fertilizers, outdated methods, environmental factors, etc., which affect farm productivity and thereby hurt the economy. Researchers have looked into a variety of AI and machine learning-based applications to identify plant diseases in order to address this problem.

 

Published by: vikaspatanker

Authors: Akshat Parekh, Jemit Patel, Deep Upadhyay, Jay Shah

Abstract: The increasing number of abandoned animals underlines the necessity of reliable and transparent adoption systems. Existing adoption practices often rely on scattered sources such as social media, which lack consistency, verification, and accountability. This paper presents Adoptly, a mobile-first application designed to streamline pet adoption by ensur- ing secure authentication, verified listings, and seamless communication between adopters and shelters. Built using React Native (Expo) for cross- platform compatibility, Clerk for user authentication, and Firebase for real-time storage and database services, Adoptly integrates features such as verified pet profiles, favorites, adoption requests, story sharing, and an in-app chat system. Developed under an agile methodology, the system reduces misinformation, enhances trust, and improves adoption efficiency compared to unstructured methods. Early testing demonstrates reliabil- ity in authentication, smooth navigation, and real-time synchronization. The findings highlight the potential of mobile-first systems to revolu- tionize adoption processes by bridging gaps of communication, trust, and scalability.

Published by: vikaspatanker

Authors: Aaditya Deo, Shah Saurabh, Anurag Tiwari, Ishordev Chaudhary, Dr. Sneha Soni

Abstract: Traditional digital marketing frequently encounter high costs, authenticity gaps, and declining consumer trust. Simultaneously regular customers and small creators who organically promote products seldom receive benefits. This paper present a concise research version of the project “Social Media Monetization: A Modern Advertising System” which enable customers to earn cashback by promoting purchased product from partnered brands on Instagram. The system leverage user generated con- tent to provide brands with authentic, cost effective promotion while offering customers a transparent reward mechanism. We summarize the problem context, objectives, system methodology, modules, expected outcomes, and future directions strictly based on the original project report, and reserve space for illustrative figures aligning with the submitted work. Customer Based Advertising, Cashback Reward, Digital Marketing, Social Media Promotion, Instagram Marketing, Authenticity, Secure Payment Integration, Marketing Ana- lytics, User Engagement Tracking, AI Based Advertisement Optimization, Scalable Marketing Model.

Published by: vikaspatanker