Authors: Assistant Professor H. M. Pawar, Pravin Chavan, Kumar Borole, Rahul Vispute, Sona Bhalerao

Abstract: The rapid adoption of electric vehicles (EVs) has created a growing demand for efficient, sustainable, and convenient charging infrastructure. This paper proposes an IoT-based solar-powered wireless power transfer (WPT) system integrated into roadways for dynamic charging of electric vehicles. The system utilizes photovoltaic panels installed alongside or beneath road surfaces to harness solar energy, which is stored and managed using intelligent energy storage systems. Wireless power transfer is achieved through inductive coupling between transmitter coils embedded in the road and receiver coils mounted on EVs, enabling real-time charging while the vehicle is in motion. The integration of Internet of Things (IoT) technology allows for continuous monitoring, control, and optimization of energy distribution, traffic conditions, and system performance. Sensors and communication modules collect real-time data, which is processed to ensure efficient power delivery and load balancing. This approach minimizes range anxiety, reduces dependency on stationary charging stations, and enhances energy efficiency by utilizing renewable energy sources. The proposed system presents a scalable, eco-friendly, and smart solution for future transportation infrastructure, contributing to reduced carbon emissions and sustainable urban mobility.

DOI: http://doi.org/10.5281/zenodo.379

Published by: vikaspatanker

Authors: Aditya Phad, Shubajit Avachite, Sujal Jadhav, Rugved Gunvante

Abstract: An online auction system developed using Python provides a digital platform where users can buy and sell items through competitive bidding. The project utilizes Python for backend logic, ensuring efficient handling of user data, bids, and auction processes. It typically includes features like user registration, login authentication, and item listing. Sellers can upload product details, while buyers can place bids in real time. The system manages bid validation to ensure only higher bids are accepted. A timer mechanism is implemented to automatically close auctions after a specified duration. The highest bidder at the end of the auction is declared the winner. Data is often stored using databases such as SQLite or MySQL for persistence. The project emphasizes security, fairness, and user-friendly interaction. Overall, it demonstrates practical a pplication of Python in building scalable web-based systems.

DOI: https://doi.org/10.5281/zenodo.19589768

Published by: vikaspatanker

Authors: Shardul Prakash Jangam

Abstract: Achieving self-reliance (Atmanirbhar) in India’s electric vehicle (EV) sector mandates a strategic shift from reliance on imported lithium-ion (Li-ion) technology toward alternative chemistries utilizing domestically abundant raw materials. The Sodium-ion Battery (SIB) is identified as the leading alternative technology capable of ensuring immediate raw material independence by leveraging domestic reserves of sodium, iron, and manganese. SIBs are ideally suited for the cost-sensitive, short-range segments of India's market, specifically electric two-wheeler (e-2W) and three-wheeler (e-3W) segments.1 While Li-ion currently holds a cost advantage, scaled SIB production is projected to achieve cost leadership, potentially reaching $40-$50 per kilowatt-hour (kWh) at the pack level by the end of the decade.4 SIBs also offer superior safety and temperature tolerance, critical for mass EV adoption and Battery Energy Storage Systems (BESS).2 The primary recommendation is the rapid utilization of the 5 GWh capacity earmarked under the Production-Linked Incentive (PLI) Niche ACC scheme to commercialize SIBs, focusing especially on establishing a completely indigenous supply chain for the hard carbon anode using domestic biomass.7 Successful localization is projected to capture nearly 80% of the estimated $300 billion domestic EV battery market by 2030, generating substantial employment and revenue.

DOI: https://doi.org/10.5281/zenodo.19589549

Published by: vikaspatanker

Authors: Prem kumar, Aryaman Arora, Dr. A Kannagi

Abstract: The constant hum of social media has become the defining factor in the way young people and young adults sleep, or, more appropriately, the way they don’t sleep. Throughout the literature, the common factor is the way in which excessive usage of social networks, online communities, and the sheer volume of electronic communications impacts the sleep cycle in this age group. The need to remain connected at all hours has become the defining factor in sleep issues for both young people and young adults. Both biology and psychology are commonly cited as the two major factors behind sleep issues in this age group. For example, the biology of the blue light emanating from their smartphones is commonly cited as a factor in sleep issues. But more than anything, the need to remain connected has become the defining factor in sleep issues in this age group. The main aim of this paper is to examine the role of social media in the way young people and young adults sleep. The secondary aim is to identify the major factor behind the sleep issues in this age group. This will be done by using a secondary research approach to identify the major factor behind the sleep issues in this age group.

Published by: vikaspatanker

Authors: Mahe Bader Fatmi

Abstract: Industrial Training Institutes (ITIs) play a crucial role in developing a skilled workforce in India, yet many graduates face challenges in securing sustainable employment due to gaps between training and industry requirements. This paper explores how strategic management practices can enhance the employability of ITI-qualified students by aligning institutional objectives with dynamic labor market needs. It examines key strategies such as industry–institute partnerships, curriculum modernization, competency-based training, soft skills development, and the integration of digital technologies in vocational education. Drawing on selected Indian case studies, the study highlights successful models where collaboration with industry stakeholders, apprenticeship programs, and outcome-oriented training frameworks have significantly improved job placement rates. Institutions that adopted proactive management approaches—such as continuous skill mapping, faculty upskilling, and data-driven decision-making—demonstrated stronger employment outcomes for their students. The paper argues that adopting a strategic management perspective enables ITIs to transition from traditional training centers to agile, demand-driven skill hubs. It concludes by recommending policy-level support, strengthened public-private partnerships, and the institutionalization of monitoring and evaluation mechanisms to ensure long-term impact. These findings provide actionable insights for educators, policymakers, and administrators aiming to bridge the employability gap in India’s vocational education sector.

DOI: https://doi.org/10.5281/zenodo.19570413

Published by: vikaspatanker

Authors: Vivek Sharma

Abstract: The financialization of private markets represents a fundamental transformation in the architecture of global financial systems, characterized by the growing dominance of non- bank financial institutions and the expansion of market-based credit intermediation. Over the past two decades, private markets—including private equity, private credit, hedge funds, and venture capital—have evolved from niche investment segments into systemically important components of global finance. This transformation has been significantly accelerated by post-2008 regulatory reforms, particularly Basel III, which imposed stricter capital and liquidity requirements on traditional banking institutions. While these reforms enhanced banking sector resilience, they also constrained credit supply, thereby creating space for private markets to expand and assume a central role in financial intermediation. This study investigates the systemic risk implications of the financialization of private markets, with a particular focus on the role of private credit and leveraged investment strategies. The research adopts a mixed-method approach that integrates theoretical insights from financial instability theory with empirical analysis based on secondary data. Key data sources include the International Monetary Fund (IMF), Financial Stability Board (FSB), World Bank, and industry reports from Preqin and BlackRock. The empirical framework is built around a regression model that examines the relationship between systemic risk and its primary determinants, including leverage, default rates, and market volatility. The results reveal that leverage is the most significant driver of systemic risk within private markets. High leverage amplifies both returns and losses, increasing vulnerability to adverse economic shocks and contributing to financial instability. Default rates are also found to have a strong positive relationship with systemic risk, reflecting the deterioration of borrower credit quality during periods of economic stress. Market volatility further exacerbates risk by increasing uncertainty and triggering liquidity constraints, particularly in markets characterized by illiquid assets. The study also highlights the structural vulnerabilities associated with private markets, including opacity, liquidity mismatches, and interconnectedness with the broader financial system. Unlike traditional banks, private market institutions operate with limited regulatory oversight and disclosure requirements, making it difficult to assess risk exposure and monitor systemic threats. The increasing interconnectedness between private funds, banks, and institutional investors further amplifies the potential for contagion. Overall, the findings suggest that while private markets enhance financial efficiency and provide alternative sources of capital, they also pose significant systemic risks that extend beyond the traditional banking sector. The paper concludes by emphasizing the need for expanded macroprudential regulation, improved transparency, and enhanced data reporting frameworks to ensure financial stability in an increasingly financialized global economy.

DOI: https://doi.org/10.5281/zenodo.19570015

Published by: vikaspatanker

Authors: Satyam Sharma, Jakkala Sanjay Kumar, S.Harshvardhan, Ms. Pabbu Parameshwari

Abstract: Rapid growth in residential electricity consumption has created a strong need for intelligent and user-friendly monitoring solutions that can help users understand and control their energy usage. Traditional energy meters provide only cumulative readings and do not offer real-time insights into appliance-level consumption. This paper presents the design and implementation of an IoT-based Smart Power Monitoring System for home appliances that enables continuous monitoring and remote access to electrical parameters. The proposed system measures real-time voltage, current, power, and energy consumption using ZMPT101B voltage and ACS712 current sensors interfaced with an ESP32 microcontroller. The ESP32 processes sensor data and transmits it securely to cloud platforms such as ThingSpeak and Blynk via Wi-Fi, allowing users to visualize and analyze energy usage through mobile or web dashboards. In addition, the system incorporates a relay-based protection mechanism that automatically disconnects the load during abnormal conditions such as overcurrent, voltage fluctuations, or excessive power consumption. This feature helps prevent electrical damage and improves system safety. The proposed solution is low-cost, scal-able, and energy-efficient, making it suitable for residential envi-ronments as well as small industrial applications. By providing real-time monitoring, data analytics, and remote accessibility, the system promotes energy awareness, reduces electricity wastage, and supports the development of smarter and more sustainable energy management systems.

DOI: https://doi.org/10.5281/zenodo.19569819

Published by: vikaspatanker

Authors: Prof. Bhagwati Galande, Parth Bhosale, Sakshi Bathe, Aditi Gadhave, Prathamesh Amrutkar

Abstract: PulseSaver is designed to fix this. It’s an all-in-one digital network that acts as an emergency lifeline, instantly bringing together people who need help with people who can give it. We are building a single platform to manage donations of blood, organs, and money—all in real-time. We use smart AI technology to cut out the waiting. The system automatically and instantly matches the patient with the closest, most compatible, and fully verified donor or resource. Everything is secure and transparent: we rigorously verify all users and requests to build trust and ensure ethical donation practices. The main goal of PulseSaver is simple: to save lives by speeding up the emergency response and making sure critical resources get to the people who need them most, especially those in remote or underserved communities.

Published by: vikaspatanker

Authors: Nitesh Baranawal, Herambh Sakpal, Pranay Manoj, Kaustabh Kadam, Prof. Mohan Kumar

Abstract: The Steganography Hider System is a secure information-hiding solution designed to protect sensitive data by embedding it within digital images, making it imperceptible to unauthorized users. Unlike traditional encryption, which only disguises data, steganography conceals the very existence of the information, providing an additional layer of security. This system employs techniques such as Least Significant Bit (LSB) substitution, transform domain methods (e.g., DCT), or advanced neural network approaches to embed secret messages while maintaining the visual quality of the cover image. The proposed system allows users to securely hide and retrieve confidential information, ensuring data confidentiality, integrity, and robustness against common image processing operations such as compression, noise addition, and format conversion. This project serves as a practical demonstration of the importance of information security in today’s digital communication era, providing a user-friendly interface that can be applied in various fields such as secure communications, copyright protection, and digital forensics.

Published by: vikaspatanker

Authors: Pratiksha Shinde, Zishan Nadaf, Onkar Bhuse, Chaitanya Deshmukh

 

 

Abstract: Skin diseases constitute a major global healthcare challenge, particularly in regions with limited access to dermatological expertise. Early and accurate diagnosis is essential to reduce disease progression and associated healthcare costs. This research presents SkinSight, an advanced artificial intelligence–based clinical decision support system for automated skin disease detection using digital skin images. The proposed system is designed by aligning a real-world deployable application with state-of-the-art research methodologies reported in recent dermatology-focused deep learning literature. SkinSight integrates an advanced preprocessing pipeline for artifact removal and illumination normalization, a two-stage validation framework to ensure input reliability, and a dual-stream deep learning ensemble combining ResNet50 and InceptionV3 architectures. Additionally, the system incorporates explainable artificial intelligence (XAI) using Grad-CAM to provide visual interpretability of predictions. A comparative analysis between the initial deployment model and the research-grade pipeline is presented, followed by a structured roadmap for bridging implementation gaps. Experimental results demonstrate that aligning deployment architecture with research-level techniques significantly improves robustness, reliability, and clinical trustworthiness. The proposed framework highlights the importance of end- to-end consistency between research and deployment in AI-driven healthcare systems.

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Published by: vikaspatanker