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MedConnect: An AI-Based Health Companion with Medical Report Simplification and 3D Anatomy Visualization

The increasing demand for accessible and continuous healthcare has motivated the development of intelligent digital health platforms. This paper presents MedConnect, an AI-powered health companion that integrates real-time vitals monitoring using IoT devices, simplification of complex medical reports using large language models, interactive 3D anatomy visualization, and an automated emergency response system. Users can upload medical reports in PDF, image, or text format. The system employs Optical Character Recognition (OCR) with Tesseract, Medical Named Entity Recognition using SpaCy and Med7, and a locally hosted LLaMA-3 8B model via Ollama to generate easy-to-understand plain-language summaries. Identified conditions are highlighted on an interactive 3D human anatomy model built with Three.js and React-Three-Fiber. The platform further supports voice input and output in English, Telugu, and Hindi, real-time emotion detection through webcam, and a reliable SOS mechanism that auto-dials 108 while alerting registered caretakers. Evaluation on a custom dataset of 150 de-identified medical reports yielded a SARI score of 47.6, BERTScore of 73.2, anatomy-mapping accuracy of 91.4%, and emergency response reliability between 96–100%. MedConnect offers a low-cost, privacy-preserving, and scalable solution suitable for preventive healthcare in resource-constrained settings such as India.

Published by: Dr. Kanigiri Suresh, Vanguri Shiva Ram, S. Ruchitha, Manchalla VLN Sri Ganesh, Shaviv Ebenezer Medhari

Author: Dr. Kanigiri Suresh

Paper ID: V12I4-1177

Paper Status: published

Published: August 18, 2026

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Research Paper

Smart Solar EV Charging Station Using IoT

Due to the growing use of electric vehicles, there is a rise in the demand for intelligent charging systems. Conventional wired charging systems rely on physical connection through wires, which results in wear and tear of cables, electricity risks, and inconvenience to the user. In this paper, we will be designing IoT-based smart wireless EV charging with an auto detection and battery monitoring system, which will help us charge the EVs in a smart and automatic manner without any physical connection with the charger, along with the battery monitoring of the vehicle. Our proposed system includes a wireless power transfer arrangement having a transmitter and receiver coil in order to transfer energy without any physical link. The charging will start automatically through the IR sensor when the vehicle is detected in the charging region and will be stopped once the vehicle is taken away from the charging zone. Charging station and vehicle will communicate with each other wirelessly through two ESP32 modules. Charging parameters will be continuously monitored with the help of the current sensor INA219, which will measure the voltage, current, and power consumption of the battery, and their values will be displayed on a 16x2 LCD screen. All the collected data will be sent wirelessly to an IoT-based mobile application for remote monitoring of battery percentage and charging states of the system.

Published by: Banothu Varun, Addetla Nithin, Ch. Rishika Sagar, D. Karthik Yadav

Author: Banothu Varun

Paper ID: V12I4-1188

Paper Status: published

Published: August 18, 2026

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Thesis

A Study to Assess the Effectiveness of a Structural Teaching Programme on Knowledge Regarding First Aid and Safety Measures Among School Children at Selected Schools of District Mandi HP

Promoting health, wellness, and disease prevention is increasingly vital in today's changing society. This study aimed to enhance the knowledge of school children regarding first aid and safety measures through a structured teaching programme to prepare them for future emergencies. A quasi-experimental research design was utilized, involving a sample of 100 school children selected via convenient sampling from schools in District Mandi, Himachal Pradesh. Data analysis was conducted using descriptive and inferential statistics. The pre-test mean knowledge scores were comparable between the control (9.68) and experimental (9.9) groups. Following the intervention, the control group’s post-test mean score remained statistically stagnant at 9.46, whereas the experimental group’s mean score significantly increased to 25.5. This massive improvement in the experimental group was statistically significant (t-value = 33.92, surpassing the critical table value of 2.021 at p < 0.05). Additionally, post-test knowledge in the experimental group showed significant associations with age, school type, maternal education, and paternal occupation. The structured teaching programme had a highly significant positive impact on improving first aid and safety knowledge among school children.

Published by: Shephali Walia, Yamini sharma, Pallavi mehra, Priyanka sharma

Author: Shephali Walia

Paper ID: V12I4-1185

Paper Status: published

Published: August 9, 2026

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Research Paper

Socio-economic Determinants of Livelihood Security among Street Vendors: Evidence from Paramathi Velur Taluk

Street vending constitutes a significant segment of the informal economy in India by generating employment opportunities and ensuring access to affordable goods and services for urban and semi-urban populations. Despite their substantial contribution to local economies, street vendors continue to experience livelihood insecurity arising from limited institutional support, inadequate infrastructure, restricted access to formal credit, and weak social protection mechanisms. This study examines the socio-economic determinants of livelihood security among street vendors in Paramathi Velur Taluk of Namakkal District, Tamil Nadu. The study is based on primary data collected from 355 street vendors using a structured questionnaire covering demographic characteristics, business profile, income, expenditure, access to financial services, registration status, and workplace conditions. The findings indicate that women constitute the majority of vendors, reflecting the growing participation of female workers in the informal economy. Most respondents belong to economically productive age groups but possess relatively low levels of formal education. A substantial proportion operate without official registration or vendor identity cards, limiting their access to government welfare schemes and institutional credit. Vegetable vending represents the dominant economic activity, while inadequate infrastructure, market uncertainty, and regulatory constraints continue to affect livelihood outcomes. The study concludes that livelihood security is shaped by a combination of socio-economic characteristics, business conditions, and institutional support. Strengthening vendor registration, expanding financial inclusion, improving market infrastructure, and enhancing awareness of welfare schemes would contribute significantly to sustainable livelihoods among street vendors.

Published by: Saravanan R., S. Parvathi

Author: Saravanan R.

Paper ID: V12I4-1179

Paper Status: published

Published: August 9, 2026

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Research Paper

Examination Integrity in India: Analysing the Role of Political Influence, Governance Deficits, and Institutional Weaknesses in Examination Paper Leaks

India has one of the world's oldest and largest education systems, where competitive examinations and board assessments play a crucial role in determining academic and career opportunities. However, examination paper leaks, cheating, and the re-conduct of exams undermine the credibility of the education system, affecting deserving aspirants' time, effort, and morale. This study examines how political influence, governance deficits, corruption, and institutional weaknesses contribute to breaches of examination integrity. METHODOLOGY: This study adopts a descriptive and analytical research design based on both primary and secondary sources of data. Primary data were collected through a structured questionnaire administered through Google Forms, with responses from 80 participants. Approximately 62% of respondents were school students, 17–18% were college students from institutions across Delhi NCR, while the remaining participants comprised working professionals from various sectors. Secondary data were collected from government reports, official documents, news articles, policy papers, and published research studies to provide contextual understanding and validate primary findings. RESULT: The findings reveal that most respondents consider examination paper leaks a serious threat to fairness and merit. They identified political influence, corruption, and weak governance as key factors contributing to these incidents. Secondary data further indicate that paper leaks affect millions of candidates, increase public expenditure due to re-conducted examinations, and weaken public trust in the examination system. CONCLUSION: The study concludes that examination paper leaks are not only educational failures but also governance challenges arising from corruption, weak accountability, and institutional shortcomings. Strengthening examination security, transparency, and institutional accountability is essential to safeguard meritocracy, restore public confidence, and protect the integrity of India's education system.

Published by: Divit Batra, Aadit Batra, Amit Gurjar

Author: Divit Batra

Paper ID: V12I4-1176

Paper Status: published

Published: August 2, 2026

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Research Paper

Automated Video Generation using Deep Learning

The increasing utilization of multimedia content in education, marketing, and digital communication has created a growing demand for efficient video generation systems. This paper presents an Automated Video Generator that converts textual input into narrated videos using a modular deep learning-based pipeline. The proposed system generates a narrative, retrieves context-relevant images, synthesizes speech using text-to-speech technology, and composes synchronized videos through a web-based Django framework. Experimental results demonstrate improved efficiency, stable performance, and audio-visual synchronization, making the system suitable for educators, marketers, and content creators while reducing manual effort and production time. ``` Batch11 Automated Video Generator Using Deep Learning.pdf

Published by: V. Shiva Kumar, K. Eshwar, M. Raja Laxmi, V. Kavya Sri

Author: V. Shiva Kumar

Paper ID: V12I4-1173

Paper Status: published

Published: August 2, 2026

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