Volume-11, Issue-6

November-December, 2025

Others

1. Locating the Role of Naga Women in the Naga Political Process since the Nineties

The 1990s were a significant period in Naga politics. The period witnessed the intensification of inter-factional violence between warring Naga insurgent groups. The signing of the ceasefire agreement between the Indian government and the Nationalist Socialist Council of Nagaland (Isak-Muivah) in 1997, and the subsequent peace talks that followed decades of violence, opened democratic space for Naga civil society to actively engage in the political process. Within this new dispensation, Naga women’s entry into the public sphere as ‘mothers’, rooted in private values and attributes such as nurturing, caring, and pacificatio, assumes significance. Naga women, traditionally confined to the private sphere, carved out a space for themselves in the public sphere by mobilizing for peace through a motherhood strategy. Based on primary and secondary sources, the paper examines the unique role that Naga women play in the public sphere, within the constraints of a traditional patriarchal ethos and Naga tribal customary practices that define gendered roles and perceptions for women. The paper concludes that the peace activism of Naga women in the public sphere has, in a way, empowered their political agency to assert for gender justice and greater participation and representation in formal politics. The 1990s were a significant period in Naga politics. The period witnessed the intensification of inter-factional violence between warring Naga insurgent groups. The signing of the ceasefire agreement between the Indian government and the Nationalist Socialist Council of Nagaland (Isak-Muivah) in 1997, and the subsequent peace talks that followed decades of violence, opened democratic space for Naga civil society to actively engage in the political process. Within this new dispensation, Naga women’s entry into the public sphere as ‘mothers’, rooted in private values and attributes such as nurturing, caring, and pacification, assumes significance. Naga women, traditionally confined to the private sphere, carved out a space for themselves in the public sphere by mobilizing for peace through a motherhood strategy. Based on primary and secondary sources, the paper examines the unique role that Naga women play in the public sphere, within the constraints of a traditional patriarchal ethos and Naga tribal customary practices that define gendered roles and perceptions for women.

Published by: Narotila ImchenResearch Area: Political Science

Organisation: Dimapur Government College, Dimapur, NagalandKeywords: Political Process, Peace Process, Civil Society, Patriarchy, Naga Women, Naga Mothers Association

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2. Performance Appraisal- A source of employee motivation in a Small Organisation

In today’s competitive and dynamic business environment, small organisations play a crucial role in economic development and job creation. However, their success largely depends on the motivation and commitment of their employees. Performance appraisal, when implemented effectively, serves as a key human resource tool to recognise employee contributions, provide constructive feedback, and foster motivation. This paper explores how performance appraisal systems influence employee motivation in small organisations. It analyses the relationship between fair evaluation, feedback mechanisms, goal alignment, and intrinsic as well as extrinsic motivation. The study is based on a mixed-method approach involving surveys and interviews conducted among employees of small enterprises. Findings reveal that transparent and participatory appraisal systems enhance motivation and job satisfaction, while a lack of clarity and bias in evaluation tend to demotivate employees. The paper concludes with recommendations for designing simple yet effective performance appraisal systems tailored to the needs of small organisations.

Published by: Rakshita BhattResearch Area: Management

Organisation: Graphic Era Deemed to be University, UttarakhandKeywords: Performance Appraisal, Employee Motivation, Small Organisations, Human Resource Management, Fairness, Feedback, Transparency, Job Satisfaction

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3. Hospital Appointment and Patient Management System

The CareSync Hospital and Patient Management System is a web-based platform designed to streamline hospital operations and improve patient care efficiency. The system provides separate login access for patients, doctors, nursing staff, administrative staff, and transport teams. Each user role has distinct functionalities tailored to their responsibilities. Patients can register, book appointments, view doctor schedules, access their medical history, and receive billing details online. Doctors can manage patient records, update diagnosis reports, and track appointments. The administrative staff can oversee hospital operations such as room and bed availability, billing, and staff scheduling. Nursing staff can track patient vitals, medication schedules, and treatment updates, while the transport team manages ambulance and in-hospital patient transfers efficiently. CareSync enhances hospital management by integrating modules like Appointment Scheduling, Room and Bed Booking, Billing Management, and Transport Coordination, all in a secure and user-friendly interface. The system minimizes manual paperwork, reduces human error, and ensures better coordination between departments. Ultimately, CareSync improves healthcare service delivery and patient satisfaction through automation, accessibility, and data centralization.

Published by: Deepika, Poorvi S Jadimath, Sneha C Yaligar, Preeti S PuranikResearch Area: Web Development

Organisation: Basaveshwar Engineering College, BagalkotKeywords: Hospital Management System, Patient Management, Appointment Scheduling, Healthcare Automation, Payment and Billing System, Web Application, CareSync.

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4. The Biochemical Basis of Schizophrenia: The Dopamine Hypothesis and Beyond

Schizophrenia is a complex neuropsychiatric disorder marked by a wide spectrum of symptoms, yet its biochemical basis remains unclear. While the classical dopamine hypothesis links excess dopaminergic activity to hallucinations and delusions, recent research implicates glutamatergic, GABAergic, serotonergic, and cholinergic systems, along with inflammatory and oxidative stress pathways. This paper argues that schizophrenia results from interactions among multiple neurotransmitter and receptor systems. By reviewing neuroimaging, pharmacological, and clinical trial evidence, it demonstrates that understanding receptor-specific contributions is crucial for developing targeted therapies addressing both cognitive deficits and affective symptoms.

Published by: Bhumika TeckchandanyResearch Area: Neuroscience

Organisation: Suncity School, GurgaonKeywords: Schizophrenia, Dopamine Hypothesis, Glutamate Dysfunction, NMDA Receptor Hypofunction, GABAergic Dysfunction, Serotonin Modulation, Neuroinflammation, Personalized Psychiatry

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5. Early Diabetic Retinopathy Detection using Federated Learning

Diabetic Retinopathy (DR) is a leading cause of vision loss worldwide, primarily affecting individuals with prolonged diabetes. Early detection is crucial to prevent irreversible blindness. This project proposes a secure and intelligent framework for the early detection of Diabetic Retinopathy using Federated Learning (FL), ensuring both data privacy and efficient model training across multiple healthcare institutions. The system utilizes Optical Coherence Tomography (OCT) images for accurate retinal analysis and employs Convolutional Neural Networks (CNNs) such as ResNet-50 and VGG-16 for disease classification. To enhance data security, Multi-Factor Authentication (MFA) is integrated, allowing only authorized medical professionals to access sensitive information. Unlike traditional centralized AI models, the proposed system prevents raw data sharing, thus maintaining patient confidentiality while improving diagnostic performance. Future enhancements, including Homomorphic Encryption (HE) and Explainable AI (XAI), will further strengthen data protection and interpretability of results. Overall, this system contributes to Sustainable Development Goal (SDG 3): Good Health and Well-being, by promoting accessible, secure, and intelligent healthcare solutions for early eye disease diagnosis.

Published by: Dharish Prasath D, Kalai arasi. M, Faziya. A, Jai Ganesh. S, Kavitha. IResearch Area: Information Technology

Organisation: SRM Valliammai Engineering College, Kattankulathur, Kanchipuram, Tamil NaduKeywords: Diabetic Retinopathy, Federated Learning, Optical Coherence Tomography (OCT), Convolutional Neural Network (CNN), Multi-Factor Authentication (MFA), Data Privacy, Secure Healthcare, Early Disease Detection, Homomorphic Encryption (HE), and Explainable AI (XAI).

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6. Financial Literacy among Youth

Financial literacy has emerged as a critical life skill in the 21st century, particularly for young people navigating an increasingly digital and complex financial environment. This paper examines the growing financial literacy gap among youth, emphasizing its implications for personal well-being, national productivity, and sustainable economic growth. It analyzes barriers such as limited access to structured financial education, overreliance on social media for financial advice, and the rising incidence of digital scams. Drawing on global comparisons, it highlights how countries like Singapore, Canada, and Australia have successfully integrated financial literacy into school curricula, while India continues to lag. The study underscores the urgent need to embed financial education into formal schooling, enhance teacher training, and strengthen digital financial awareness. Government initiatives such as the National Strategy for Financial Education (NSFE 2020–2025) demonstrate progress, yet a stronger post-2025 roadmap is essential. The paper concludes that equipping youth with financial skills not only improves individual financial resilience but also drives entrepreneurship, savings, and inclusive national development.

Published by: Ridhaan JainResearch Area: Financial Literacy

Organisation: Shri Ram School, AravaliKeywords: Financial Literacy, Youth, Financial Education, Digital Finance, Economic Development, Financial Inclusion, Entrepreneurship, India, National Strategy for Financial Education (NSFE), Global Comparison

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7. Harnessing the Wind: Evaluating Technological Advancements, Policy Frameworks, and Environmental Strategies for Large-Scale Wind Energy Adoption in India

India’s transition to clean energy is crucial for achieving its goal of 500 GW of non-fossil fuel capacity by 2030 and mitigating its dependence on coal. This research examines how advancements in wind energy technology, supportive policy frameworks, and sustainable environmental practices can collectively drive large-scale wind energy adoption in India. It explores the evolution of turbine design and efficiency, the promise of offshore wind energy, and the integration of digitalization and energy storage systems that enhance reliability and cost-effectiveness. The study further analyzes India’s policy landscape—including Power Purchase Agreements (PPAs), Renewable Purchase Obligations (RPOs), and incentives under the National Action Plan on Climate Change—highlighting their role in promoting investor confidence and infrastructure development. Moreover, it discusses environmental sustainability through Environmental Impact Assessments (EIAs), community engagement, and wildlife protection strategies. By comparing global best practices from Denmark, Germany, and China, the research identifies pathways for India to overcome challenges such as grid integration, regulatory inconsistencies, and land acquisition barriers. Ultimately, this paper concludes that a synergistic approach—combining technological innovation, policy support, and environmental stewardship—can position India as a global leader in sustainable wind energy development.

Published by: Vivaan DumirResearch Area: Renewable Energy

Organisation: Oberoi International School, Mumbai, IndiaKeywords: Wind energy, Offshore Wind, Renewable Energy Policy, Turbine Technology, Grid Integration, Environmental Impact Assessment (EIA), Sustainable Development, Climate Change Mitigation

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8. The Role of Mathematics in Sports Statistics: Analyzing Player Performance

Mathematics forms the backbone of modern sports analytics, enabling the transformation of raw performance data into structured, quantifiable insights that enhance both individual and team evaluation. This study examines how mathematical and statistical tools—including weighted averages, regression analysis, principal component analysis (PCA), z-score standardization, clustering methods, Monte Carlo simulations, and Expected Goals (xG/xA) models—collectively contribute to a sophisticated understanding of athlete performance. By applying these techniques, the research demonstrates how multidimensional player data can be normalized, compared, and interpreted to produce objective ratings and identify key performance indicators. Furthermore, the study highlights the predictive power of mathematical modelling in sports. Regression-based forecasting and probabilistic simulations allow analysts to estimate goal-scoring likelihood, evaluate tactical strategies, and anticipate match outcomes with greater accuracy. Dimensionality-reduction methods, such as PCA and factor analysis, streamline complex datasets into meaningful components, revealing hidden patterns and correlations within player behavior. Beyond individual assessments, mathematics also enhances broader strategic decision-making in areas such as player recruitment, opponent analysis, load management, and game planning. The findings emphasize that the integration of quantitative models not only improves analytical precision but also reduces subjective bias, resulting in a more transparent and reliable framework for performance evaluation. Overall, this research illustrates the essential role mathematics plays in shaping the contemporary sports analytics landscape, demonstrating how rigorous quantitative analysis contributes to improved tactical understanding, more informed coaching decisions, and data-driven competitive advantage.

Published by: Kashyap JalaliResearch Area: Statistics

Organisation: Edify School, Karnataka, BengaluruKeywords: Sports Analytics, Player Performance Evaluation, Statistical Analysis, Quantitative Analysis, Regression Analysis, Monte Carlo Simulations

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9. An Intelligent Matchmaking System for Peer-Assisted Learning in Educational Communities

This study presents an AI-driven intelligent matchmaking system that facilitates peer-assisted learning in educational communities by dynamically connecting students based on academic profiles, shared interests, and availability. The system addresses critical challenges in modern digital learning environments, including inefficient peer matching, a lack of personalization, and low student engagement. By leveraging machine learning algorithms, particularly TF-IDF vectorization and cosine similarity, the platform intelligently forms collaborative study groups that promote peer-to-peer knowledge exchange. The system integrates gamified learning features, including badges, points, and leaderboards, to sustain motivation, and incorporates real-time progress tracking through comprehensive analytics dashboards. Built using a microservice architecture with React.js frontend and FastAPI backend, the platform demonstrates superior scalability and modularity compared with traditional learning management systems. The testing results indicate the successful implementation of all core functionalities with 100% test case pass rates across the user management, matchmaking, resource sharing, and gamification modules. The system represents a significant advancement in creating student-centered, adaptive digital learning ecosystems that foster meaningful academic collaboration beyond conventional classroom boundaries.

Published by: Vinay Kumar Siddha, Poojitha Karuturi, Palli Kalyan Babu, Kona Karthik, Sneha PradhanResearch Area: Education Technology

Organisation: Sri Vasavi Engineering College, Andhra PradeshKeywords: Peer-Assisted Learning, Intelligent Matchmaking System, Educational Technology, Machine Learning Algorithms, Gamification in Education, Collaborative Learning Platforms, Microservices Architecture

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10. Chess and Business: Strategic Thinking, Risk, and Cognitive Ability

This paper explores how the strategic plays and discipline that chess cultivates translate into strategic thinking, cognitive and leadership abilities, and risk perception in the real business world. Studies cited in this paper show that people who interact with this strategic gameplay regularly generally display higher cognitive and problem-solving abilities and are more adept at dealing with high-stakes situations in the business world. This paper also looks at differences in risk-taking tendencies between different genders. This paper analyses the overlap between chess strategies and abilities that develop from regular interaction with the game, and the critical thinking, and business strategies which likely develop from the game as well, to the point where even the elite credit their success to the game.

Published by: Jaisal KohliResearch Area: Business Strategy

Organisation: Shiv Nadar School, GurgaonKeywords: Chess strategies, Business Strategies, Strategic Thinking, Problem Solving, Cognitive Abilities.

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11. Interpreting Opaque Scheduling Heuristics in Timetabling via Surrogate GNN

Opaque timetabling heuristics often deliver strong schedules yet remain difficult to interpret, limiting trust, diagnosis, and controlled adaptation in educational scenarios. This work presents a practical pipeline that learns a constraint-aware graph neural network (GNN) surrogate from input-output pairs of a black-box timetabling solver and then applies global explainability to characterize the surrogate’s decision-making logic across entities and relations in the context of timetabling. Using a synthetic dataset with hard constraints, the study evaluates both the assignment fidelity to the solver outputs and the feasibility under hard constraints, complementing these with global explanations and counterfactual sensitivity analysis. The results highlight which entities and relations most influence the predicted assignments. The pipeline is intended as a methods-oriented contribution that standardizes data generation, surrogate training, and explanation estimators for timetabling, enabling reproducible assessment of interpretability alongside fidelity and feasibility without claiming domain deployment readiness.

Published by: Kashish Ukey, Nakul Badwaik, Labdhi Soni, Ojas Kamde, Smita NirkhiResearch Area: Explainable AI

Organisation: GH Raisoni College of Engineering and Management, Nagpur, MaharashtraKeywords: Scheduling Algorithms, Surrogate Models, Explainable Artificial Intelligence, Black-Box Optimization, Model Interpretability, Decision Support Systems

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12. Visual Storytelling on Instagram: Redefining Digital Narratives in Indian Contexts

In contemporary India, Instagram has evolved into a powerful site of visual storytelling where images, reels, and aesthetic choices continually reshape how narratives are created, shared, and consumed. This paper explores how Indian creators—from rural artisans and independent journalists to lifestyle influencers and grassroots activists—use Instagram to express identity, culture, and socio-political consciousness. Moving beyond the platform’s commercialised image culture, the study highlights how Indian users adapt Instagram’s global features into localised storytelling traditions such as “darshana,” “kahani,” “dastangoi,” and “lok-drishti.” Through qualitative digital ethnography, content analysis of 200 Instagram accounts, and semi-structured interviews with 25 creators, this paper argues that Instagram in India is not merely a social media platform but a transformative narrative ecosystem. It enables micro-communities, democratizes content creation, and crafts new hybrid forms of cultural expression that blend imagery, captions, hashtags, and audio-visual cues. Findings reveal that Indian Instagram storytelling is shaped by regional languages, socio-economic aspirations, caste-class markers, digital literacy gaps, and platform algorithms that reward emotion-driven, relatable, and visually immersive content. The paper concludes with implications for digital culture, media literacy, and storytelling futures in India.

Published by: Vidhi Sikka, Mayank AroraResearch Area: Media And Communication

Organisation: Tecnia Institute of Advanced Studies, DelhiKeywords: Instagram, Visual Storytelling, Indian Digital Culture, Narrative Studies, Influencers, Digital Identity.

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13. Tackling Rural Healthcare Gaps: Intelligent Doctor Recommendation by Distil BERT with Coordinated Medicine Delivery

In rural healthcare, patients often struggle to navigate complex medical systems, leading to misdirected consultations and treatment delays. Traditional paper-based clinics further exacerbate inefficiencies with crowded queues and poor emergency handling. Current digital solutions typically offer only basic appointment booking or generic disease prediction, failing to provide personalized guidance or integrate the complete patient journey. Our AI-powered platform addresses these gaps using a fine-tuned Distil BERT model that analyses patient-described symptoms and recommends appropriate medical specialities with 83.8% accuracy. The system seamlessly integrates intelligent doctor matching with a token-based queue management system, real-time emergency SOS alerts, and digital prescription generation. This creates a comprehensive, patient-centric workflow from initial symptom assessment through treatment completion. Future enhancements will incorporate multi-lingual support, voice-input capabilities, pharmacy integration, and telemedicine modules to further expand accessibility and create a complete healthcare ecosystem for underserved communities.

Published by: Mansi Yadav, Mohammad Faizan, Nitin Singh Thakur, Neha KumariResearch Area: Artificial Intelligence In Healthcare , Natural Language Processing , Human-Computer Interaction

Organisation: Oriental Institute of Science and Technology, Madhya PradeshKeywords: Healthcare Access, Rural Healthcare, Doctor Recommendation System, Distil BERT, Natural Language Processing, Symptom Classification, Real-time Alert System, Digital Prescription.

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14. Real-Time Detection of Obfuscated Abusive Multilingual Comments using Prompt-Tuned and LoRA Fine-Tuned LLMs

The rapid expansion of multilingual communication on social media has led to a surge in abusive, toxic, and offensive user-generated content. Traditional rule-based filters and monolingual detection systems fail to address modern linguistic challenges such as code-mixing (English–Hindi– Hinglish), transliteration variance, and obfuscation (e.g., “id!ot”, “b!tch”). To address these limitations, this work proposes a real-time multilingual abusive comment detection framework built using a LoRA-based parameter-efficient fine-tuning approach on Multi-lingual BERT (mBERT), augmented with a custom preprocessing pipeline and prompt-based linguistic normalization. The proposed system integrates leetspeak decoding, repeated-character normalization, slang expansion, context-driven abusive-pattern recognition, and Hindi transliteration handling, significantly improving classification robustness. The fine-tuning utilizes Low-Rank Adaptation (LoRA) to enable efficient domain adaptation without full-model training costs. A Flask-based REST API and Web Interface provide real-time detection capabilities with confidence scoring and content-restriction logic. Experiments show improved F1 scores on code-mixed and obfuscated datasets, demonstrating substantial gains over baseline mBERT and rule-based systems. Future work aims to extend the system to multimodal toxicity detection, emoji-semantic embeddings, and adversarial robustness.

Published by: Ayushi Gupta, Arjita Prajapati, Anushka Agrawal, Ayushi Uikey, Anamika JoshiResearch Area: Computer Science Engineering

Organisation: Oriental Institute of Science and Technology, Madhya PradeshKeywords: Abusive Speech Detection, Multilingual NLP, mBERT, LoRA Fine-Tuning, Text Normalization, Obfuscation Handling, Real-Time Moderation.

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15. Smart Home System Automation Based on Zigbee Protocol with Internal Cloud Server

The standard protocols used in educational, business, residential, and industrial environments in Indonesia still rely on standard protocols such as Wi-Fi and Bluetooth. This applied research is related to a standard protocol called Zigbee, which is IEEE 802.15.4 standard that has begun to be widely used in networks for IoT-based control purposes. In smart home technology, connectivity is very important. To build a smart home system, users must consider the connectivity or communication between one smart home device and another. The most familiar and widely used communication protocol network for smart home devices is currently Wi-Fi. However, alternative wireless connectivity protocols are now emerging, one of which is Zigbee. Zigbee is a global standard for low-power, short-range networks, offering a complete and operable Internet of Things (IoT) solution for homes and buildings. Zigbee has features that enable it to manage its own network and data exchange on the network, and it can support hundreds of devices and has reliable security features. In this applied research, monitoring uses the Zigbee protocol with a cluster topology consisting of a Zigbee coordinator and several Zigbee end devices that will be installed in locations with or without wall obstructions.

Published by: Muhammad Sulkhan Arif, Wawan Heryawan, bangbang HermantoResearch Area: Electrical Engineering

Organisation: Politeknik Negeri, IndonesiaKeywords: Zigbee, IoT, Smart Home.

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16. The Impact of English language on different languages

This research paper examines the impact of English on different languages, German, Hindi and French. It looks at how English has evolved from being a regional language confined to a small area to a lingua franca through colonial expansion and globalisation. This research shows that the impact of English is neither uniform nor superficial. This paper highlights how the English language influences each of these three languages differently based on different historical, political, and socio-cultural contexts. This paper demonstrates how English simultaneously opens a path for global opportunities, but at the same time presents a challenge to linguistic integrity and heritage.

Published by: Aanya ChahalResearch Area: Sociocultural Linguistics

Organisation: Heritage Xperiential Learning School, HaryanaKeywords: Language Erosion, Language Imperialism, Language Hybridization, Loanwords and Borrowing, Globalisation.

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17. The Triple Barrier: Pricing, Distribution, and Policy Dynamics Shaping Organic Food Sustainability in India

This study employs the rigorous frameworks of the Triple Bottom Line (TBL)—assessing people, planet, and profit and Value Chain Analysis (VCA) to investigate the structural imperatives of pricing, distribution, and policy in determining the long-term sustainability of India’s burgeoning organic food sector. The market demonstrates robust economic potential, with growth projections estimated up to a Compound Annual Growth Rate (CAGR) of 20.13% through 2033, driven largely by burgeoning urban health consciousness and a strong global export orientation. However, the analysis indicates that true sustainability remains structurally fragile. The sector faces a critical "triple barrier" that restricts value capture and systemic resilience. The report concludes that achieving a sustainable organic ecosystem by 2030 requires integrated policy intervention, specifically focusing on certification reform, public-private investment in cold-chain logistics, and implementing dual incentive models to ensure fair pricing and broader market access.

Published by: Naina Singh KhatkarResearch Area: Organic Food Sustainability

Organisation: Delhi Public School, HaryanaKeywords: Organic Food Sustainability, Organic Food Sector in India, Policy Intervention Models, Social Sustainability, Policy Regulation.

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18. How Can Global Brands Balance Cultural Authenticity and Universal Appeal in an Era of Glocalization?

In today’s globalized yet culturally diverse marketplace, multinational brands face the complex challenge of balancing universal brand identity with localized cultural relevance. This research explores the strategic concept of glocalization, which integrates global brand consistency with authentic local adaptation to enhance consumer resonance. Through qualitative methodology, secondary data analysis, and case studies of McDonald’s, Coca-Cola, Nike, and Starbucks, the study demonstrates that cultural authenticity significantly strengthens consumer trust, emotional engagement, and brand loyalty. Findings reveal that successful glocalization requires maintaining universal brand values while adapting products, messaging, and customer experiences to align with cultural beliefs, traditions, and socio-emotional expectations. The study also analyzes branding failures such as Dolce & Gabbana and Pepsi to highlight risks of cultural insensitivity. As digital transformation accelerates hyper-local targeting and consumer co-creation, glocalization emerges as a strategic necessity for competitive advantage. The research concludes that brands that develop cultural intelligence, empower local insight, and adopt flexible global frameworks can achieve sustainable global-local equilibrium.

Published by: Siya SarojResearch Area: Global Branding Strategy

Organisation: SP Jain School of Global Management, Dubai, Mumbai, Singapore and SydneyKeywords: Glocalization, Cultural Authenticity, Global Branding, Localization Strategy, Consumer Perception, Brand Identity, Cultural Intelligence, Digital Hyper-Localization, Cross-Cultural Marketing, Global-Local Balance, Brand Loyalty, Case Studies.

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19. Smart Basket

The Smart Basket is an automated, RFID-enabled shopping system designed to enhance the retail shopping experience by eliminating manual billing and reducing customer waiting time at checkout counters. The proposed system integrates an RFID reader, RFID tags, a microcontroller, and an LCD display into a shopping trolley, enabling automatic identification and pricing of products as they are placed inside or removed from the cart. Each product is equipped with a passive RFID tag, which is detected instantly by the RFID reader, and the corresponding information—such as product name, price, and updated total bill—is displayed to the user in real time. The system also incorporates an RFID card-based authentication mechanism to ensure secure access and user identity verification during purchase. The Smart Basket minimizes human intervention in billing, reduces errors associated with manual scanning, and increases overall operational efficiency in shopping malls and supermarkets. By providing a transparent, user-friendly, and time-saving shopping environment, the system contributes to improved customer satisfaction and smoother store management. This project demonstrates that RFID technology can serve as a cost-effective, scalable, and reliable solution for modern retail automation and lays the foundation for future integration of IoT, mobile payments, and AI-based analytics.

Published by: Rajwardhan Ashok Pawar, Rupesh Natha Pawar, Paresh Rajendra Jagtap, Shahid Nazim Mulani, S. P. SuryawanshiResearch Area: Iot And Ai

Organisation: Adarsh Institute of Technology and Research Centre, MaharashtraKeywords: Smart Shopping Basket, Internet of Things (IoT), Automatic Billing System, RFID Technology, Load Cell Sensor, Embedded Systems.

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Research Paper

20. Data-Driven Crop Recommendation for Rajasthan Using Linear and Ensemble Models

The agricultural sector is a vital part of the Indian economy, comprising 18.2% of India’s GDP and representing approximately 44% of the total labour force. However, one of the biggest problems faced is the loss of crop yield, especially among farms using traditional methods of farming that lack the technological means to predict and maximise their potential yield. The problem is further compounded by farmers often being unaware of which crops are suitable, given conditions that are specific to individual farmers or parcels of land. This research paper focuses on maximising crop yield by helping farmers choose a suitable crop in Rajasthan, one of the largest Indian states by land mass and population, where over 54% of citizens depend on agriculture as a primary source of income. The data used throughout this paper are publicly accessible and are taken from multiple official Indian government sources. Using these data, the paper incorporates exploratory data analysis to identify key variables such as soil nutrient levels, rainfall, and temperature that influence crop performance. Furthermore, the paper aims to lay out the groundwork for building a crop yield prediction and, primarily, a crop recommendation model that is easily accessible and simple to understand. This is implemented using a transparent linear regression baseline and a decision-tree-based ensemble approach, specifically Random Forest.

Published by: Aryaveer JainResearch Area: Data Science, Statistics, Agriculture, Technology

Organisation: Hill Spring International School, MaharashtraKeywords: Crop Yield Modelling, Random Forest, Multiple Linear Regression, Soil Nutrients, Rainfall Variability, Agricultural Decision Support, Rajasthan Agriculture.

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21. A Study of Clustering Analysis in Identification of Butterfly Species

This study investigates the use of clustering analysis techniques for identifying butterfly species based on their morphological characteristics. Butterflies exhibit substantial variation in wing patterns, colors and body size which makes traditional taxonomic identification both time-consuming and error-prone. Clustering analysis provides a data-driven strategy to group individuals into putative species based on similarities in measurable features. By applying multiple clustering algorithms together with appropriate validation methods, this work evaluates the effectiveness of clustering analysis for butterfly species identification and highlights its potential applications in biodiversity research and conservation. Accurate identification of butterfly species is fundamental to biodiversity conservation, ecological monitoring, and environmental impact assessment. This study examines the efficacy of clustering methods for species identification using butterfly image data. Several algorithms, including K-means, hierarchical clustering, spectral clustering, Gaussian mixture models, and DBSCAN, are employed to partition images into species clusters. To represent discriminative visual information, feature extraction techniques such as Histogram of Oriented Gradients (HOG), Gray Level Co-Occurrence Matrix (GLCM), and Local Binary Patterns (LBP) are used to encode wing textures and shape characteristics. The quality of the resulting clusters is assessed by comparing them with known species labels, enabling a systematic evaluation of each method. The results indicate that clustering analysis offers a scalable and promising approach for automated butterfly species identification and biodiversity monitoring, while also clarifying the strengths and limitations of different clustering techniques for image-based species classification.

Published by: Ajaykumar RResearch Area: Machine Learning

Organisation: Christ College Mysore, KarnatakaKeywords: Butterfly, Identification, Species.

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Research Paper

22. Ergonomic Mechanical Tools for Reducing Repetitive Strain Injuries among Workers in Small-Scale Manufacturing Units

Repetitive strain injuries (RSIs) have emerged as a major challenge within small-scale manufacturing environments, damaging worker health and productivity. Ergonomically designed mechanical tools are increasingly recognized as a pivotal solution to this chronic problem. This paper undertakes a thorough examination of RSI etiology, analyzes ergonomic design methodologies relevant for mechanical tools, and synthesizes practical recommendations for designing interventions targeted at small enterprises. Emphasizing both technical and organizational dimensions, the discussion highlights evidence-based strategies and implementation barriers, providing a comprehensive roadmap for sustained ergonomic improvement.

Published by: Nevaan AggarwalResearch Area: Mechanical Engineering

Organisation: Shiv Nadar School, HaryanaKeywords: Ergonomic Tool Design, Repetitive Strain Injuries, Small-Scale Manufacturing, Anthropometric Data, Vibration Reduction, Grip Force Optimization, Participatory Ergonomics, Occupational Health.

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23. AI Bias in Data Training

This research paper talks about AI bias in data training and how it creates age, gender and cultural discrimination. This paper also talks about how spreading awareness about AI bias can help mitigate the issue. It examines how biased training data distorts decision-making in various fields like hiring, healthcare and law enforcement. This paper shows us the need for transparency, accountability and awareness in AI systems and how mitigating data bias is essential for creating an AI system that is fair, responsible, and that can be held accountable in case of any biased decisions and output.

Published by: Sarjas Gauhar SinghResearch Area: Artificial Intelligence

Organisation: Heritage Xperiential Learning School, HaryanaKeywords: AI Bias, Biased Training Data, Algorithmic Discrimination, Awareness and Bias Mitigation, Transparency and Accountability.

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24. Parkinson’s Disease – History, detection, and cure

This paper talks about the neurodegenerative disease commonly known as Parkinson's disease, about the history of this disease and its causes, various subtypes, as well as how the diagnosis of this disease takes place. It has mainly 3 causes those being environment, genetics, or interactions. It usually happens to people above the age of 60, but there are younger cases as well. This disease causes loss of dopaminergic neurons in the brain; these neurons help in motor activities of the body, thus their loss causes loss of motor activities of the body. The dopamine-producing neurons Substantia Nigra are directly affected. The neurons degenerate due to the accumulation of Alpha’s nuclein in the brain. The paper discusses how motor, non-motor and psychological aspects should be taken into account during the identification of this disease.

Published by: Prisha TeotiaResearch Area: Neurodegenerative Disorder

Organisation: Suncity World School, HaryanaKeywords: Parkinson's Disease, Neurodegenerative Disease, Brain Disorder, Carbidopa-Levodopa, Dopaminergic Neurons, Disease Treatment.

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Research Paper

25. AI-Driven Smart Air Quality Monitoring and Predictive Pollution Control System Using IoT and Edge Computing

Air pollution has become a major environmental threat, yet traditional monitoring systems rely on expensive fixed stations with limited coverage and delayed reporting. This project introduces an AI-driven Smart Air Quality Monitoring and Predictive Pollution Control System that integrates IoT sensors, edge computing, machine learning, and cloud analytics for real-time, scalable monitoring. A network of low-cost sensors measures pollutants such as PM2.5, PM10, CO₂, CO, and NO₂, sending data to an edge device (ESP32/Raspberry Pi) for cleaning, filtering, and anomaly detection. Edge processing minimizes latency, saves bandwidth, and enables rapid local decision-making. Cleaned data is then uploaded to the cloud, where models like Random Forest, XGBoost, and LSTM generate short- and long-term pollution forecasts. An interactive dashboard visualizes real-time AQI, spatial patterns, and predictive insights to support timely interventions. Overall, this cost-effective system demonstrates key CS engineering skills and offers a practical framework for smarter, healthier, and more resilient cities.

Published by: Daksh JainResearch Area: Environmental Engineering

Organisation: Jayshree Periwal International School, RajasthanKeywords: IoT, Air Quality Monitoring, Predictive Analytics, Machine Learning, AQI Forecasting, Edge Computing, Smart Environmental System, Pollution Control, Real-time Sensors, LSTM.

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Research Paper

26. Greenscan: An AI-Powered, Cross-Platform System for Instant Plant Identification and Care Guidance

This paper presents GreenScan, an intelligent and interactive web platform developed to enable fast, accurate, and user-friendly plant species recognition through uploaded images. Addressing the persistent challenges of manual plant identification, such as inefficiency, limited accessibility, and a lack of centralized information, GreenScan leverages the power of Artificial Intelligence (AI) and Deep Learning to deliver real-time classification of more than 100 distinct plant species. The system employs a Convolutional Neural Network (CNN) model trained on a large and diverse dataset of plant images to ensure high recognition accuracy, even under varying lighting and background conditions. The platform integrates a responsive and intuitive web interface, allowing users to seamlessly upload images, view classification results, and explore detailed plant profiles. Each identified species is linked to a comprehensive backend database containing essential details such as taxonomy, physical characteristics, ideal growing conditions, and care guidelines. Furthermore, GreenScan provides external purchase links and educational resources, making it an invaluable tool for students, researchers, horticulturists, and nature enthusiasts. A key feature of GreenScan is its feedback-driven learning mechanism, which enables continuous model retraining based on user input to progressively enhance prediction precision over time. The platform’s implementation achieved high confidence scores, including a 91% accuracy rate for identifying species such as the Snake Plant. Beyond its technical merits, GreenScan contributes significantly to promoting environmental education, sustainable living, and ecological awareness by bridging the gap between modern technology and biodiversity knowledge. This work demonstrates the potential of AI-powered solutions to transform traditional plant identification into a more engaging, efficient, and educational digital experience.

Published by: Vaishnavi Duratkar, Twinkal Sapate, Snehal Ninawe, Sanket Barapatre, Ashwary Dhakate, Sharwari Mohadikar, Prajakta Singham, Mamta BalbudheResearch Area: Computer Science And Engineering

Organisation: Karmaveer Dadasaheb Kannamwar Engineering College, MaharashtraKeywords: GreenScan, Plant Recognition, Artificial Intelligence, Image Classification, Web Application.

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