Authors - Reena (Mahapatra) Lenka, Jaya Chitranshi, Vanishree Pabalkar Abstract - Artificial Intelligence (AI) has undoubtedly emerged as an extremely dynamic and powerful tool in the area of IT. It is currently handling complex-work in data-analysis, working through predictive modeling, showcasing high level of capabilities and supporting the function of strategic decision-making. AI is dependent on real-time data to identify patterns of attrition, understand dissatisfaction and predict future exits. An AI system in the area of HRM, would thus help the organization in filtering staff-retentions and impending attrition. Meaningful insights can be developed with the use of AI that will help organizations work on reducing employee-turnover on one hand and engaging with their workforce in the long-run, on the other. The innovation elaborated in the study, connects with forecasting the employee-attrition and retention strategies in human resource management. It makes use of AI (Artificial Intelligence) through which HR data sources are incorporated to analyze performance evaluations, engagement surveys, attendance records and demographics in real time and historical context. The machine learning embedded in the system will detect patterns that show evidence of turnover and associate attrition scores to each employee, then recommend targeted retention strategies through personalized career guidance, modification of the workload, and incentives. The system incorporates attrition feedback loops to heighten prediction accuracy and refine strategies over time, enabling the organization to control and reduce turnover rates, boost workforce stability, and achieve cost savings. It is scalable across verticals like corporate HR, healthcare, education, and retail, where talent retention is imperative.
Authors - Reena (Mahapatra) Lenka, Jaya Chitranshi, Vanishree Pabalkar Abstract - A person's ‘perception’ and ‘consumer behaviour’ regarding mutual funds both are influenced by a variety of factors, including socioeconomic characteristics of a given society, financial awareness, risk tolerance, and prior investing experiences. As a professionally managed investment choice and a convenient investing tool, mutual funds are particularly well-liked among middle-class and urban individuals. In contrast to traditional savings instruments, investors typically connect mutual funds with advantages such as access to liquidity, diversification opportunities, and the potential for higher returns. Additionally, perceived dangers, market volatility, and a lack of thorough understanding of financial instruments all have a significant impact on consumer behaviour. A mutual fund is a professional system that collects funds from different investors for investment and protection. Since shared reserves have no legal meaning, the term applies as ambiguously as possible to aggregate speculation that is controlled, accessible, and open to investors. Mutual funds enjoy strengths and weaknesses instead of putting resources directly into personal protection. Today, they represent a significant portion of household budgets. Therefore, the current review focuses on general asset-related buyer behavior and preeminent mutual fund companies. Information was gathered from important resource sources. Important information was collected through systematic research. An opportunity-sampling method was used to collect responses, and the process was targeted toward major Indian cities. This review provides information on donor mindfulness of communal property, donor knowledge, donor propensity, and communal property sufficiency. Ideas were also developed to enhance mindfulness of joint assets and measures to select appropriate common assets to increase profit.
Authors - Jeevesh Sharma Abstract - Blockchain technology is largely used in banking, but it also has applications in gaming, real estate, supply chain management, and healthcare. By 2023, digital money will be the most widely discussed blockchain application. The potential uses of blockchain technology concerning various facets of any sector, market, agency, or governmental organization have gained attention in recent years. Blockchain scalability analyzes the effects on the security of scaling blockchain networks to support more transactions per second. This innovative distributed peer-to-peer architecture drew the interest of companies and communities outside and inside the financial sector. Furthermore, the system it operates in has been created around numerous scenarios that address the trust issue in open networks without the requirement for a trustworthy third party. Even though its decentralized structure allows for a wide range of potential applications, scalability remains a hurdle. Function extension, excessive delay in confirmation, and performance inefficiency are three important areas where blockchain scalability has been hindered. This research paper provides a thorough summary of previous research on scalable blockchain systems.
Authors - Ajidhashini Thulasidass, M. Suresh Abstract - Climate change is making agriculture more challenging in many parts of the country. This is notably true in developing nations where small farmers depend on systems that obtain water from rain to keep their land open. Numerous studies were conducted from 2015 to 2025 to discover how climate change is transforming farming systems in rural regions, how people are responding, and what policies are in place to make these systems safer and more resilient. It looks at significant challenges, including rising temperatures, unclear rain, soil depletion, and more pests that consume food. There is less food, which contributes to reduced food production and declining market stability. One method to make things better is to employ local expertise. Another is to employ agroforestry. Most individuals have problems agreeing because they don't have enough money, technology, or aid from the government. There are tips for extra reading at the end of the essay. To enhance farming, we may employ both new and ancient equipment and processes, as well as long-term research and approaches that engage both men and women.
Tuesday August 25, 2026 9:30am - 11:30am IST Virtual Room CGOA, India
Authors - Reena (Mahapatra) Lenka, Ronak Gupta, Vanishree Pabalkar, JayaChitranshi Abstract - Organizations in the contemporary global economy encounter substantial challenges in managing payroll operations, particularly concerning data security, transparency, and compliance with diverse regulatory standards. Traditional payroll systems rely on centralized infrastructures and are vulnerable to fraud, inefficiencies, and elevated operational costs. These centralized systems pose significant risks, including unauthorized data access and single points of failure, leading to potential data breaches and financial losses. Organizations handling payroll operations in today's international market confront several obstacles, such as protecting data, upholding openness, and adhering to various legal standards. Because they frequently rely on centralized infrastructures, traditional payroll systems are vulnerable to fraud, inefficiency, and excessive operating expenses. In order to solve these problems, this article investigates the integration of blockchain technology into payroll management. We suggest a multi-layered architecture that consists of (1) an off-chain Human Resources (HR) system for payroll and employee management, (2) a distributed storage layer that uses technologies such as the Interplanetary File System (IPFS) for safe data storage, and (3) an on-chain blockchain layer that uses smart contracts to guarantee immutable transaction records and automate payroll processing. This decentralized approach enhances transparency, bolsters security through encryption and consensus mechanisms, and streamlines payroll operations by reducing manual dependencies. Furthermore, the system facilitates real-time cross-border payments and integrates with Decentralized Finance (DeFi) platforms, offering employees innovative financial services. By leveraging blockchain for payroll, organizations can enhance trust, reduce operational costs, and eliminate redundancies, making it a promising use case for HR departments worldwide. This framework demonstrates how blockchain technology can revolutionize payroll management, increasing organizations' efficiency, cost-effectiveness, and trust.
Authors - Shripada Rao, Aadithya Mahesh, Navya Jaideep, Rajeshwari Hegde, Vinay Rao, Saurabh Suman Choudhuri Abstract - This paper introduces a novel approach to integrate LLM capabilities directly on mobile devices to enhance chat applications. By implementing a tonality-driven paraphrasing feature, our system can rephrase poorly written messages into clear, professional text while preserving the intended tone. Unlike conventional server-side AI solutions that raise privacy concerns, our approach processes data locally using fine-tuned models (TinyLlama Instruct 1.1B and Qwen2 0.5B) with parameter-efficient techniques such as LoRA and QLoRA. Experimental evaluations demonstrate competitive paraphrasing quality, improved inference speed, and reduced resource consumption on mobile devices, making this work a promising step toward privacy-preserving on-device conversational assistance.
Authors - Anusha.S.Pujar, Gourishankari.S.P, Saniya.G, Pooja.B.L, Sanchit.H, Amit.N, Suneetha.V.B Abstract - For the purpose of controlling traffic flow, identifying congestion, and averting accidents, contemporary urban traffic monitoring is essential. An enhanced YOLOv5 model is presented in this study for precise vehicle tracking and identification under a variety of circumstances, including day and night. A multi-scale feature detection layer for seeing cars of all sizes in congested regions and an improved pixel-to-real-world distance calibration for accurate speed and distance estimation are two important improvements. Real-time traffic management is improved by integrated collision warning and congestion identification algorithms. Experimental results demonstrate improved detection reliability and mean Average Precision (mAP), making this approach suitable for scalable urban traffic control systems.
Authors - Pratiksha Kulkarni, Rakshita Patil, Veena S Kulkarni, Satish Chikkamath, Suneeta V Budihal, Sujatha Kotabagi Abstract - The major reason for deaths across is due to alarming increase in Heart Disease. There are many factors which elevates the risk of cardiovascular diseases which includes high blood pressure, obesity, cholestrol, smoking habits , lack of physical activities and heavy work pressure. Diagonising and identifying the Heart disease in prior is a challenging task.Which can be overcome by Machine learning methods based on huge dataset of patient traits and medical indicators that help in prediction of heart diseases.
Authors - Dipti Varpe, Gouri Kulkarni, Nishant Thakare, Mitesh More, Suyog Shinde, Navanath Patil Abstract - Traditional farming methods often require extensive manual labour, leading to inefficiencies and increased costs. Recent advancements in agricultural robotics provide innovative solutions to automate essential tasks. The Node-MCU based Solar Powered Multipurpose Farming Robot is an autonomous system designed to enhance farming operations, including ploughing, weeding, and harvesting. Powered by solar energy, it offers a sustainable and energy-efficient alternative to conventional farming practices. The robot operates using a Node-MCU microcontroller, ensuring precise navigation and task execution. Integrated soil moisture and temperature sensors enable real-time environmental monitoring, optimizing farming decisions. Programmed via Node-MCU IDE, the robot is customizable and supports various smart farming features. With its modular design, multiple farming tools can be attached, reducing labour demands and improving efficiency. Additionally, IoT connectivity enables remote monitoring and control through cloud-based platforms. By integrating renewable energy, automation, and IoT-driven sensing technologies, this project enhances agricultural productivity while promoting sustainability. The system lays the groundwork for intelligent robotic solutions in modern farming.
Authors - Harie Sanker V, Gayathri E , Akshay R, Vandana Madhavan Abstract - The human resource management practices have developed alongside technological advancements. AI-based coaching and engagement chatbots are new tools with a great potential to improve employee engagement. Conventional coaching processes have certainly proven their effectiveness but could never attain the scalability or cost-efficiency needed for widespread implementation. Machine learning- and natural language processing-adapted AI solutions can assist by providing real-time feedback, setting goals, and automating HR services based on specific individual need assessments. This research is aimed at understanding the influence of the AI coaching and chatbots on motivation, active engagement, and general employee satisfaction within technological organizations. This study employed primary data collected from questionnaires, finding that AI coaching promotes motivation, satisfaction, and expansion of remote working opportunities. However, lack of trust in AI and perceived ethical absence of transparency on the part of recommendations made by the AI can be seen as significant drawbacks. To overcome these challenges, a hybrid form of human-AI coaching is suggested where AI maximum benefits are retained without missing out on the human touch and consideration that defines coaching. This may facilitate the understanding of the substantial influence that AI has on employee engagement and ultimately on the future of human resource management. The study also suggests how organizations can optimally leverage AI coaching and engagement chatbots while minimizing associated risks.
