Volume 14 | Issue 4

 Abstract

भारतीय ज्ञान परंपरा केवल अतीत की स्मृति नहीं है, बल्कि जीवन को समझने और संतुलित ढंग से जीने की एक दीर्घकालिक पद्धति है। यह मनुष्य को केवल ज्ञान अर्जित करने वाला प्राणी नहीं मानती, बल्कि उसे एक ऐसे जीवित चेतन अस्तित्व के रूप में देखती है जिसमें शरीर, मन, बुद्धि, भाव, आचरण और आत्मिक संवेदना सभी का महत्व है। इसी कारण भारतीय परंपरा में ज्ञान का अर्थ केवल सूचना या तथ्यों का संचय नहीं, बल्कि जीवन के साथ उसका संबंध स्थापित करना है। आज के समय में यह दृष्टि और अधिक महत्त्वपूर्ण हो जाती है, क्योंकि आधुनिक समाज में बाहरी प्रगति के साथ-साथ भीतरी असंतुलन, मानसिक तनाव, मूल्यहीनता, सांस्कृतिक दूरी और सामाजिक विखंडन जैसे संकट बढ़ते दिखाई दे रहे हैं। विशेष रूप से युवा और विद्यार्थी इन परिस्थितियों से गहरे रूप में प्रभावित हैं।यह शोध भारतीय ज्ञान परंपरा की आज की आवश्यकता, उसकी प्रासंगिकता और उसके व्यवहारिक प्रयोग की संभावनाओं को समझने का प्रयास करता है। अध्ययन का एक प्रमुख उद्देश्य यह भी है कि भारतीय ज्ञान परंपरा को केवल दार्शनिक विमर्श तक सीमित न रखा जाए, बल्कि शिक्षा, परिवार, समाज और नीति के स्तर पर उसे लागू करने योग्य रूप में सामने लाया जाए। इसी दिशा में इस अध्ययन में एक क्रियान्वयन रूपरेखा को प्रस्तुत किया गया है, जिसमें पाठ्यक्रम, शिक्षण पद्धति, भाषा, शिक्षक प्रशिक्षण, मूल्यांकन, डिजिटल माध्यम, परिवार और सामाजिक जीवन सबको एक साथ जोड़ा गया है।अध्ययन का निष्कर्ष यह है कि भारतीय ज्ञान परंपरा आज के भारत के लिए केवल सांस्कृतिक गौरव का विषय नहीं, बल्कि शिक्षा को पुनः मानव निर्माण की प्रक्रिया बनाने का आधार बन सकती है। यदि इसे सरल, सुगम, जीवनोपयोगी और समकालीन संदर्भों के अनुरूप प्रस्तुत किया जाए, तो यह व्यक्ति के भीतर नैतिकता, आत्मानुशासन, सामाजिक उत्तरदायित्व, मानसिक संतुलन और सांस्कृतिक आत्मविश्वास विकसित कर सकती है। इस प्रकार यह एक संतुलित, नैतिक और समरस समाज के निर्माण में महत्वपूर्ण भूमिका निभा सकती है।

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This research focuses on the sustainable design development of the paisley motif in fabric painting. It is an invention from ancient Persian and Indian art and has developed through changes in shapes, styles, and designs. Even though it has been studied extensively in the context of fashion and textile printing, its usage in fabric painting, particularly the ways in which paisley can be created by designers, has not been well researched. This paper will address the origination of paisley patterns, their adaptation to fabric painting, techniques used, and strategies employed in making them in surface design.

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Paisley Motif, Sustainable Design Development, Fabric Painting.

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With the rapid growth of decentralized finance (DeFi) and peer-to-peer transactions on high-performance blockchains, managing trustless escrow for assets between untrusted parties has become essential for security, transparency, and efficiency. Traditional centralized escrow services are slow, expensive, and vulnerable to counterparty risk. This project proposes a Secure Solana Escrow Smart Contract System that automates escrow creation, fund deposit, conditional release, and dispute handling using on-chain logic. The system comprises two primary modules: (1) Escrow Creation and Management, and (2) Intelligent Transaction Execution and Release. In the first module, users create escrow accounts via a web-based dApp; the smart contract (developed in Rust using the Anchor framework) validates parties, amount, and release conditions. The second module automatically releases funds upon condition satisfaction or enables refund/cancellation. The contract leverages Solana's Program Derived Addresses (PDAs) for secure fund holding, Solana Web3.js for client interaction, and SPL token support for fungible/non-fungible assets. All transactions are recorded immutably on the Solana blockchain, enabling real-time monitoring and auditability. The system is developed using Rust, Anchor framework, Next.js/React frontend, and Solana RPC nodes. Experimental testing on Solana Devnet demonstrates that the system achieves transaction confirmation in under 400 milliseconds with 99.2% success rate and near-zero compute unit wastage compared to manual or Ethereum-based escrow solutions. This project delivers a scalable, low-cost, and tamper-proof escrow solution for modern DeFi ecosystems, contributing to the advancement of trustless Web3 applications.

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Escrow Bond, Solana Blockchain, Escrow Smart Contract, Anchor Framework, Rust, Decentralized Finance (DeFi), Trustless Transactions, Program Derived Addresses (PDA), Secure Asset Management.

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Black hole attacks pose a significant threat to network security, particularly in Mobile Ad Hoc Networks (MANETs), where malicious nodes absorb and discard data packets. This paper proposes a Long Short-Term Memory (LSTM)-based deep learning model to detect and prevent black hole attacks by analyzing sequential network behaviour. The model leverages temporal dependencies in routing patterns to identify anomalies. Experimental results demonstrate that the proposed approach achieves high detection accuracy and reduces packet loss compared to traditional methods.

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LSTM, Black Hole Attack, MANET, Intrusion Detection, Deep Learning, Network Security

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Institution of prison is a mechanism used for punishing convicts and detaining offenders waiting trial and is an integral part of criminal justice system. With the advancement of the humanitarian movement the concept of prisons and the prison system from mere facilitator for the exclusion and segregation of Criminal offenders has been transformed into reformative and correctional institutions. Originally, prisons were used only to detain criminals until their trials began and to house inmates for the duration of their sentences now focus is on psychological treatment of the offender to reform the criminal thought of the convict and to help him to return back into society. The essay is an analysis of the evolution of the prison system in India from ancient to modern time in the light of contemporary humanitarian movement, highlighting the pivotal role of the Supreme Court of India in safeguarding inmates' human rights through the interpretation and expansion of fundamental rights enshrined in the Constitution of India, thereby developing a comprehensive jurisprudence of prisoners' rights. This paper endeavors to study the landmark judgments of the Supreme Court of India, considering the profound sensitivity surrounding the human rights issues related to prisoners, including the torture of detainees, the disappearance of suspects, and the prolonged detention of under-trials without trial.

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Prisoners, Punishment, Rehabilitation, Supreme Court, Humanities.

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Cardiovascular diseases (CVDs) are among the leading causes of death worldwide. Early prediction and prevention are essential to reduce mortality rates. Artificial Intelligence (AI) and Machine Learning (ML) techniques have been widely used to predict cardiovascular risk using patient health data. However, many AI models act as "black boxes," making their predictions difficult to understand for medical professionals. Explainable Artificial Intelligence (XAI) provides transparency by explaining how AI models make predictions. This paper presents an explainable AI framework for cardiovascular risk assessment using machine learning models and interpretation techniques such as SHAP and LIME.

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Explainable Artificial Intelligence (XAI), Cardiovascular Disease (CVD) Prediction, Machine Learning, SHAP and LIME, Healthcare Decision Support Systems.

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This study is based on understanding something that we come across almost every day but don't always stop and think about properly--why people keep buying the same brand again and again, even when there are many other options available. In today's market, just having a good product is definitely important, but at the same time, it is no longer enough on its own. Customers now expect brands to connect with them in a more meaningful and consistent way. The main objective of this research is to examine how consumer engagement influences brand loyalty, especially in the FMCG sector, with ITC as the primary focus. A total of 81 responses were collected through a questionnaire. While collecting the data, it was observed that many people already had fixed preferences for certain brands, even when similar alternatives were easily available in the market. Factors like trust, product quality, and communication were taken into consideration. It was also noticed that people who interact more with a brand--either directly through usage or indirectly through advertisements and social media--tend to develop a stronger sense of trust over time. So, engagement may not always be clearly visible, but it works gradually in the background. Over time, it builds familiarity, and that familiarity often turns into loyalty without the consumer even realizing it fully.

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Consumer Engagement, Brand Loyalty, FMCG Sector, ITC Limited, Consumer Behavior, Brand Trust, Customer Experience

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"From data to practice: A study on contextual hurdles in HR analytics adoption", it is an empirical study, in today's digital and mass media communication era, Human Resource Analytics in organization it develop as an essential tool for evidence-based decision-making in HR practices such as, Recruitment, Performance appraisal management, and retention, compensation etc. but yet it is facing a significant challenge in adoption of these analytics, mainly in developing the HR analytics and economies such as India. This is grounded in an open system theory, TOE framework, Change management perspectives, and Resource based view. This study particularly focus on examining the organizational technological, and environmental challenges to implement the Human Resources Analytics. This research address the essential key objectives such as, assessing impacts of change in management, identifying the data quality, and mainly leadership roles, by analysing all of these objectives and the adoption of HR analytics. This is a Quantivative information collected through survey and collected the responses of 72 HR employees from different industries or organization, by using a structured questionnaire in google form and used various scales like Likert, Multiple choice, Ranking and rating scales, and the data analysed by using frequency distribution, tables and graphs of percentage (pie charts). From findings which shows that there is (79.2%) high adoption of Human Resource Analytic tools, and effectively utilizing the insights in decision making (87.5%, on the other hand the challenges like 47.2% is sufficient and moderately using analytical skills, there is budget constraints around 45.8%, the quality of data to using analytical tools is an issue it is around (66.7%) in frequent, change resistance is 38.9% and leadership inconsistency in organization is 45.8%. there is a dominance of IT sector which underscores the tech-driven progress, there is a strong cross departmental collaboration and coordination is around 41.7%. This data focusses on the study which bridges the gap between the Human Resource Analytics adoption and practice, this study also highlights the need for enhancing the skills and the commitment of the leadership in organization to overcome the hurdles in HR Analytics adoption in industries.

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(HRA) Human Resource Analytics, Hurdles in adoption of HRA, Open system Theory, Data quality, Organizational readiness, HR practitioners, TOE framework, Resistance to change management.

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The ongoing conflict involving Iran has intensified concerns about global energy security and regional stability. For India, a major energy-importing country, the consequences are immediate and wide-ranging. Disruptions in supply routes, especially through the Strait of Hormuz, have raised concerns about fuel availability, price volatility, and broader economic pressure. This paper examines the impact of the Iran conflict on India across multiple dimensions, including energy security, domestic economy, agriculture, trade, and foreign policy. It argues that while India faces structural vulnerabilities due to its dependence on external energy sources, it continues to respond through diversification, diplomatic balancing, and strategic planning. The study highlights the need for long term resilience in energy and foreign policy to manage such external shocks

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Iran Conflict, India, Energy Security, LPG Crisis, Foreign Policy, Strategic Autonomy, Economy Introduction

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Polycystic Ovary Syndrome (PCOS) is a prevalent endocrine disorder affecting women of reproductive age, with significant implications for physical and psychological well-being. This study aims to assess the attitude towards PCOS among young women in Tamil Nadu and to examine its association with selected socio-demographic and clinical factors. A descriptive research design was adopted for the study. Data were collected from women aged 18-35 years across selected districts of Tamil Nadu using a non-probability convenience sampling method. A semi-structured questionnaire was used to assess socio-demographic characteristics and attitudes related to PCOS. The findings show that attitudes towards PCOS are varied, with nearly one-third (34.9%) of respondents demonstrating low attitude, while 32.5% each showed moderate and high levels. The majority (75.9%) of respondents belonged to the 21-25 years age group, and the vast majority (85.5%) were unmarried. More than half of the respondents were postgraduates (57.8%) and students (59.0%). Further inferential analysis using non-parametric tests indicated that there were no statistically significant differences in attitude scores across most socio-demographic variables. However, significant differences were observed with respect to clinical diagnosis of PCOS, irregular menstrual periods, and experience of hair thinning or hair loss (p < 0.05), indicating higher attitude scores among affected respondents. Overall, the findings highlight the need for targeted awareness programs focusing not only on improving knowledge but also on shaping positive attitudes towards PCOS. Incorporating peer support and experiential learning approaches may further enhance attitude change and promote better health outcomes among young women.

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Polycystic Ovary Syndrome, awareness, attitude, young women

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This research paper presents an integrated analysis of society, poverty, religious beliefs, and human crisis, mainly focusing on the selected poems of Jayanta Mahapatra. Many of his poems were written in different contexts, but there is a deep underlying connection between them, which clearly shows the real tumultuous condition of Indian society. The poem "Dawn at Puri" primarily talks about the poverty, death, and devastating condition of Indian society hidden behind the holy places. Religious faith fails to eliminate human sufferings completely. Another poem, "Hunger," deals with the extreme poverty and the moral degradation where human relationships cannot survive. The term "hunger" has multidimensional meanings portrayed by the writer. On the other hand, the poem "Indian Summer" reflects the feelings of human conflict, fatigue, and emptiness through the scorching heat and stagnant environment of nature. Mahapatra raises deep social, moral, and philosophical questions through his poetic ways and beautiful imagery. In his poems, nature plays a major role as not only just a backdrop but also a symbol of the mental and social condition of humanity. At the same time, he confronts the reader with moral questions by pointing out the limitations of religious beliefs and the brutal reality of poverty. As a result, these three poems together give a complete picture that shows the complexity of modern Indian society and the deep problems in human life.

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Integrated, Poverty, Crisis, Society, Human life

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This project provides an effective solution to replace the traditional manual switch-based system with an advanced voice-controlled home automation system. The system is designed to reduce manual work and save time by enabling users to control household appliances through voice commands. It eliminates the need for physical interaction with switches and provides a more convenient and efficient way of managing home devices.By using Internet of Things (IoT) technology, this system ensures fast communication and allows users to control appliances from anywhere in the world. In this project, we have developed a Voice-Controlled Home Automation system that is automatic, user-friendly, and highly reliable. The system continuously waits for voice commands from the user through a smartphone or voice recognition module. Once the command is received and processed, the system performs the required action, such as turning devices ON or OFF. The user can control and monitor home appliances remotely, which reduces effort and improves accessibility, especially for elderly and disabled individuals. This system also helps in saving energy by allowing efficient control of devices. Overall, the voice-controlled home automation system enhances comfort, efficiency, and modern living by providing a smart and intelligent way to manage home appliances .

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Voice-Controlled Home Automation Internet of Things (IoT) Smart Home System Voice Commands Automation Remote Control Home Appliances Wireless Communication Smartphone Control Voice Recognition Energy Efficiency User-Friendly System Modern Living Smart Technology Accessibility (Elderly & Disabled Support) Time Saving Convenience Intelligent System

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The rapid expansion of Internet of Things (IoT) systems has led to increased demand for intelligent, energy-efficient, and scalable solutions for real-time monitoring and anomaly detection. Traditional cloud-based architectures suffer from high latency, excessive energy consumption, and network dependency. This paper proposes an energy-aware anomaly detection system based on Tiny Machine Learning (TinyML) deployed on an ESP32 microcontroller. The system utilizes MPU6050 sensor data to detect vibration anomalies and employs a lightweight TinyML model for local inference. To reduce communication overhead, LoRa (RA-02 SX1278) is used to transmit only relevant anomaly data over long distances with minimal power consumption. Additionally, a TP4056 battery management module is integrated to ensure efficient energy utilization and portability. The proposed system demonstrates the effectiveness of edge-based intelligence in reducing energy consumption and improving real-time performance. A Python-based dashboard is developed for visualization, displaying time-series data, anomaly status, and historical records. Furthermore, a conceptual implementation of federated learning is introduced, where multiple nodes operate independently and share summarized insights instead of raw data. The results show that the system significantly reduces unnecessary data transmission while maintaining reliable anomaly detection, making it suitable for energy-constrained IoT applications.

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TinyML, IoT, ESP32, LoRa, Anomaly Detection, Edge Computing, Energy-Aware Systems, Federated Learning

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semantic segmentation; TRT-ViT; MixBlockC; Vision Transformers; TensorRT; Cityscapes; OHEM; real-time inference; hybrid CNN-Transformer; Semantic FPN.

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The rapid growth of digital media has made it easier to find information, but it has also made it easier for fake news and misinformation to spread, which is a major threat to public discourse. At the same time, predicting how popular news articles will be is important for understanding how users interact with content and how it spreads. In this paper, we created a new dual-task machine learning framework that uses both textual content features and user engagement metrics to find fake news and predict how popular news will be. We used Natural Language Processing methods, specifically TF-IDF vectorization, to get useful representations from news headlines. We also added user-focused features like past behavior, engagement patterns, sentiment analysis, and source reliability to make the credibility assessment more accurate. We used Support Vector Machine (SVM) to tell the difference between real and fake news and Random Forest to guess how popular something will be. We developed a web interface where users can input news headlines and engagement metrics to receive real-time fake news detection and popularity predictions. Experimental results demonstrate that our approach achieves superior performance compared to traditional content-based methods, validated through confusion matrices and standard classification metrics.

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Fake News Detection, News Popularity Prediction, TF-IDF, SVM, Random Forest, NLP, User Engagement

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Focal fibrous hyperplasia (FFH), also known as irritation fibroma, is a common benign reactive lesion of the oral cavity caused by chronic irritation such as cheek biting, sharp teeth, or ill-fitting dental appliances. It typically presents as a painless, slow-growing mass and is most commonly seen on the buccal mucosa, tongue, or gingiva. These lesions are non-neoplastic in nature and arise as a response to repeated trauma. This case report describes a patient with a gradually enlarging, asymptomatic gingival growth. The lesion was surgically excised, and histopathological examination confirmed the diagnosis of focal fibrous hyperplasia. The patient showed good healing with no recurrence on follow-up. This case highlights the importance of early diagnosis, removal of the source of irritation, and simple surgical management for successful treatment.

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In the contemporary digital age, students are increasingly exposed to smartphones, social media, and online entertainment, which significantly influence their academic performance. Excessive screen time often leads to distraction, reduced concentration, and poor study habits. This study aims to examine the impact of a structured digital detox program on students' academic performance. An experimental research design was adopted with a sample of 60 undergraduate students divided into experimental and control groups. The experimental group participated in a 7-day digital detox intervention, while the control group continued their regular digital usage. Pre-test and post-test scores were compared to analyze the effect. The results indicate a significant improvement in academic performance, concentration, and study habits among students who underwent digital detox. The study highlights the importance of digital discipline in educational settings and suggests integrating digital detox strategies into academic practices.

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Digital Detox, Academic Performance, Screen Time, Students, Experimental Study, Higher Education.

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Education is a powerful tool for changing society. In the century India had a lot of social problems like caste hierarchy, patriarchy and religious orthodoxy. At that time educating women and lower-caste groups was an idea. Savitribai Phule was one of the people to challenge these social problems through education. She started a movement with her husband Jyotirao Phule to make education accessible to women, Dalits and other marginalized communities. Savitribai Phule opened one of the modern schools for girls in India in Pune in 1848 and played a key role in spreading literacy among socially excluded groups. Her work laid the foundation for an educational revolution that questioned traditional norms and emphasized equality, dignity and social justice. She also worked against evils like child marriage, caste discrimination and the denial of education to women. Through initiatives like night schools for laborers and shelters for widows and abandoned children Savitribai Phule showed that education can be a tool for empowerment and reform. Today even though we have made a lot of progress in literacy and educational access issues like gender inequality, caste discrimination and socio-economic disparities still exist in our systems. The ideas and practices introduced by Savitribai Phule are still very relevant in addressing these challenges. Her vision of inclusive socially conscious education aligns closely with modern educational policies and global goals like universal education and gender equality.

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Educational Reform, Women's Education, Social Justice, Inclusive Education, Gender Equality, Educational Revolution in India.

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Swargadham Sevak Sangha, situated in the Khagra locality of Berhampore in Murshidabad district, West Bengal, represents a significant example of Barowari socio-cultural organization that contributes to the formation of regional identity. This study examines the multifaceted role of the Sangha, not only as a prominent organizer of Durga Puja but also as an influential institution shaping local socio-cultural life. Emerging within a region historically associated with Nawabi culture and artistic traditions, the Sangha has evolved from an informal collective into a structured organization that integrates religious practices with broader social responsibilities. Adopting a qualitative historical methodology, the study draws upon archival records, secondary literature, news sources, and field-based observations to trace the institutional development of the Sangha. Particular attention is given to its engagement with traditional artisan communities, especially the Pal sculptors, in preserving the distinctive Murshidabad style of idol-making. The research also highlights the Sangha's sustained commitment to seva (selfless service), encompassing welfare initiatives that function as an informal social support system for the local population. The findings demonstrate that Swargadham Sevak Sangha operates beyond the confines of a religious body, serving as a platform for cultural expression, social cohesion, and civic participation. By linking ritual practices with community-oriented activities, the Sangha plays a crucial role in sustaining the syncretic cultural heritage of Murshidabad. The study concludes by addressing the challenges faced by such grassroots institutions in the context of globalization and digital transformation, while affirming their continued relevance in fostering collective identity and social responsibility.

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Swargadham Sevak Sangha, Barowari, Murshidabad, socio-cultural organization, seva

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Memory, reasoning, and behavior are all impacted by dementia, a degenerative brain disorder that primarily affects older persons. Early on, it is frequently undetected, which reduces the effectiveness of subsequent treatment. In order to control symptoms and enhance quality of life, early detection is essential. Cognito Track is an AI-based system that uses passive tracking of users' interactions with smart devices, such as voice assistants, tablets, and smartphones, to identify early indicators of dementia. It detects minute alterations in speech hesitancy, typing speed, navigation habits, and routine modifications. In order to identify anomalies over time, these patterns are transformed into relevant data and examined using machine learning models like Transformers and LSTMs. User data never leaves the device because to the system's usage of on-device processing and federated learning Cognito Track can notify users or caregivers in advance, facilitating prompt medical attention and promoting preventive digital healthcare, by creating a personal behavior baseline and detecting deviations.

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AI, Dementia Detection, Cognitive Monitoring, Smart Devices, Behavioral Analysis.

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