Volume 14 | Issue 6

 Abstract

Farmers often rely on intermediaries to sell their produce, which reduces their profits and limits their access to larger markets. A web-based digital marketplace enables direct interaction between farmers and buyers, ensuring fair pricing, greater market reach, and transparent transactions. The platform streamlines agricultural trade, reduces supply chain inefficiencies, and helps farmers increase their income while providing buyers with fresh produce at competitive prices. The Farm Management System is a web-based platform designed to digitize and streamline the process of managing farmer information and agricultural products. The system allows users to register, log in securely, and perform key operations such as adding, viewing, editing, and deleting farmer records. Additionally, users can manage agro products by uploading details such as product name, description, and price. The application ensures secure access through an authentication module and maintains transparency with a trigger logging system that records significant actions within the platform. The backend is powered by a MySQL database, integrated through SQLAlchemy ORM in Flask, which handles data storage for users, farmers, farming types, products, and system logs. The use of Flask as the web framework ensures a lightweight, modular, and scalable architecture. The system provides a responsive web interface for ease of use and supports administrative tasks with functionality to manage different farming types and monitor user activity. This system is particularly beneficial in agricultural sectors for maintaining organized and accessible digital records, promoting efficiency, and reducing manual workload. It serves as a foundational tool for smart farming practices and can be expanded in the future with analytics, mobile access, and AI-based crop recommendations.

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 Keywords

MySQL, SQLAlchemy ORM, Farm Management System, AI-based crop recommendations

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वैश्वीकरण के वर्तमान दौर में, जहाँ भू-राजनीतिक तनाव और सांस्कृतिक रूढ़िवादिता वैश्विक शांति के लिए चुनौती बनी हुई है, सांस्कृतिक पर्यटन एक शक्तिशाली पुल के रूप में उभरा है। प्रस्तुत शोध पत्र "सांस्कृतिक पर्यटन" को केवल एक आर्थिक गतिविधि के रूप में न देखकर, वैश्विक शांति और अंतर-सांस्कृतिक संवाद को बढ़ावा देने वाले एक उत्प्रेरक के रूप में विश्लेषित करता है। इस अध्ययन का मुख्य उद्देश्य यह समझना है कि किस प्रकार विभिन्न समुदायों की विरासतों, परंपराओं और जीवन शैलियों का प्रत्यक्ष अनुभव, वैश्विक नागरिकों के बीच आपसी समझ को गहरा करता है और पूर्वाग्रहों को कम करता है।हालाँकि इस प्रक्रिया के विश्लेषणात्मक अध्ययन में उन चुनौतियों को भी नजरअंदाज नहीं किया जा सकता जो सांस्कृतिक पर्यटन के अति-व्यावसायीकरण या 'सांस्कृतिक आघात' के कारण उत्पन्न होती हैं। कई बार पर्यटकों के अनियंत्रित व्यवहार से स्थानीय समाज में सांस्कृतिक प्रतिरोध भी देखने को मिलता है। इसलिए, यह शोध पत्र न केवल पर्यटन के सकारात्मक पक्षों की सराहना करता है बल्कि एक संतुलित समाजशास्त्रीय दृष्टिकोण अपनाते हुए यह भी रेखांकित करता है कि कैसे 'जिम्मेदार पर्यटन' के माध्यम से इन द्वंद्वों को कम करके 'अंतर-सांस्कृतिक संवाद' को वैश्विक शांति का एक अचूक उपकरण बनाया जा सकता है।

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सांस्कृतिक पर्यटन, वैश्विक शांति, अंतर-सांस्कृतिक संवाद ,सतत पर्यटन, सांस्कृतिक विविधता, सांस्कृतिक पारस्परिकता ,जन-कूटनीति,सांस्कृतिक संकीर्णता|

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This article sees the issue of MHM from a humane angle. It opens up with the judgment of the Supreme Court (SC) on MHM as Right to Life under the article 21. It touches upon the key issues related to MHM from the SC point of view.

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SC, MHM, ARSH, WASH, RHRL, RAE, RTE

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Conventional bituminous surface courses in pavements are getting damaged easily. They suffer from deformation, fatigue cracking and thermal distress. This happens because of increasing traffic loads and extreme weather conditions in places like Maharashtra, India. At the time disposing of old tyres is a big environmental problem. This study checks if waste tyre crumb rubber (CRM) can be used to improve concrete surface course mixes. CRM is used to replace VG-30 bitumen in the mixes. The mixes are prepared using the process of modification. The base VG-30 bitumen was first tested as per IS 73:2013. It was found to be within all limits. The Optimum Bitumen Content (OBC) was found to be 5.4% by weight of mix. This was done using Marshall mix design. CRM-modified specimens were then made at four levels: 10% , 12.5% , 15% , 17.5% These levels are based on the weight of bitumen. The specimens were tested for Marshall Stability, Flow Value and Bulk Density as per IS 17127:2019. The results show that as CRM content increases: Penetration reduces , Softening point and flash point increase This means that the binder becomes stiffer. It also becomes more thermally stable and safer to handle. Among all tested levels 17.5% CRM content gave the performance. It achieved a Marshall Stability of 15.45 kN. This is a 32% improvement over the mix at 11.7 kN. The average Flow Value was 3.58 mm. Both results meet IS 17127:2019 requirements. The 12.5% and 15% CRM mixes had flow values, above the permissible limit of 4.0 mm. The study confirms that waste tyre crumb rubber can be used to improve bitumen. It can be used for surface course applications. This can lead to pavement performance and sustainable waste tyre management.

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Crumb Rubber Modifier (CRM); VG-30 Bitumen; Marshall Stability; Flexible Pavement; Sustainable Pavement; Waste Tyre Recycling; IS 17127:2019; Bituminous Concrete Surface Course

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Broad-spectrum sunscreen, Zinc oxide, Titanium dioxide, Sun Protection Factor, Photoprotection, UVA, UVB, Stability study.

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 Abstract

ಭಾರತ ದೇಶವು ವಿವಿಧ ಸಂಸ್ಕೃತಿಯ ನೆಲಬೀಡಾಗಿದೆ ಹಲವಾರು ಭಾಷೆಗಳಿಂದ ಕೂಡಿದ ಹಾಗೂ ಅನೇಕ ವೈವಿದ್ಯತೆಯಿಂದ ಏಕತೆಯ ನಾಡಾಗಿದ್ದು, ಕಲೆಗಳಿಗೆ, ಮನರಂಜನೆಗಳಿಗೆ ಹೆಸರುವಾಸಿಯಾದ ರಾಷ್ಟ್ರವಾಗಿದೆ. ಭಾರತೀಯ ಸಿನಿಮಾವು ಪ್ರಪಂಚದಾದ್ಯಂತ ಅಕರ್ಷಿಸುವ ವಿಶೇಷ ಮಾಧ್ಯಮವಾಗಿದೆ. ಸಿನಿಮಾ ಸಮಾಜದ ಪ್ರತಿಬಿಂಬ, ಯಾವುದೇ ಕಲೆ ಮತ್ತು ಸಾಹಿತ್ಯ ತನ್ನ ಸಮಕಾಲೀನ ಸಮಾಜವನ್ನು ಪ್ರತಿಬಿಂಬಿಸುವಂತೆ ಸಿನಿಮಾರಂಗವು ಜನಪ್ರಿಯ ಮಾಧ್ಯಮವಾಗಿದೆ. ಸಿನಿಮಾ ಮತ್ತು ಸಿನಿಮಾಗಳನ್ನು ಬಿತ್ತರಿಸುವ ಜಾಹೀರಾತುಗಳು ಸಹ ಸಮಾಜದ ಸಂಸ್ಕೃತಿಯನ್ನು ಹಾಗೂ ಸಮಾಜದ ಆಗು- ಹೋಗುಗಳನ್ನು ಸವಿಸ್ತಾರವಾಗಿ ಚಿತ್ರಸುವ ಕಾರ್ಯಮಾಡುತ್ತದೆ. ಸಿನಿಮಾ ಭಿತ್ತಿಚಿತ್ರ ಜಾಹೀರಾತುಗಳು ಚಿತ್ರಮಂದಿರಗಳಿಗೆ ಪ್ರೇಕ್ಷಕರನ್ನು ಕರೆತರುವಲ್ಲಿ ಮಹತ್ವದ ಪಾತ್ರವನ್ನುವಹಿಸುತ್ತದೆ. ಭಾರತ ಪುರಷಪ್ರಧಾನ ರಾಷ್ಟ್ರವಾಗಿದೆ. ಪುರುಷಪ್ರಧಾನವಾದ ಸಮಾಜದಲ್ಲಿ ಮಹಿಳೆಯರನ್ನು ಸಿನಿಮಾದಲ್ಲಿ ಹಾಗೂ ಸಿನಿಮಾ ಜಾಹೀರಾತುಗಳಲ್ಲಿ ಚಿತ್ರಿಸುವುದು ಏಕಮುಖವಾಗಿದೆ. ಸಾಮಾಜಿಕ ವ್ಯವಸ್ಥೆಯನ್ನು ಪ್ರತಿಬಿಂಬಿಸುವ ಸಿನಿಮಾಗಳಲ್ಲಿ ಲಿಂಗ ವ್ಯತ್ಯಾಸ ಮತ್ತು ಲಿಂಗ ಸಮಾನತೆಗಳು ಅನಿವಾರ್ಯವಾಗಿ ಬೆಸೆದುಕೊಂಡಿರುವುದರಿಂದ ಸಿನಿಮಾ ಪರದೆಯ ಮೇಲೆ ಸ್ತ್ರೀ ಪುರುಷರ ನಡುವೆ ತಾರತಮ್ಯ ಸಮಾನತೆಯ ಸಂಘರ್ಷಗಳನ್ನು ಕಾಣಬಹುದಾಗಿದೆ. ಅದರಲ್ಲೂ ಸಿನಿಮಾ ಭಿತ್ತಿ ಚಿತ್ರ ಜಾಹೀರಾತುಗಳಲ್ಲಿ ಮಹಿಳೆಯರನ್ನು ಹೇಗೆ ತೋರಿಸುವ ರೀತಿ ಲೈಗಿಂಕವಾಗಿ ಆಕರ್ಷಿಸುವ, ಪ್ರಚೋದಿಸುವ ಜಾಹೀರಾತು ಸರುಕಾಗಿ ಮಾರ್ಪಾಡಾಗಿರುವುದು ದುರಂತವಾಗಿದೆ. ಮಹಿಳೆಯರನ್ನು, ಸಿನಿಮಾದ ಪಾತ್ರದಾರಿಯನ್ನು ಚಲನಚಿತ್ರಗಳ ಭಿತ್ತಿಚಿತ್ರ ಜಾಹೀರಾತುಗಳಲ್ಲಿ ಹೇಗೆ ಚಿತ್ರಿಸಲಾಗಿದೆ ಎಂಬುದರ ಬಗ್ಗೆ ಗಂಬೀರವಾಗಿ ಈ ಲೇಖನವು ಬೆಳಕು ಚೆಲ್ಲುತ್ತದೆ. ಇತ್ತೀಚಿನ ಆಧುನಿಕ ಹತ್ತು ಕನ್ನಡ ಚಲನಚಿತ್ರಗಳ ಭಿತ್ತಿಚಿತ್ರ ಜಾಹೀರಾತುಗಳನ್ನು ಮಾದರಿಯಾಗಿ ಪರಿಗಣಿಸಲಾಗಿದೆ, ಈ ಲೇಖನವು ದೃಶ್ಯ ಚಿತ್ರಗಳು ಸಂದೇಶವನ್ನು ಸಂವಹಿಸುವ ಸಂಜ್ಞಾತ್ಮಕ ವಿಧಾನ (ವಿಷುಯಲ್‌ ಸೆಮಿಯೋಟಿಕ್ಸ) ಬಳಸಲಾಗಿದ್ದು, ಈ ವಿಧಾನದಿಂದ ಮಹಿಳೆಯರನ್ನು ಸಿನಿಮಾ ಭಿತ್ತಿಚಿತ್ರ ಜಾಹೀರಾತುಗಳಲ್ಲಿ ಹೇಗೆ ಚಿತ್ರಸಲಾಗುತ್ತಿದೆ ಎಂಬುದರ ಒಂದು ಸಂಜ್ಞಾತ್ಮಕ ಹಿನ್ನಲೆಯಲ್ಲಿ ವಿಶ್ಲೇಷಿಸಲಾಗುತ್ತದೆ.

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ಆಧುನಿಕ ಕನ್ನಡ ಸಿನಿಮಾರಂಗದ ಭಿತ್ತಿಪತ್ರ ಜಾಹೀರಾತುಗಳಲ್ಲಿ ಮಹಿಳೆಯರ ಚಿತ್ರಣ: ಒಂದು ಸಂಜ್ಞಾತ್ಮಕ ವಿಶ್ಲೇಷಣೆ

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The widespread adoption of electric vehicles (EVs) has introduced new challenges for stakeholders ranging from grid operators to EV owners. A critical challenge is to develop an effective and economical strategy for managing EV charging while considering the diverse objectives of all involved parties. In this study, we propose a context-aware EV smart charging system that leverages deep reinforcement learning (DRL) to accommodate the unique requirements and goals of participants. Our DRL-based approach dynamically adapts to changing contextual factors such as time of day, location, and weather to optimize charging decisions in real time. By striking a balance between charging cost, grid load reduction, fleet operator preferences, and charging station energy efficiency, the system offers EV owners a seamless and cost-efficient charging experience. Through simulations, we evaluate the efficiency of our proposedDeepQ-Network(DQN)systembycomparingitwithotherdistinctDRLmethods:ProximalPolicy Optimization (PPO), synchronous Advantage Actor-Critic (A3C), and Deep Deterministic Policy Gradient (DDPG). Notably, our proposed methodology, DQN, demonstrated superior computational performance compared to the others. Our results reveal that the proposed system achieves a remarkable, approximately 18% enhancement in energy efficiency compared to traditional methods. Moreover, it demonstrates about a 12% increase in cost-effectiveness for EV owners, effectively reducing grid strain by 20% and curbing CO2 emissions by 10% due to the utilization of natural energy sources. The system's success lies in its ability to facilitate sequential decision-making, decipher intricate data patterns, and adapt to dynamic contexts. Consequently, the proposed system not only meets the efficiency and optimization requirements of fleet operators and charging station maintainers but also exemplifies a promising stride toward sustainable and balanced EV charging management.I.

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Electric Vehicle (EV) Charging Smart Charging Load Scheduling IoT (Internet of Things) Cloud Computing

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National Education Policy

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National Education Policy

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Creative Commons Attribution 4.0 and The Open Definition

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The National Education Policy (NEP) 2020 and the NIPUN Bharat Mission have firmly established Foundational Literacy and Numeracy (FLN) as the highest educational priority in India's school system. The NIPUN Lakshyas are grade-wise, measurable learning benchmarks for children in Balvatika, Grade 1, and Grade 2, which define the irreducible minimum competencies every child must demonstrate before transitioning to Grade 3. However, a critical challenge in realizing this vision is assessment: the Foundational Stage explicitly avoids formal written examinations, yet systematic monitoring of FLN mastery is indispensable. While several qualitative assessment tools exist, including learning diaries, rating scales, checklists, running records, and observation schedules--this article makes a focused argument for leveraging two tools that are already institutionally established and professionally familiar to every teacher: anecdotal records and student portfolios. Rather than introducing new assessment instruments, the article proposes that these existing tools, when deliberately and systematically aligned with the NIPUN Lakshyas, can serve as powerful, teacher-friendly mechanisms for monitoring FLN compliance in every child. Drawing on empirical research from the past decade and key Indian policy documents, including NEP 2020 and NCF-FS 2022, the article examines how anecdotal records and portfolios can be repositioned from generic developmental documentation tools into targeted FLN compliance trackers--ensuring that no child crosses into Grade 3 without demonstrable mastery of foundational skills.

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NIPUN Bharat Mission, NIPUN Lakshyas, foundational literacy and numeracy, FLN compliance, anecdotal records, portfolio assessment, qualitative assessment, NEP 2020, NCF-FS 2022, Foundational Stage

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The rapid adoption of artificial intelligence (AI) is transforming workplace skill requirements and increasing the importance of continuous learning and workforce upskilling. As organizations seek to develop future-ready employees, understanding workforce learning preferences has become essential for designing effective learning and development strategies. This study aims to examine the underlying dimensions of employees' learning and upskilling preferences in the AI era, identify distinct workforce segments based on these preferences, and analyse demographic differences among the identified segments. A quantitative research design was employed using data collected from 300 employees across various industries. Exploratory factor analysis was conducted to identify the key dimensions of workforce learning preferences, while cluster analysis was used to classify employees into homogeneous groups. Furthermore, analysis of variance (ANOVA) and Chi-square tests were performed to examine differences among workforce segments and their demographic characteristics. The findings revealed four major dimensions of learning and upskilling preferences: AI-related skills, technical skills, soft skills, and career-development learning. Three distinct workforce segments emerged from the analysis, namely AI Enthusiasts, Career-Oriented Learners, and Passive Learners. Significant differences were observed among the identified segments across all learning dimensions. Additionally, workforce segment membership was significantly associated with age, educational qualification, work experience, and industry, whereas gender did not exhibit a significant association.

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Artificial Intelligence, Workforce Upskilling, Employee Learning Preferences, Workforce Segmentation, Human Resource Management.

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In Mamang Dai's The Legends of Pensam (2006), the central concept of pensam--the "in-between"--serves as a critical liminal threshold where myth, history, and modern transition intersect. This paper examines how Adi women navigate this space, confronting a "gendered subaltern" condition shaped by patriarchal customary laws, rigid gender roles, and the restrictive rituals of widowhood. While characters like Pinyar and Omum experience social isolation and the silencing of their lived struggles, this study argues that they are not merely passive victims of their circumstances. Instead, the narrative articulates a profound model of relational agency that challenges Western paradigms. Drawing on Indigenous feminism and cultural memory studies, the paper highlights how this agency is rooted in collective responsibility, intergenerational continuity, and ecological custodianship. As the primary transmitters of oral tradition, women serve as the vital custodians of ancestral knowledge, myths, and rituals that sustain communal identity. Their intimate environmental wisdom--expressed through agricultural practices and healing--redefines power as a life-sustaining responsibility rather than institutional dominance. By centering the roles of these women as storytellers, mourners, and caregivers, Dai's work performs a decolonising act, restoring "narrative visibility" and "symbolic presence" to voices historically relegated to the margins. Ultimately, the paper concludes that Dai redefines Indigenous strength as the capacity to negotiate the threshold of tradition and change, transforming lived silence into a profound form of cultural authority.

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Pensam, Relational Agency, Adi Tribe, Cultural Memory, Gendered Subaltern.

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Creative Commons Attribution 4.0 and The Open Definition

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The present study aims to examine the relationship between Growth Mindset and Psychological Well-Being among prospective teachers. Growth Mindset refers to the belief that intelligence and abilities can be developed through effort, learning, and persistence, whereas Psychological Well-Being represents positive mental health, emotional balance, and life satisfaction. A descriptive survey method was adopted for the study. The sample consisted of prospective teachers selected through a simple random sampling technique. Standardized tools were used to collect the required data. The data were analyzed using descriptive statistics and Pearson's product-moment correlation. The findings of the study revealed that prospective teachers possess a moderate level of Growth Mindset and Psychological Well-Being. Further, a positive significant relationship was found between Growth Mindset and Psychological Well-Being among prospective teachers. The study highlights the importance of fostering a growth mindset in teacher education programs to enhance the psychological well-being of future teachers.

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Growth Mindset, Psychological Well-Being, Prospective Teachers, Teacher Education, Mental Health, Academic Psychology.

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This paper argues that mental health must be treated as a core national priority in India's development trajectory towards 2047. The case is based on three linked propositions: first, the burden of mental illness is not merely a clinical concern but a constraint on human capital, productivity, public safety, social cohesion and constitutional dignity; second, India's present psychiatric infrastructure remains uneven across geography, workforce, institutions, financing and data systems; and third, the country's demographic, technological and federal capacities make a 2047 transformation feasible if mental health is elevated from programme-level delivery to mission-mode governance. Using doctrinal legal analysis, secondary policy review and systems planning, the paper examines India's National Mental Health Survey findings, the Mental Healthcare Act, 2017, the National Mental Health Programme, the District Mental Health Programme, Tele-MANAS and global standards under the WHO Comprehensive Mental Health Action Plan 2013-2030. It proposes a five-tier psychiatric infrastructure model covering community prevention, primary-care mental health, district psychiatric services, regional centres of excellence and national research-surveillance platforms. The paper further recommends a National Mental Health Infrastructure Mission 2047, a dedicated psychiatric workforce pipeline, mental health budgeting norms, insurance-linked continuity of care, school and workplace mental health systems, crisis response services, suicide prevention registries, and enforceable state-level accountability indicators. It concludes that India's goal for 2047 should be not only more hospitals and psychiatrists, but an integrated mental health ecosystem that is rights-based, community-anchored, digitally enabled and institutionally accountable.

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Mental Health, Psychiatric Infrastructure, India 2047, National Mental Health Programme, Tele-MANAS, Mental Healthcare Act 2017, District Mental Health Programme, Public Health Governance, Human Capital.

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Creative Commons Attribution 4.0 and The Open Definition

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Recent advances in deep learning--particularly Convolutional Neural Networks (CNNs)--have opened transformative opportunities for automated object detection and classification in complex outdoor environments. Models from the YOLO (You Only Look Once) family, especially YOLOv8, have emerged as highly effective tools for real-time multi-class detection, offering an optimal balance between inference speed and detection accuracy. Unlike rule-based or template-matching methods, CNN-based architectures learn intricate visual features directly from data, enabling them to adapt to varying lighting conditions, occlusion from vegetation, and complex natural backgrounds [2]. This paper proposes a complete smart farm surveillance framework that combines YOLOv8-based object detection with automated Telegram Bot API notifications. The system processes live video feeds from farm cameras, identifies threats as they occur, captures annotated snapshots, and delivers instant alerts to farmers' smartphones. Key contributions include: o A fine-tuned YOLOv8 detection model trained on a diverse agricultural dataset covering humans, birds, and animals. o An integrated Telegram Bot alerting module providing real-time notifications with timestamped annotated images. o Deployment on resource-constrained edge devices (Raspberry Pi / NVIDIA Jetson Nano) demonstrating practical feasibility. o Comprehensive experimental evaluation under varied farm conditions confirming 94.7% precision and 93.1% recall.

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CNN, YOLOv8, Smart Farming, Object Detection, Telegram Alerts, Agricultural Surveillance, Real-Time Monitoring, Edge Computing, IoT, Deep Learning

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Microfinance has become an important tool for boosting rural economic development by offering financial services to low-income households often left out of the formal banking system. Through microcredit, savings, insurance, and financial education programs, microfinance helps poor households engage in productive activities, create jobs, and improve their living conditions. In India, the Self-Help Group (SHG)-Bank Linkage Program and Microfinance Institutions (MFIs) have greatly increased financial inclusion in rural areas. As of March 2024, over 144.22 lakh Self-Help Groups were connected to banks, with savings exceeding INR65,089 crore. More than 83 percent of these groups were made up of women, highlighting the significant role of microfinance in empowering women. This paper looks at how microfinance contributes to rural economic development, with a focus on reducing poverty, generating employment, developing agriculture, promoting entrepreneurship, and enhancing social empowerment. The study also addresses key challenges in the sector and offers policy recommendations for improving its effectiveness.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Microfinance, Rural Development, Poverty Alleviation, Financial Inclusion, Self-Help Groups, Entrepreneurship, Women's Empowerment

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Heart attack remains one of the leading causes of mortality worldwide, creating a critical need for early prediction and preventive healthcare strategies. HeartIntel: A Machine Learning Framework for Early Heart Attack Risk Prediction and Clinical Decision Support presents an intelligent system designed to identify individuals who may be at elevated risk of heart attack using clinical and physiological parameters. The framework utilizes patient information such as age, blood pressure, cholesterol level, chest pain characteristics, maximum heart rate, ST depression, and related health indicators for predictive analysis. Data preprocessing, feature transformation, and normalization techniques are applied to improve data quality and model performance. Machine learning algorithms including Logistic Regression, Random Forest, and Support Vector Machine are employed for classification and risk assessment. A web based interface enables efficient data entry, prediction generation, and result visualization. Experimental evaluation demonstrates reliable predictive capability, satisfactory accuracy, and timely identification of high risk cases. The system supports clinical decision making, promotes early intervention, enhances healthcare efficiency, reduces diagnostic delays, and contributes to improved patient safety and outcomes.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Heart Attack Risk Prediction, HeartIntel, Machine Learning, Clinical Decision Support, Logistic Regression, Random Forest, Support Vector Machine, Healthcare Analytics, Predictive Modeling, Risk Assessment.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Electrical poles are critical components of power distribution networks, yet faults such as current leakage, conductor breakage, and pole electrification can pose serious risks to public safety and infrastructure reliability. This paper presents ElectroSentrix, an IoT-based intelligent electrical pole fault detection and accident prevention framework designed to monitor pole conditions continuously and respond to hazardous situations in real time. The proposed system integrates voltage sensors, current sensors, an ATmega328 microcontroller, a NodeMCU communication module, an LCD display, and a voice alert unit to detect abnormal electrical conditions and issue timely warnings. Upon fault identification, the framework generates local audio notifications, displays fault information, and transmits alerts to authorized personnel through an IoT platform for rapid maintenance action. Automated monitoring minimizes manual inspection efforts and enhances operational efficiency while reducing the likelihood of electrocution incidents. Experimental implementation demonstrates reliable fault detection, prompt alert generation, and effective communication capabilities. The developed framework offers a cost-effective, scalable, and practical solution for improving electrical pole safety, ensuring public protection, and supporting smarter power distribution infrastructure.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Electrical Pole Safety, Internet of Things (IoT), Fault Detection, Accident Prevention, Smart Monitoring, NodeMCU, ATmega328, Voltage Sensor, Current Sensor, Public Safety.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Underground Cable Fault Detection, Arduino Uno, GSM Module, GPS Tracking, Fault Distance Locator, Power Distribution System, Smart Monitoring, Fault Localization.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

: Road traffic accidents remain one of the major causes of fatalities, injuries, and economic losses worldwide. This project aims to reduce the increasing number of road accidents by developing an AI-powered road safety system that proactively identifies accident-prone zones and provides real-time alerts to drivers. The proposed system utilizes five years of historical accident data (2021-2025) collected across twelve accident-related parameters, including fatalities, grievous injuries, accident intensity, and yearly accident trends. The accident records are mapped to precise geographical coordinates across Pune, Maharashtra, enabling spatial analysis and hotspot identification.The system integrates machine learning and geospatial technologies to improve road safety. K-Means clustering is employed to identify and visualize accident hotspots, achieving an optimal Silhouette Score of 0.5925 with three distinct clusters. Furthermore, an XGBoost classification model is trained using historical accident data from 2021-2023 to predict future accident-prone zones for 2024-2025. Experimental evaluation demonstrates strong predictive performance, achieving an accuracy of 92.08%, precision of 91.84%, recall of 100%, F1-score of 95.74%, and ROC-AUC of 97.78%.To enhance user awareness and safety, the identified accident-prone zones are displayed on an interactive Leaflet.js map as color-coded hotspots. Drivers receive visual alerts and audio notifications through the Web Speech API whenever they approach within a predefined distance of a hazardous zone. The system is further supported by a FastAPI backend and GPS-based location tracking for real-time operation. By combining accident hotspot detection, predictive analytics, and proactive driver alerts, the proposed framework contributes toward safer transportation networks, reduced accident risks, and improved decision-making for both drivers and traffic management authorities.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Accident-Prone Zone Identification, Road Safety, K-Means Clustering, XGBoost, Leaflet.js, Machine Learning, FastAPI, GPS Tracking, Real-Time Alerts.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Attendance management is an essential activity in educational institutions and organizations, where accurate record keeping directly influences administration, monitoring, and performance evaluation. Traditional attendance methods such as manual registers and card-based systems are often time consuming, error prone, and vulnerable to proxy attendance. This paper presents FaceTrack: An Intelligent Vision-Based Attendance Monitoring Framework Using Deep Facial Analytics, a smart attendance solution that automates the identification and recording process through facial recognition technology. The framework utilizes OpenCV for real-time face detection, dlib-based facial feature encoding for identity matching, and a Flask-powered web interface for attendance visualization and management. Captured facial images are processed and compared with stored facial encodings to accurately identify registered individuals and automatically generate attendance records with timestamps. Attendance information is maintained in both CSV files and a MySQL database to ensure reliable storage and easy retrieval. Experimental evaluation demonstrates high recognition accuracy, reduced processing time, and effective prevention of proxy attendance under standard indoor conditions. The proposed framework enhances operational efficiency, minimizes administrative workload, and provides a scalable, contactless, and cost-effective attendance monitoring solution for modern academic environments.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Attendance Management, Face Recognition, Computer Vision, OpenCV, Deep Facial Analytics, Flask, MySQL, Biometric Authentication, Automated Monitoring, Machine Learning.

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Creative Commons Attribution 4.0 and The Open Definition