Category Archives: Uncategorized

Authors: Dr. Rishabh Bhardwaj, Iram Khan, Ms. Meenal Maan

Abstract: Heavy metal contamination in agricultural soils has become a major environmental concern due to its adverse effects on soil quality, crop productivity, and human health. The present study focuses on the quantitative analysis of heavy metals in agricultural soil samples collected from selected locations. Metals such as lead (Pb), cadmium (Cd), chromium (Cr), nickel (Ni), zinc (Zn), and copper (Cu) were analyzed using standard analytical techniques. Soil samples were collected, air-dried, sieved, and subjected to acid digestion followed by analysis using Atomic Absorption Spectroscopy (AAS). The results indicated variation in heavy metal concentrations across different sampling sites, reflecting the influence of anthropogenic activities such as fertilizer use, wastewater irrigation, and industrial emissions. Some metals were found near or above permissible limits, indicating localized contamination. Statistical analysis revealed correlations among metals, suggesting common sources. The study highlights potential environmental and health risks associated with heavy metal accumulation and emphasizes the need for sustainable soil management and regular monitoring.

DOI: https://doi.org/10.5281/zenodo.19677896

 

Published by: vikaspatanker

Authors: Ganapathy T, Thirumalai T, Anbarasan A J

Abstract: The Real-Time Visual Crowd Guidance System for Railway Stations is a smart safety and passenger management solution developed using Python and ESP32 with serial communication. A camera connected to the Python system continuously monitors the crowd near each train compartment and analyzes the density in real time using computer vision techniques such as OpenCV-based people detection. Based on the crowd level, the Python application sends serial commands to the ESP32, which controls the red, yellow, and green LEDs, buzzer, and LCD display to guide passengers. When the crowd is high, the red LED glows, buzzer alerts, and the LCD displays “Move to Next Compartment”; for moderate crowd, the yellow LED indicates caution; and for low crowd, the green LED with the message “You Can Enter” is shown. This system helps reduce congestion, improves passenger flow, and enhances safety in railway stations during peak hours through real-time visual and audio guidance.

DOI: https://doi.org/10.5281/zenodo.19676460

 

Published by: vikaspatanker

Authors: M. Saicharan, K.Hari Krishna, J. Krishna, Dr M.Sri Suresh

Abstract: A 2 kW Hybrid Microgrid with PV, Wind Turbine and BESS: Design, Modeling and Simulation. In this paper, design, modeling and simulation of a 2 kW hybrid renewable energy microgrid having solar PV, wind turbine generation and BESS are presented. Perturb and observe (P&O) MPPT algorithm is adopted for PV subsystem whereas dynamic wind speed model is used for wind turbine. In this model, a Fuzzy Logic Controller (FLC) controls the power flow between battery, load, grid, and renewable sources in real time. The DC link is connected to AC grid through a three-phase inverter and transformer. Simulation results in MATLAB/Simulink indicate that the proposed system can supply steady 2 kW load with proper battery charge/discharge control and it doesn't need a lot of grid power. The proposed system can find applications in rural electrification, isolated communities, and smart grid installations.

DOI: https://doi.org/10.5281/zenodo.19675652

Published by: vikaspatanker

Authors: Pratik Halnor, Om Kale, Vishal Gore, Abhishek Kahar, Devyani Jadhav

Abstract: Retrieval-Augmented Generation (RAG) improves the factual accuracy of Large Language Models by grounding responses in external documents. However, most existing systems rely on dense em-beddings, vector databases, and GPU-based computation, making them unsuitable for low-resource environments. This paper presents a lightweight RAG system designed specifically for CPU-only environments. The system integrates PDF text extraction and Optical Character Recognition (OCR) using PyMuPDF and Tesseract, followed by a keyword-based retrieval mechanism. The retrieved context is then passed to a language model API for response generation. Experimental evaluation demonstrates that the system achieves an accuracy of 83.3% with an average response time of approximately 2.2 seconds. The results highlight that efficient document intelligence systems can be developed without heavy computational requirements

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Authors: Amit Gupta, Mohammad Mokarram Siddiqui, Kaminee Pachlasiya, Santoshi Kharal

Abstract: To address these challenges, this study proposes a Service Provider & Job Seeker Ap-plication, a digital platform designed to connect customers directly with skilled workers through a centralized and interactive system. The application enables service providers to register, create professional profiles, and showcase their skills, while customers can search, compare, and hire workers based on ratings, location, and availability.The system architecture is built using modern technologies such as React Native for frontend development, Node.js with Express for backend services, and MongoDB/MySQL for data storage. It incorporates essential features such as realtime booking, secure digital payments, notifications, and a rating system to ensure trust and transparency.Unlike traditional service models, the proposed system not only simplifies the hiring process but also enhances employment opportunities for skilled workers by providing them with a digital platform. Additionally, features like role-based access control, real-time updates, and analytics improve system efficiency and scalability.Overall, the application the gap between service seekers and job seekers, promoting digital transformation and improving accessibility in the service industry.

DOI: https://doi.org/10.5281/zenodo.19675217

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Odimgbe Ezekiel Izuu
Affiliation	Graduate Assistant, Industrial Chemistry Department .
Email-Id:	easyodimx@gmail.com
Publication: Odimgbe Ezekiel Izudike, Clark Poro David, Olubunmi Abiola Adewusi, Akpanuko Mary Emmanuel, Apuyor Stanley Ejohwomu, Onwugbuta Godpower Chukwuemeka,  Ikechukwu Sampson Chikwe and Erienu Obruche Kennedy (2026). Modification of Coconut Shell Activated Carbon With an Azo Ligand (Ddptp) For Enhanced Removal Of Pb²⁺ From Contaminated Water. FUDMA Journal of Sciences (FJS), 10 (2): 284 – 293. Akacha Joshua Richard, Oladosu Micheal Abimbola, Moses Adondua Abah, Oderanti Mustapha Olayemi, Agbanigo Bolade Sunday, Imade Blessing, Shinggu Paula Paul, Akinbolawa Olujimi Adeolu, Okabeonye Sunday Agbo, Inyam Benjamin Izang, Odimgbe Ezekiel Izudike , Philemon Onyejeme Chimere, Igwe Ejikeme Peter. (2025).The Effect of Cefuroxime on Aquatic Macrophyte (Lemna Minor) and Algae (Scenedesmus Sp.). Journal of Medical Discoveries, RPC Publisher, 2(1): 1 – 15. Moses Adondua Abah, Micheal Abimbola Oladosu, Sulaiman Luqman Olaitan, Leah Eneotse Adayi, Silas Verwiyeh Tatah,  Ochuele Dominic Agida, Okocha Jennifer Uchenna, Ibrahim Ayinla Mahmud, Odimgbe Ezekiel Izudike, Ridwan Musa, Najamu Yau, and Okpanachi Nuhu Oyibo (2025). Advanced Oxidation Processes for the Degradation of Organic Pollutants in Wastewater. Environmental Sciences and Ecology: Current Research (ESECR), 6(1): 1 – 7. Kehinde Sowunmi; Oladosu Micheal Abimbola; Moses Adondua Abah; Luqman Olaitan Sulaiman; Odimgbe Ezekiel Izudike; Ugwah Jiata Ekele; Dele-Osibanjo Taiwo A; Olowookere Adepeju Kafayat; Adewale Femi Emmanuel; Julius Sarah Oluwaseun; Nnametu Peter Onyedikachukwu; Agbanigo Bolade Sunday; Tobi David Farinde; Olutayo Nathaniel Farinde; Kelechi Asogwa; Taiwo Awojulu; Sunday Ameh (2025). Green Synthesis, Photo-Physical Characterization, and Evaluation of in-vitro Antioxidant, Anti- Inflammatory, and Antidiabetic Properties of Selenium Nanoparticles Derived from Nigella Sativa seeds. Journal of Nanomedicine, 8(1): 1 – 6. Micheal Abimbola Oladosu, Moses Adondua Abah, Ezekiel Izudike Odimgbe3, Femi Emmanuel Adewale, Clinton Arthur, Abiola Samuel Ajayi, Joseph Ezeani, Franklin Ogonna Ede, Olaide Ayokunmi Oladosu, Emmanuella Chidimma Ohanele (2026). Smart Electrochemical Sensors and Iot For Monitoring Heavy Metals in Nigerian Water: Review Of Advances And Deployment Challenges. Trends in Ecological and Indoor Environmental Engineering, 4(1), 79–89.

Published by: vikaspatanker

Authors: R.Ranjith, S.Sudhakar, A.Adhithya, Dr. T. Sengolrajan

Abstract: This project develops a wirelessly connected hair drying system that automatically adjusts airflow speed based on real-time hair moisture detection through integration with existing hair dryer units. The system employs ESP32 microcontroller as the central processing unit with built-in Wi-Fi capability for cloud connectivity and mobile application interface. Capacitive moisture sensors continuously monitor hair wetness levels and transmit data to the ESP32 which processes the information through adaptive algorithms. DS18B20 temperature sensors monitor thermal output while solid-state relays control the heating element through PWM signals. Motor speed regulation utilizes to modulate AC motor performance across three operational levels high speed for very wet hair conditions, medium speed for moderately damp hair and low speed for nearly dry hair conditions. The touch control interface integrates mounted on the dryer surface for manual operation while the mobile application communicates through Firebase cloud platform enabling remote parameter adjustment. An OLED display module presents real-time operational data including moisture levels and temperature readings. The integration process involves mounting the moisture sensor near the dryer nozzle, installing temperature sensors adjacent to heating elements and housing the ESP32 module within the dryer handle.

DOI: https://doi.org/10.5281/zenodo.19675047

Published by: vikaspatanker

Authors: Mrs. S. Revathi, M. Aarthi Sree, N.Deepika, K.Rajalakshimi

Abstract: Medication management plays an important role in maintaining good health, especially for elderly individuals and patients undergoing long-term treatment. Forgetting medication times or improper organization of medicines can lead to serious health issues. A smart medicine box is developed to assist users in managing daily medication schedules in an efficient and reliable manner. The system operates using a microcontroller (Arduino) integrated with a real time clock to monitor predefined medication timings and generate timely reminders. Multiple medicine compartments are provided to store different medicines separately, reducing the chances of confusion and incorrect usage. Visual and audio alerts notify users at scheduled times, ensuring regular intake of medicines. The system also monitors medicine availability and provides alerts when medicine levels become low, helping users refill medicines on time. Simple controls and a user- friendly interface make the system suitable for home use without requiring technical knowledge. The smart medicine box enhances medication adherence, improves patient safety, and reduces dependence on caregivers. Such a system is especially useful in households with elderly people and patients requiring continuous medication, offering an effective solution for organized and timely medicine management.

DOI: https://doi.org/10.5281/zenodo.19672584

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Authors: Jiya Bhatt, Manthan Khopkar

Abstract: Digital surveillance has emerged as an integral feature of governance in contemporary India. The desire for national security, prevention of crime, distribution of welfare services, and administrative efficiency has prompted the Indian state to increasingly adopt digital technologies in the areas of governance. The rapid expansion of digital technologies such as biometric technologies, facial recognition technologies, and extensive communication interception technologies has enabled the Indian state to increasingly use digital surveillance. The use of such technologies has not only provided efficiency in governance but has also posed significant challenges to civil liberties such as the right to privacy, freedom of expression, and the right to due process. The paper seeks to examine the evolution of digital surveillance in India, the constitutional basis of digital surveillance in India, and the implications of digital surveillance on civil liberties in India. The paper seeks to examine the implications of digital governance in India on the constitutional values of a democratic society. The paper seeks to examine the implications of digital governance in India on the constitutional values of a democratic society. The paper seeks to examine the implications of digital governance in India on the constitutional values of a democratic society.

DOI: https://doi.org/10.5281/zenodo.19672251

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Authors: Babandi Usman, Salim Ahmad, Zahraddeen Safyanu

Abstract: Student academic failure remains a persistent challenge in higher education, particularly in developing countries where late identification of at-risk students limits timely intervention. Recent advances in Educational Data Mining and Learning Analytics have enabled predictive modelling of student performance; however, many existing models suffer from poor interpretability, data imbalance, and limited integration of behavioral and socio-economic variables. This study presents a comprehensive review and synthesis aimed at guiding the development of an enhanced algorithm for student failure rate analysis. A systematic review methodology was employed, involving structured literature collection, screening, categorization of predictive techniques, and comparative analysis of statistical, machine learning, ensemble, and deep learning approaches. Algorithms were evaluated using established performance metrics including accuracy, precision, recall, F1-score, and ROC-AUC, alongside qualitative criteria such as interpretability, scalability, and real-time applicability. The analysis reveals that while ensemble and deep learning models achieve superior predictive accuracy, they often lack transparency and struggle with imbalanced educational datasets. Based on these findings, the research proposes a hybrid and explainable predictive framework that integrates ensemble learning, neural networks, imbalance-handling techniques, and explainable AI methods. The review demonstrates that hybrid approaches provide the most promising balance between accuracy, interpretability, and early detection capability. The major contribution of this research lies in synthesizing fragmented literature into a unified framework for enhanced student failure prediction, identifying critical research gaps, and establishing a methodological foundation for developing a scalable, interpretable, and real-time predictive system to support data-driven academic interventions.

DOI:

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