bluuebunny/crossref_metadata_2025 huggingface dataset:
Tourist valorization of the cultural potential of the Homolje region
Authors: Novović Maja
Published: November 2024

The valorization of the cultural potential of the Homolje region is a key process for the preservation and promotion of its rich cultural heritage. This involves recognizing, respecting and enhancing the value of various cultural elements such as traditions, customs, architecture, art and language. Research in this area shows how it promotes tourism and economic development while preserving cultural identities by using qualitative-quantitative methods and Hilary du Cross' cultural motif valorization methods.The problem of the study of Homolje lies in recognizing and valuing the cultural motifs of the region for the purposes of tourism development. The objectives of valorizing the cultural potential in tourism are reflected in the preservation and promotion of the cultural heritage of Homolje in order to attract tourists, support the local economy and strengthen the identity of the community. The results of the qualitative-quantitative analysis conducted confirm that the cultural motifs of Homolje are characterized as sites of good quality and moderate touristic value. The Hilary du Cros analysis shows a moderate value of the indicators of cultural significance and market attractiveness of the cultural assets. These results indicate favorable conditions for the development of cultural tourism in Homolje, with appropriate monitoring, planning, promotion and protection of the area from possible damage during tourist visits. In addition, the valorization of cultural motifs promotes social cohesion and intercultural understanding. Engaging with the different facets of Homolje's cultural heritage helps individuals realize the importance of intercultural dialog and respect for diversity. Despite important steps, challenges such as limited financial resources and preserving authenticity in tourism remain. Collaboration with local institutions and community involvement are crucial to the success of this process. In essence, enhancing the cultural motifs of Homolje plays a central role in preserving identity, promoting economic growth and improving intercultural understanding.
The development of machine vision and its applications in different industries: A review
Authors: Zhang Lili , Jia Xiaowei , Chang Qing , Liu Xin , Zhang Zhicheng , Cao Yanghao , Liu Junjie , Yang Yizhao
Published: November 2024

In recent years, the development of machine vision research is rapid in several areas. In order to promote the better development of machine vision research, it is necessary to clarify its development and application direction. At present, there are few reviews on the application direction of machine vision. This paper sorts out the application of machine vision in various fields, and summarizes the current application status of machine vision from four main functions: recognition, measurement, classification and detection. This paper mainly introduces the improvement of different algorithms of machine vision and its application in medical, agriculture, manufacturing and other industries, providing guidance for the selection of machine vision research direction.
Financialisation of everyday life: exploring socio economic behaviour in Southern European Countries
Authors: Abalde Nazaret , López-Roldán Pedro , Massó Matilde
Published: November 2024

Despite the growing literature on the financialisation of everyday life, studies that empirically examine the various theoretical approaches to it have been scarce. This paper aims to bridge this gap by analysing the financialisation of individuals’ socio-economic behaviour in Southern Europe. To this effect, we used data from the second wave of the Household Finance and Consumption Survey (HFCS), drawn up by the European Central Bank in 2016. Firstly, we designed an operational model of the financialisation of everyday life based on variables related to individual financial behaviour, household money management, and the perception of economic risk. Secondly, we conducted a Multiple Correspondence Analysis (MCA) combined with a Cluster Analysis (CLA) to study the behaviour of individuals in Spain, Italy, Greece, and Portugal. The results question the financialisation of individual economic action in Southern Europe and point to the characterisation of a heterogeneous pattern of socio-economic behaviour in the region. This paper opens a new methodological and theoretical research agenda, since the literature on financialisation could benefit from our operational model of everyday life financialisation by applying it to further surveys.
A pesar de la creciente literatura sobre la financiarización de la vida cotidiana, los estudios fundamentados empíricamente son muy escasos. Este artículo tiene como objetivo contribuir a la comprensión empírica de este proceso analizando la financiarización del comportamiento socioeconómico de los individuos en el sur de Europa. Para ello, utilizamos datos de la segunda oleada de la Household Finance and Consumption Survey (HFCS), elaborada por el Banco Central Europeo en 2016. En primer lugar, diseñamos un modelo operativo de financiarización de la vida cotidiana basado en variables relacionadas con el comportamiento financiero individual, la gestión del dinero del hogar, y la percepción del riesgo económico. En segundo lugar, realizamos un análisis de correspondencias múltiples combinado con un análisis de clúster para estudiar el comportamiento de los individuos en España, Italia, Grecia y Portugal. Los resultados cuestionan la financiarización de la acción económica individual en el sur de Europa y apuntan a la caracterización de un patrón heterogéneo de comportamiento socioeconómico en el Sur Europeo. Este artículo abre una nueva agenda de investigación metodológica y teórica, ya que la literatura sobre la financiarización podría beneficiarse de nuestro modelo operativo de financiarización de la vida cotidiana aplicándolo a futuras encuestas.
Non-Invasive Measurement of Stress Levels in Knee Using IoT
Authors: S Jayakumar , Rathnam Martin Joel
Published: November 2024

As Knee replacement surgery has become widely prevalent with a high success rate in the short to medium term. However, over the long term, implant degradation may occur due to wear and tear. To address this issue, a potential solution involves using a PIC controller to monitor and compare pressure levels, displayed on an LCD. This system employs a load cell to detect stress, which causes changes in inductance. Additionally, Internet of Things (IoT) technology, through wireless connectivity such as Bluetooth, is integrated with an Android mobile app for continuous monitoring of knee pain based on the weight applied.
Advancing Gender Equality in Higher Education and Research: A Contemporary Perspective
Authors: Manna Adisha
Published: November 2024

Higher education institutions, as key drivers of socio economic transformation, are increasingly positioned as pivotal sites for advancing gender equity and diversity. However, despite these potentials, universities remain inherently “gendered” spaces, where entrenched patriarchal structures perpetuate systemic gender inequalities in representation, career trajectories, compensation, and scholarly practices. This Special Issue critically interrogates the persistent gender disparities within academia, highlighting how institutional and structural norms systematically disadvantage women and gender minorities, with implications that are compounded by neoliberal market logics, gender based violence, and harassment. While Gender Equality Plans have demonstrated some institutional traction, their transformative potential is often constrained by resistance to cultural and structural change. A critical lens on intersectionality reveals the compounded disadvantages faced by marginalized groups, particularly in relation to caregiving responsibilities, racialized identities, and socio economic status. Key themes include the marginalization of gender studies, the neoliberal commodification of academic labour, work life balance, care work, and the impact of gendered labour divisions in academic hierarchies. The findings advocate for systemic reforms that move beyond tokenistic approaches, calling for a radical reimagining of academic culture and policy to address the deeply embedded gendered power structures.
Automatic Opening and Fullness Alert System using IoT
Authors: S Jayakumar , S Srikanth , N Sathya , Tamilarasu Megalathuru , Kousar Neha
Published: November 2024

Rapid urbanization has intensified challenges in waste management, with traditional methods struggling to keep up. Overflowing bins, inefficient collection, and high transport costs are common issues. To address these, we introduce Intell Bin, a smart, connected waste bin system. Intell Bin uses a proximity sensor for contactless access, allowing users to open the bin without touching it. Ultrasonic sensors monitor the bin’s fill level, sending alerts when it reaches capacity. This helps prevent overflow and ensures collections occur only when necessary, reducing unnecessary trips. Intell Bin integrates with a mobile app, allowing remote monitoring and real time notifications for waste management teams. The system also connects to a cloud platform, which aggregates data for optimized collection routes. By leveraging cloud analytics, Intell Bin can reduce transportation costs and fuel consumption. Scalable and adaptable, Intell Bin integrates seamlessly with existing waste management systems. This smart system not only improves efficiency but also reduces environmental impact, making it ideal for modern urban areas.
Smart Property Assistant: Automated Valuation and Legal Advisory System
Authors: S Nellai Sivagami , G Sathya , G Shreya Agarwal , C Pavitra , Pattar Vishwas M , A Abirami
Published: November 2024

The real estate market’s dynamic nature and its dependence on multiple factors create significant challenges in property valuation and legal compliance. This study presents an integrated system that combines automated property valuation with legal advisory services to address the challenges faced by buyers, sellers, and investors. The research focuses on developing a unified platform that provides accurate property valuations while ensuring users understand the legal aspects of real estate transactions. The system leverages machine learning algorithms to analyse property value determinants, including location, market trends, and infrastructure development, delivering accurate and real time valuations. Through an intelligent chatbot interface, the platform provides comprehensive legal advisory services, helping users navigate the complexities of property transactions. This research makes significant contributions by automating the property valuation process and simplifying legal compliance procedures for real estate transactions. Implementation results demonstrate improved accuracy in property valuations and enhanced user understanding of legal requirements. The study transforms traditional real estate decision making by providing a reliable, automated solution that enhances transparency and efficiency in property transactions, ultimately revolutionizing how property valuations and legal advisory services are delivered in the real estate market.
Lithium Battery Management and Monitoring System
Authors: M Suhas , A S Harsha , L S Shankara Reddy , R M Raghavendra
Published: November 2024

The efficient management and monitoring of lithium ion batteries are critical for optimizing their performance, enhancing lifespan, and ensuring safety in various applications, such as electric vehicles, renewable energy storage, and portable electronics. A comprehensive Lithium Battery Management and Monitoring System (BMS) integrates multiple functions, including state of charge (SOC) estimation, state of health (SOH) tracking, temperature regulation, voltage balancing, and protection against overcharge, over discharge, and thermal runaway. This paper presents a novel BMS architecture that incorporates real time data acquisition, intelligent algorithms for SOC and SOH estimation, and advanced protection mechanisms. The system utilizes embedded sensors and microcontroller based circuits to monitor the battery parameters and communicates with external devices through a user friendly interface for data visualization and decision making. Experimental results demonstrate the effectiveness of the system in enhancing battery efficiency, prolonging operational lifespan, and preventing potential failures, making it a robust solution for modern energy storage systems. The proposed BMS provides a scalable, cost effective, and reliable solution for the next generation of lithium battery powered devices and systems.
A Computer Vision-Based Method for Vehicle Speed Detection Using Video Footage
Authors: M M Swedha , S Thenmozhi , K Thrisha , V Varshini , M Malathi
Published: November 2024

The primary objective of this project is to create a web application for vehicle speed detection that will help law enforcement, traffic authorities, and private users measure vehicle speeds correctly from recorded footage. The goal of the project is to develop an affordable, easily usable speed monitoring tool that doesn’t require specialized gear, which will be especially helpful for law enforcement, traffic management, and accident investigation. The approach uses computer vision techniques with Python’s OpenCV module, integrating the Lucas Kanade optical flow algorithm to estimate speed from video data with the Haar Cascade algorithm for vehicle detection. With a user friendly interface that allows users to upload videos and obtain processed results with speed annotations, the system is based on the Django framework for the backend. User credentials and other fundamental data are stored in a database called SQLite, which guarantees data security and accessibility. For converting video formats to accommodate several input types, FFmpeg is utilized. Important findings show that this technology offers accurate speed estimates that are on par with those of specialized speed monitoring devices. The application makes it possible to upload videos, analyzes the film to identify cars, determines their speeds, and shows the user the annotated video. This makes it appropriate for both personal and real world traffic enforcement applications. Important findings show how useful this strategy is in situations where resources are scarce and real time monitoring systems are impractical. In some situations, this approach might be used in place of or in addition to current speed detection techniques, offering a productive, software based substitute for vehicle speed analysis.
ISL(Indian Sign Language) Gesture to Speech with Multilingual Support
Authors: G Fathima , G S Mogan Ram , E Siva Subramanian , V Sasi Kumar , M Mukunda
Published: November 2024

The Real Time Indian Sign Language (ISL) Translator project aims to bridge the communication gap between the deaf and hard of hearing community and the hearing world by leveraging advanced deep learning techniques. This project utilizes Convolutional Neural Networks (CNNs) to recognize the ISL gesture and converts them into text. The recognized text is then translated into speech in multiple Indian languages, allowing seamless real time communication. The system is comprised of three primary components: the Gesture Recognition Module, which employs a CNN to process real time video input of ISL gestures; the Text processing Module, which converts the recognized gesture into structured text; and the Text to Speech (TTS) Module, which translates the test into speech in various Indian languages. An additional Language Selection Module provides users with the option to choose their preferred language for the TTS output. To ensure accessibility and usability, this project integrates a user friendly website interface, enabling individuals to use the translator easily across different platform. By fostering greater inclusion and improving communication in social, educational, and professional settings, the Real Time ISL Translator project stands as a significant technological advancement for the deaf and hard of hearing community in India.
Mental Health Tracker-MHT
Authors: M Yashanth , Balaji Sandeep , S Sidram , Roy Vaibhav
Published: November 2024

The creation and assessment of a mental health tracker intended to make it easier for people to monitor and manage their mental health. Self report surveys, mood logs, and symptom checklists are all integrated into the tracker’s user friendly interface, which enables users to record and evaluate their mental health conditions over time. In order to evaluate usability, engagement, and the effect of consistent tracking on mental health outcomes, we carried out a pilot study with a varied participant base. According to the results, regular usage of the tracker improves communication with mental health specialists, coping mechanisms, and self awareness. This study opens the door for future advancements in mental health by demonstrating how digital technologies may advance mental health literacy and offer useful data to physicians and consumers alike.
Conversational Image Recognition Chatbot
Authors: N Devi Praba , S Kishor Kumar , R Vijay Surya , Melagiri Ananya R , S Vijayaraman
Published: November 2024

This article proposes how to build conversational image recognition chatbot in python using CNN and LLM. We are going to see about building a model using CNN (Convolutional neural network), LLM (Large language model) and how to implement those with traditional chatbot models like encoders, NLP (natural language processor) and decoders. This chatbot able to detect image and answer the queries, it is can provide answer for variety of question asked on images and objects and it can also answer the simple open ended questions. It is a model where an AI agent can hold meaningful dialogue with humans in natural language about a visual content, specifically images.
Dynamic Wireless EV Charging System
Authors: H Thejashwini , Khan Saqlain
Published: November 2024

This project is aimed to design a system that can charge an electric vehicle battery wirelessly when the electric vehicle is in motion. It is similar to wireless charging for mobile the method used in this inductive power transmission. The challenge is applying the wireless inductive power transmission system on roads to generate the vast magnetic field to get the vehicle charged. This technology is claimed to be allowing wireless charging of electric vehicles that have ground clearance up to 18 centimetres. The road uses charging plates that will transfer the power to the vehicles whenever electric vehicles are driven on road. This charging system must and should have coil alignment. Normally the battery charging of an electric vehicle takes a long time so here this charging system can be used and this is a very efficient method to charge the vehicle. The coil alignment and the distance between the coils are important factors for dynamic wireless charging for the electrical vehicle. Key factors for the success of this dynamic wireless charging system include coil alignment and the distance between the coils. Proper alignment ensures optimal energy transfer, while maintaining the correct distance is crucial for effective charging. By integrating this technology into road infrastructure, we can enhance the convenience of electric vehicle usage, reduce range anxiety, and promote the adoption of cleaner transportation options. Overall, this project aims to revolutionize the way electric vehicles are charged, making it a seamless part of everyday travel.
Smart Vending Machine with Auto-Return Mechanism
Authors: Biradar Prajwal D , C K Upendra , K Ravi Prakash , S C Nithin , A Suguna
Published: November 2024

When money is placed in a vending machine a product is automatically dispensed to the consumer. The items available in these machines usually include some snacks such as chips, candies and soft drinks, juices or bottled water. You insert a coin, bill, or a card and press a few keys, and your snack or a drink falls out from the slot ready for you to take it. Furthermore, in many countries, there are vending machines that sell not only pizza, muffins, and French fries but also offer some other items like books. Some even prepare coffee for you while you wait. The advantages of starting a vending machine business are low risk, affordable start up costs and relatively high returns. This is a very straightforward operation with very low operational costs. A wide range of items such as pretzels, drinks, meals that do not need further preparation, and dairy products can be offered. Reports published indicate that a fair return on investment characteristic of this particular industry is roughly 25%. And reducing food waste is important from both an ecological standpoint and for profit performance. Lower waste translates into higher income. It’s safe to say that the vending machine business is pretty much set and established worldwide, and for India, it seems to be in its nascent stages which gives an opportunity to capitalize it. It is a low investment, high return, and low time and labor binding business. Moreover, it is also easy to scale up and gain revenues over the years. For regular returns, vending machines are a good option and if you venture into this line, it might just be for you.
AI-Enhanced Career Guidance System for Personalized Career Pathways
Authors: M Amsa Lakshmi , S K Sankarshan , M Shruthi , H B Niveditha , Ansari Firoj
Published: November 2024

Creating easily available services that connect education and job services is a problem for career counseling in the age of lifelong learning. The use of artificial intelligence to assist with advice in both higher education and the workplace has received very little attention up to this point. The use of artificial intelligence to assist and advance career counseling in higher education institutions is discussed in this study. The findings from focus groups, scenario analysis, and real world experiments are shared, outlining the needs and potential applications of artificial intelligence in career counseling from the perspectives of institutions, guidance personnel, and students. The results show the potential benefits and uses of artificial intelligence in career counseling, along with the obstacles and motivators for using it in order to promote lifelong learning and higher education
Adaptive Learning Management System
Authors: ME Lavanya , G Shiyamala Devi , S Shuba , K Sneha , S Sofiya
Published: November 2024

Adaptive Management Systems (ALMS) are an evolving class of educational technology designed to deliver personalized, data driven learning experiences. Traditional Learning Management Systems (LMS) typically provide static content, offering limited flexibility to adapt to individual learner needs. In contrast, ALMS utilize artificial intelligence (AI) and machine learning algorithms to analyse student data and dynamically adjust instructional materials, pacing, and assessments to better match each student’s unique strengths, weaknesses, and learning preferences. This paper explores the structure and function of ALMS, focusing on key components such as adaptive content delivery, real time feedback, and predictive analytics. By analysing a range of student behaviours including response times, quiz scores, and engagement patterns ALMS can create a tailored learning path that maximizes retention and understanding. This approach aligns with principles of personalized learning, where educational materials and activities are continuously adapted based on individual progress, fostering a more efficient and supportive learning environment. Further, this paper investigates the pedagogical theories and cognitive models that drive adaptive learning, such as constructivist learning theory, zone of proximal development, and scaffolding.
AI-Driven Document Analysis and Interactive Learning Platform with Q and A, Image Search, and Quiz Generation
Authors: A Sarika , A Chethan , S Deepika , K S Channaveera
Published: November 2024

This study explores the development of a machine learning powered educational tool to enhance the accessibility and usefulness of educational materials. The tool uses advanced technologies like Google Gemini artificial intelligence, Google Search Programming interface, Lang Chain, PyPDF2, PDFReader, and Python to create a comprehensive system that allows users to transfer PDF reports, process text, retrieve data from the web, and generate meaningful responses to user queries. The tool’s main goal is to improve the interaction with educational content, making it more intelligent and accessible. System testing, unit testing, utility testing, and execution testing were conducted to evaluate its effectiveness and precision. The results showed a text extraction accuracy rate of over 95% and a 92% accuracy in question responses. Future improvements include a test age feature, improved text extraction calculations, multilingual support, and support for additional file formats.
Urban “Digital Twins” for Smart Cities and Citizens
Authors: C Saranya , K Haripriya , S Bhargava , CM Tejashree , Thomas Joel T
Published: November 2024

Despite the abundance of urban data available and the possibility of improving decision making city administration skills, and infrastructure, contemporary data driven methods for city data based knowledge discovery cannot frequently use collective data. In a loose manner specified elements for data interpretation, or disciplinary discrete analyses of particular datasets make it simple to ignore essential subject knowledge, frequently leading to speculative decisions. Intelligent City Digital twins are intended to get past this obstacle by incorporating analytics and visualization that are more comprehensive approaches to knowledge discovery in real time procedure from diverse city data. Here, we offer a spatiotemporal knowledge discovery framework that integrates social and sensor data and allows for insights from human cognition for the collective exploitation of city data in smart city digital twins. Even though these applications are effective, they frequently use vast quantities of high dimensional and multi domain data to monitor and characterize various urban sub systems. This poses problems in application areas where data availability and quality are restricted, as well as expensive efforts to generate urban scenarios and design alternatives. Generative Artificial Intelligence (GenAI) models are a new field of study in deep learning that has shown promise in producing original material. With an emphasis on several urban sub systems, including building and infrastructure, energy, water, and transportation, this article attempts to investigate the creative integration of GenAI approaches with urban digital twins to address issues in the planning and administration of built environments.
Development of Mini Humanoid Robot for Enhanced Interaction and Assistance
Authors: A Adil Basha , R Spurthi , R Divyashree , S Shreya , K V Dhamarai Selvi
Published: November 2024

This paper presents a prototype artificial intelligence system based on deep learning algorithms aimed at supporting individuals who may struggle with adhering to a balanced routine of meals and hydration. Short term memory challenges can lead to issues like missing meals, overeating, or dehydration, often requiring caregiver oversight to ensure consistency in daily nutrition and hydration. The proposed system leverages artificial intelligence to recognize human activity in video, identifying instances when a person is eating or drinking. It sends audio reminders if a meal or drink was missed or if there was excessive intake, fostering a healthier and more structured routine. Additionally, it enables remote supervision by a caregiver, facilitating easy monitoring and management of the individual’s nutrition program.
Predicting Brain Anomalies in Brain Wave Signals using ML Algorithms
Authors: C Valarmathi , M Avinash , Vikram Poojari
Published: November 2024

The endeavor of predicting brain age and identifying anomalies in brain wave signals represents a significant stride in leveraging machine learning algorithms within neuroscience. With an overarching goal of understanding age related changes in brain structure and function, this research carries profound implications for comprehending cognitive decline and neurological disorders. By harnessing a diverse array of neuroimaging data, spanning from EEG to MRI scans, the study aims to accurately predict brain age while simultaneously delving into the intricate analysis of brain wave signals to detect anomalies. Through the employment of sophisticated machine learning models, including support vector machines, random forests, and deep neural networks, the project endeavor’s to establish robust predictive frameworks capable of discerning subtle patterns indicative of aging or neurological irregularities. This multifaceted approach not only provides insights into the aging process and its impact on the brain but also holds promise in early detection and diagnosis of neurological disorders. Integral to the research are ethical considerations, interpretability, and the ability to generalize findings across diverse populations. Addressing these aspects ensures that the developed models are not only accurate but also ethically sound and applicable across different demographic groups. By prioritizing transparency and interpretability, the research aims to foster trust in the predictive frameworks, facilitating their adoption and utilization in real world clinical settings. Ultimately, the outcome of this research extends beyond the realms of academic.
Enhancing Generative Model through the Integration of Large Language Models and MLOps
Authors: R Supritha , M Tejaswini
Published: November 2024

The Generative model is a powerful tool in generating data resembling training sets, often struggling with producing coherent and contextually relevant outputs in domains like internal communication. Traditional HR processes involve manual resume analysis and are inconsistent due to subjective judgment. Due to this a novel approach developed in human resource (HR) chatbots. It leverages the capabilities of Large Language Models (LLMs) like ChatGPT to enhance the coherence and contextual understanding of generated responses in HR interactions, fine tuning an LLM on a dataset of HR specific queries and responses, and integrating with existing generative models. The outcomes of the experiment show notable gains in the relevance and quality of generated answers for HR queries. Analyze the effectiveness of our integrated approach and discuss its potential for broader applications in advancing internal communication and conversational AI systems within organizations.
An Automated Exam hall management Application that allocates both seating arrangement for students and Invigilation of Supervisor
Authors: M Kasthuri , C Shenabaha , G Swetha , U Vaanmiga , K Vaishnavi
Published: November 2024

The Automated Exam Hall Allocation System is a comprehensive solution for managing exam hall assignments and invigilation duties, aiming to enhance efficiency and reduce manual workload. By leveraging automated scheduling algorithms, the system assigns examination halls based on pre established rules, optimizing space utilization and minimizing conflicts. Each exam hall is allocated to ensure maximum use, balancing the number of students with available spaces. Staff members receive a notification a day before their scheduled invigilation duty, allowing them to confirm availability. If a staff member cannot confirm, they are reassigned to a future exam, with increased priority to ensure equitable distribution of responsibilities. This approach ensures a fair and balanced invigilation schedule, giving all staff members and opportunity to participate. Students receive their hall assignments in advance, reducing confusion and ensuring they know exactly where to go on exam day. Additionally, a reminder is sent to staff on the exam morning to prevent missed duties. Administrators can easily monitor hall allocations, adjust schedules, and check real time status updates, all through an intuitive interface. Overall, the Automated Exam Hall Allocation System addresses the inefficiencies of traditional manual methods, reducing human errors, saving time, and promoting accuracy in exam logistics. The system fosters a smoother examination experience for students and staff, making it an ideal solution for educational institutions.
Supermarket Automation System
Authors: P Charu Prabha , R Ganashree , A Hajeera Thabasum , V Kalai Vani
Published: November 2024

As more people gain access to supermarkets, the demand for staff to manage checkout lines efficiently grows. This results in higher labour costs and operational challenges in keeping queue times short. To address this issue, there is a growing need to automate the billing process. A practical and efficient solution is to decentralize the billing system by allowing customers to handle their own checkout through their mobile devices. The Supermarket Automation System aims to streamline the billing process by allowing customers to use their mobile devices to scan product barcodes directly from the packaging. This eliminates the need for manual checkout, enabling a self service experience. Customers can scan barcodes, add items to a virtual cart, and view the total bill in real time. The system automates traditional billing workflows, reducing cashier dependence and speeding up transactions.
Guarding Against the Invisible Threats: Insights into Cybersecurity Risks and Solutions
Authors: C Saranya , S Sanjana , G S Monika , M G Meghana Reddy , G K Monika
Published: November 2024

Rising threats from cybercriminals in an increasingly connected world require critical examination in four areas: fake Apple charging cables, the Dark Web, One Time Password (OTP) use, and Bluetooth security have been assessed. First, fake original charging cables with Wi-Fi units integrated inside the cable can be used to perform MITM attacks that cause unauthorized access to compromised connected devices, interception of transmitted data, injection of malware to corrupt devices, and subsequent listening to the data streams of the connected gadgets. However, lacking stringent security measures that should characterize public charging points the practices make user personal alarms and precautionary measures mandatory. The Dark Web offers activists anonymity, yet it enables drug sales and identity thefts and is difficult for police to prevent advances in cybercrime. Two factor authentication (2FA) One Time Passwords (OTPs) are analyzed and discussed as applied to electronic payments with the overview of OTP positives, negatives and weaknesses, and threats stemming from cyberattacks. Finally, Bluetooth security threat categories are discussed with reference to secure data transfer during the wireless link, proceeding to types of attacks, and countermeasures. To sum up, more attention and preventive actions regarding such cyber threats are crucial as technologies are all pervading.
Automated Guided Vehicle for Inventory Management
Authors: A Lavanya , D Jyothi , D Ankitha
Published: November 2024

The initiative centers on the development and production of an Automated Guided Vehicle (AGV), designed to transform logistics across multiple industries, such as manufacturing, healthcare, and hospitality. As businesses increasingly aim to enhance their operational efficiency, automating transportation becomes vital for lowering labor expenses and minimizing the time delays associated with human involvement. The AGV presents considerable benefits in material handling, facilitating the effective and dependable movement of goods. Fitted with cutting edge sensors, the AGV can navigate autonomously within its surroundings, identifying and circumventing obstacles in real time. This feature guarantees safe functionality in dynamic environments, making it applicable in a variety of sectors. For example, in healthcare settings, the AGV can deliver medical supplies and equipment, reducing wait times and improving patient outcomes. In educational facilities, it can transport documents between offices, optimizing administrative workflows. The AGV’s adaptability also extends to shopping centers, hotels, banks, and corporate offices, where it can efficiently distribute items, thereby enhancing service delivery. Powered by a battery operated remote sensing system, the vehicle is designed to follow designated routes indicated by QR codes. This approach ensures precise navigation and simplifies the complexities often associated with traditional routing methods. By incorporating advanced technology, the AGV not only boosts operational effectiveness but also fosters a more organized and systematic logistics framework. In summary, this project is set to significantly influence various sectors by meeting the urgent demand for automation in material transport. As industries continue to progress and adopt technological innovations, the deployment of AGVs will be essential in optimizing operations, ensuring prompt deliveries, and ultimately enhancing overall productivity.
Predicting Smartphone Addiction
Authors: S Priya Dharshika , S Ramya , G Sakthini , S Sanchana , V Kalai Vani
Published: November 2024

Smartphone addiction has become a growing concern in today’s digital era, where excessive mobile phone use impacts mental health, productivity, and social interactions. This project aims to identify individuals at risk of addiction based on their usage behaviors and psychological patterns. The project is developed with the objective of identifying individuals prone to smartphone addiction based on various behavioral, psychological, and usage patterns. The survey included questions about demographics, cell phone usage patterns, and various psychological conditions such as anxiety, depression, and stress. The system utilizes Python for backend, while the frontend is built using HTML, CSS, and Java Script. The data was pre processed by coding the raw variables and adjusting the numerical variables to ensure that the model could be studied effectively. We train the model on some data and evaluate its performance on other data using some metric such as accuracy. Our results show that the model achieves high accuracy in predicting the smartphone addiction. The dataset used for this project comprises 200 records with 10 attributes, which include survey responses focused on phone usage patterns and addiction related behaviors. These attributes range from questions about daily phone habits, such as taking the phone to social gatherings or frequently checking it without notifications, to more serious indicators of addiction like anxiety over losing the phone or relying on it in awkward situations. The target attribute classifies users into two categories: addicted and not addicted, providing a clear objective for the prediction models.
5G/Next Generation Networks
Authors: T Harish , V Suriya , R Velan
Published: November 2024

5G, the latest advancement in wireless communication, represents a significant leap from previous generations by offering faster data transmission, higher network capacity, and ultra low latency. Designed to support a wide range of applications, 5G caters to enhanced mobile broadband, mission critical communications, and massive IoT connectivity, enabling smarter cities, autonomous vehicles, and advanced healthcare systems. This technology leverages innovations like millimeter waves, massive MIMO, small cells, and mobile edge computing, resulting in improved reliability and efficiency. 5G’s ability to connect billions of devices in real time creates transformative possibilities across industries, from enabling smart manufacturing to supporting seamless virtual and augmented reality experiences. As the global demand for high speed, reliable communication grows, 5G is poised to reshape how we live and work by enabling more efficient and interactive environments. With continuous advancements, the future of 5G holds immense potential to drive technological progress and innovation across multiple domains.
Eye blink Password Based Secure Authentication
Authors: K Malar , S Nayan Kumar , N Ravi , G M Rohith Kumar , T M Yuva Kishor
Published: November 2024

An eye blink password based secure authentication system utilizes the unique biometric patterns found in the human eye, particularly the iris or retina, to verify an individual’s identity. This technology capitalizes on the distinct and stable nature of eye biometrics, making it highly secure and reliable. The system involves capturing high resolution images of the iris or retina, extracting unique features, and matching them against a stored database for authentication. Due to its accuracy, it is ideal for high security applications where traditional methods like passwords may fall short. Integrated with encryption and liveness detection, eye based authentication prevents unauthorized access and is resilient against spoofing attempts, offering a robust, non invasive solution for secure identity verification. When users authenticate passwords through PINs, they must be obligatory to physically input the PIN, making them susceptible to password cracking techniques like shoulder surfing or thermal tracking. In contrast, utilizing hands off gaze based PIN entry methods eliminates any physical traces, providing a significantly more secure option for password entry. Gaze based authentication involves determining the eye location across consecutive image frames and continuously tracking the precise eye center.
H-IoT for Asthma Anticipated Effects Prediction Using Machine Learning Algorithm
Authors: A Suguna , T K Pradeep Kumar , S Nithiya
Published: November 2024

Asthma affects millions worldwide, presenting significant challenges in symptom prediction and management. The rapid advancement of Healthcare Internet of Things (H-IoT) technology has enabled continuous monitoring of physiological and environmental factors relevant to asthma. This paper presents an approach that leverages H-IoT data and machine learning (ML) algorithms to predict asthma related effects, allowing for timely intervention and management. Using real time physiological data, environmental metrics, and historical health records, we train predictive ML models to anticipate asthma episodes and exacerbations. Our results show high accuracy in episode prediction, demonstrating the potential of combining H-IoT and ML for improved asthma management.
PERAMALAN BEBAN PENERANGAN KAPAL RO-RO 32.45 METER MENGGUNAKAN METODE ZCM (ZONAL CAVITY METHOD)
Authors: Suardi Suardi , Setiawan Wira , Uswah Pawara Muhammad , Mursid Nugraha Arifuddin Andi , Alamsyah Alamsyah , Yulia Astin Widya
Published: November 2024

Sistem penerangan di atas kapal penumpang kapal ro-ro 32.45 meter masih menggunakan lampu fluorescent atau biasa disebut sebagai lampu neon, lampu ini dipandang kurang efektif mengingat berbagai penelitian menyebutkan bahwa lampu fluorescent memiliki dampak negatif berupa kandungan mercury yang membahayakan lingkungan dan daya yang lebih boros dibandingkan dengan menggunakan lampu LED. tujuan dari penelitian ini adalah mengkaji tingkat penghematan daya generator untuk penerangan setelah mengganti lampu fluorescent menjadi lampu LED. Metode yang digunakan dalam penelitian adalah metode lumen atau biasa disebut metode ZCM (Zonal Caviti Method). Hasil penelitian di dapatkan jumlah beban listrik penerangan pada penerangan fluorescent yang telah di akumulasikan tiap deck sebesar 24.41 kW, sedangkan penerangan dengan jenis penerangan LED di dapatkan beban listrik penerangan sebesar 12.49 kW. Sehingga dengan hasil yang tertera di atas didapatkan efisiensi daya sebesar 11.92 kW yang kemudian akan disimulasikan pada desain gambar 3D.
ANALISIS PENERAPAN MODEL PEMBELAJARAN PROBLEM POSING DALAM PEMBELAJARAN DI SEKOLAH
Authors: Nuridayanti Nuridayanti , Vitalocca Dyah , Labusab Labusab
Published: November 2024

Penelitian ini memiliki tujuan untuk mengkaji penerapan model Pembelajaran Berbasis Problem Posing dalam konteks pembelajaran di sekolah. Penelitian ini menggunakan metode studi literatur dengan pendekatan deskriptif kualitatif untuk menganalisis implementasi model Problem Posing dalam pembelajaran di sekolah. Data dikumpulkan melalui dokumen, dengan pencarian jurnal yang relevan mengenai Problem Posing melalui platform Sinta dan Google Scholar (Google Cendekia) dalam rentang tahun 2018-2022. Kata kunci yang digunakan adalah "model Problem Posing". Berdasarkan pencarian ini, ditemukan 100 jurnal, yang kemudian diseleksi menjadi 22 jurnal sesuai kriteria untuk analisis lebih lanjut. Berdasarkan analisis terhadap 22 jurnal tersebut, diperoleh informasi sebagai berikut: 1) Model Problem Posing umumnya ditemukan dalam bidang ilmu sains dengan persentase penerapan di sekolah sebesar 64%. Sementara itu, dalam bidang ilmu teknik atau kompetensi keahlian, persentase penerapan model ini adalah 18%. Bidang ilmu bahasa memiliki persentase 9%, sementara ilmu sosial dan ilmu agama masing-masing memiliki persentase 5%. Dalam konteks bidang studi yang lebih spesifik, model pembelajaran Problem Posing paling sering diterapkan dalam bidang matematika, dengan persentase sebesar 36% dari total jurnal yang dianalisis. 2) Implementasi model problem posing memberikan dampak positif terhadap peserta didik; 3) Dampak dari penggunaan model pembelajaran Problem Posing positif yaitu dapat meningkatkan hasil belajar peserta didik, mengembangkan kemampuan dalam memecahkan masalah, meningkatkan minat belajar, mendorong motivasi belajar serta mengembangkan kemampuan berpikir kritis peserta didik.
Pelatihan Komputer dan Microsoft Office untuk Meningkatkan Keterampilan Digital Remaja Tahfidz di Gowa
Authors: NFH Alifyah , Muntazarah Fediyatun , Nasrullah Asmaul Husnah , Mappalotteng Abdul Muis , Syahrul Syahrul
Published: November 2024

Pelatihan penggunaan komputer dan aplikasi Microsoft Office untuk remaja di Rumah Tahfidz Kabupaten Gowa telah berhasil meningkatkan keterampilan digital mereka, yang sangat penting di era teknologi informasi saat ini. Program ini dirancang untuk memberikan pemahaman dasar mengenai komputer dan aplikasi Microsoft Office, dengan penekanan pada penggunaan Microsoft Word dan Excel. Meskipun terdapat kendala seperti kurangnya akses ke perangkat, peserta mampu beradaptasi melalui pembelajaran kolaboratif yang meningkatkan semangat dan kerjasama tim. Hasil dari pelatihan ini menunjukkan peningkatan keterampilan teknis dan kepercayaan diri peserta dalam menggunakan teknologi informasi, yang sangat diperlukan untuk menghadapi ujian berbasis komputer di sekolah. Untuk meningkatkan efektivitas pelatihan di masa mendatang, disarankan agar pengelola rumah tahfidz melakukan evaluasi secara berkala dan menjalin dukungan dari pihak terkait, serta menyelenggarakan sesi lanjutan untuk memperdalam pemahaman peserta.
PENDAMPINGAN DIGITALISASI KELOMPOK TANI TAMBAK DALAM PROMOSI PRODUK MELALUI MEDIA SOSIAL E-COMMERCE
Authors: Riska Muhammad , Ashari Hilda , Muchtar Akhyar , Tandirerung Veronika Asri , Burhan Muh. Iswal
Published: November 2024

Kegiatan ini bertujuan untuk meningkatkan kesejahteraan petani tambak di Desa Bonto Manai melalui pemanfaatan teknologi e-commerce. Masalah utama yang dihadapi petani adalah terbatasnya akses pasar dan fluktuasi harga yang merugikan. Melalui pelatihan dan pendampingan, petani dilatih untuk menggunakan platform Shopee dalam memasarkan produk perikanan mereka. Hasil kegiatan menunjukkan adanya peningkatan pengetahuan petani tentang e-commerce dan minat untuk memanfaatkan platform ini. Adapun kendala utama yang dihadapi adalah terbatasnya pengetahuan dasar digital di daerah tersebut sehingga tim perlu memberikan pendekatan lebih personal untuk memastikan peserta mampu memahami. Meskipun demikian, kegiatan ini memberikan bukti bahwa digitalisasi pemasaran dapat menjadi solusi yang efektif untuk meningkatkan pendapatan petani tambak. Kegiatan pengabdian ini merekomendasikan perluasan program literasi digital bagi petani tambak serta dukungan pemerintah dalam penyediaan infrastruktur digital yang memadai.
Kata Kunci: Petani Tambak, Pemasaran Produk Tambak, E-Commerce, Pelatihan dan Pendampingan, Digitalisasi