Volume 13 | Issue 3 |

 Abstract

This research paper presents the design and development of a smart surveillance bot capable of autonomous navigation along predefined paths using a line-following mechanism. The system integrates an ESP32-CAM module for live video streaming, a color sensor for line detection, an ultrasonic sensor for obstacle avoidance, and a voltage sensor for battery monitoring. The bot is designed to enhance security and industrial monitoring by providing real-time surveillance and automated patrolling. The integration of multiple sensors ensures efficient navigation, making it a cost-effective and scalable solution for security applications. The proposed system is tested under different environmental conditions, ensuring reliability and efficiency in various real-world applications.

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Line Following Robot WiFi-Controlled Robot Surveillance Bot

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 Abstract

Authentication has always been a critical challenge in examination settings, where ensuring the legitimacy of candidates is essential to maintaining the integrity of the assessment process. Traditional manual verification methods, such as paper-based identity checks and physical clearance cards, are highly vulnerable to security threats, including impersonation, fraudulent identity documents, and administrative errors. These weaknesses not only compromise the credibility of examinations but also place an additional burden on exam administrators.To address these challenges, this research proposes an advanced, automated authentication system that leverages facial biometrics and Convolutional Neural Networks (CNNs) to provide a robust and secure solution for student verification during exams. By integrating deep learning models, the system is capable of detecting, analyzing, and recognizing candidates' faces in real-time, ensuring a highly accurate and tamper-proof authentication process.The proposed approach significantly reduces the risks associated with impersonation by using image-processing techniques to match each candidate's face against a pre-registered database, preventing unauthorized individuals from gaining access to the examination hall. Furthermore, the system enhances operational efficiency by automating the verification process, eliminating the need for manual document checks, and reducing the administrative workload. By implementing this biometric authentication system, institutions can reinforce examination security, enhance transparency, and ensure a fair evaluation process. The integration of deep learning and facial recognition technologies represents a significant step toward modernizing exam security protocols, ultimately leading to a more reliable and fraud-resistant examination framework.

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 Keywords

Authentication, Examination Security, Face Biometrics, Convolutional Neural Networks (CNNs), Deep Learning, Real-time Face Recognition, Student Verification, Impersonation Prevention, Image Processing, Automated Identity Verification, Seating Allotment System, Biometric Authentication, Fraud Prevention, AI in Education, Security in Examination Systems.

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Creative Commons Attribution 4.0 and The Open Definition

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In this project, a tiny self-driving automobile with line-following, obstacle-detection, and emergency braking features is designed and developed. The vehicle moves through a predetermined track while dodging obstacles and keeping a steady course thanks to an Arduino microcontroller, ultrasonic sensors, infrared sensors, and DC motors. While the obstacle recognition system initiates emergency braking to avert collisions, the line follower algorithm guarantees precise tracking. This project demonstrates how programming, robotics, and sensor technologies may be used to produce a working tiny self-driving automobile.

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dashboard

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Creative Commons Attribution 4.0 and The Open Definition

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Social media has revolutionized many business functions, with Human Resource (HR) management being one of the most affected functions. HR practitioners are increasingly using social media platforms like LinkedIn, Facebook, and Indeed to improve recruitment, employer branding, and employee engagement. This research paper examines the level of social media usage in HR practices, assessing its advantages, disadvantages, and overall effect. Employing a mixed-methods methodology, the research integrates qualitative interviews with HR managers and quantitative surveys to capture observations on social media use in recruitment, employee participation, and company culture. Key results point to the fact that social media has enhanced recruitment effectiveness and employer image, but data privacy issues and the absence of clear guidelines on usage are major challenges. The paper concludes that although social media has much to offer HR, organizations need to develop sound policies and invest in training HR professionals to deal with the attendant risks successfully. Future studies can examine the long-term impact of social media on employee performance and retention.

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 Keywords

Social Media, Human Resources, Recruitment, Employer Branding, Employee Engagement, HR Strategies, Digital Recruitment.

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This paper explores the implications of the African Union's (AU) inclusion in the Group of Twenty (G20) for global trade dynamics in the next decade. It provides an overview of G20 and highlights its origins, structure, and role in global economic governance, and also discusses India's strategic initiative to integrate the AU into G20, emphasizing its significance in enhancing India's global influence. Then, it explores the implications of the AU's membership in G20 for India, African nations, and global trade dynamics. It examines the AU's role in balancing representation within G20, particularly against the dominance of developed country regional blocs. The paper also highlights the AU's focus within G20 on trade-oriented matters and investment in local labourers. Finally, it discusses the alignment between the AU's Agenda 2063 and G20's goals, identifying potential areas of cooperation. The paper concludes that the AU's inclusion in G20 represents a transformative step in global economic governance, offering opportunities for enhanced collaboration and economic growth.

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 Keywords

G20, Trade, African Union

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Creative Commons Attribution 4.0 and The Open Definition

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The Real Tech Arm is a biomimetic robotic arm designed to replicate human hand movements with high precision. By utilizing servo motors and camera vision, this project aims to develop a responsive and interactive robotic limb. The integration of a vision-based tracking system ensures real-time data processing and arm control. Unlike traditional sensor-based approaches, this system relies entirely on computer vision to detect and interpret hand gestures. This paper presents the design, implementation, and functionality of the Real Tech Arm, showcasing its potential applications in prosthetics, robotics, and industrial automation.

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Arduino,Automation,Advanced Robotics Prosthetic Technology ,Smart Prosthetics

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Brain tumor detection is critical for early diagnosis and treatment planning. This study presents an automated approach utilizing OpenCV to analyze both MRI (Magnetic Resonance Imaging) and CT (Computed Tomography) scans for tumor identification. The proposed method involves image preprocessing, segmentation, and feature extraction to detect abnormal regions in brain scans. Techniques such as grayscale conversion, noise reduction, adaptive thresholding, morphological operations, and edge detection are applied to enhance tumor visibility. The system is designed to work with both MRI and CT images, ensuring broader applicability in medical imaging. Furthermore, machine learning models can be integrated for improved classification accuracy. The proposed approach provides a cost-effective, efficient, and automated solution to assist radiologists in early diagnosis and decision-making.

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Detection, Machine Learning, OpenCV

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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The paper study analyses Thomas Harris's Hannibal and Hannibal Rising using Social Cognitive Theory (SCT) by Albert Bandura. It explores how Hannibal Lecter's transformation from a traumatized child to a sophisticated predator is shaped by observational learning, reciprocal determinism, and moral disengagement. In Hannibal Rising, Hannibal experiences severe trauma during World War II, witnessing violence and cannibalism, which later influences his behaviour. Through observational learning, he adopts violent tendencies from his environment and refines them under the guidance of his aunt, Lady Murasaki. His intelligence and adaptability allow him to develop a self-regulated moral code, justifying his actions as acts of justice. In Hannibal, Lecter's fully formed persona demonstrates reciprocal determinism, where his thoughts, actions, and environment reinforce his identity as both a cultured intellectual and a ruthless predator. He engages in moral disengagement, rationalizing his killings by targeting only those he deems unworthy, thus detaching himself from guilt. His ability to manipulate and control situations reflects his mastery of learned behaviour. By applying Social Cognitive Theory, this study provides a deeper understanding of Hannibal Lecter's psychology beyond typical criminological and psychoanalytic perspectives. It highlights how external influences, cognitive processes, and behavioral reinforcement shape identity and moral reasoning. This analysis contributes to broader discussions on learned behaviour, trauma, and the complexities of villainous characters in literature.

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: Social Cognitive Theory, Observational Learning, Reciprocal Determinism, Moral Disengagement, Trauma.

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The COVID-19 pandemic marked a paradigm shift in education, as it catalyzed the use of technology to overcome challenges in traditional teaching methods. This paper explores emerging trends in educational technology, focusing on Artificial Intelligence (AI), Virtual Reality (VR), Learning Management Systems (LMS), and their integration into blended and hybrid learning models. AI-based learning tools have revolutionized education through customized learning, auto-assessment, and real-time data analytics that help refine the teaching strategies. VR has provided immersive learning; students are exposed to interactive simulations of complex ideas, making learning more efficient and productive. Learning management systems have been at the forefront of online learning as they manage all content, facilitate communication, and provide an opportunity for assessment. Such progressions have allowed a smooth shift toward blended learning: a mixture of face-to-face and digital instructions. Success with Ed-Tech in post-pandemic learning indicates a likelihood of access, engagement, and better outcomes in diverse populations. The National Education Policy 2020 is the backbone in integrating technology in education, digital infrastructure, and skill development through learner-centric approaches. AI tools, VR, and LMS solutions have therefore bridged the gaps in education, making it more inclusive, equitable, and relevant to current needs by aligning with NEP 2020. This paper points out how these innovations address post-pandemic challenges and transform education, preparing students for a technology-driven future in alignment with policy objectives and global trends.

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 Keywords

Online Learning, AI & VR in learning, Collaborative learning, Educational Technology in NEP2020

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