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A Review of IoT Security Issues in Smart City Systems
No full textThe rapid development of smart cities relies heavily on interconnected IoT devices, intelligent communication infrastructures, and emerging technologies such as artificial intelligence and blockchain. While these advancements enhance urban efficiency, they also introduce significant security challenges that threaten data integrity, privacy, and system resilience. This review critically examines the key IoT security issues encountered in smart city ecosystems, including vulnerabilities in device authentication, insecure communication protocols, data leakage, and weak access control mechanisms. The objective of this review is to consolidate existing research on IoT-related security threats within smart city environments and evaluate how modern technologies are being used to mitigate these issues. The paper identifies key research gaps such as the lack of unified security frameworks, inadequate real-time threat detection, and limited scalability of existing solutions. Future directions are proposed, emphasizing the integration of AI-driven threat analytics, blockchain-based trust models, and standardized security architectures to strengthen the security posture of next-generation smart cities
Development of Portable Electroplating Equipment to Enhance the Efficiency of Small and Medium-Sized Jewelry Industries Indonesia
No full textSmall and medium-sized jewelry enterprises (SMEs) in Indonesia face challenges because traditional electroplating methods are expensive and lack flexibility, which reduces their productivity and slows down operations. This study addresses this problem by creating a novel, affordable, and user-friendly electroplating tool specifically designed for these small businesses.To develop the tool, the researchers reviewed existing literature and conducted field visits and interviews with personnel at three jewelry companies located in Bekasi, Bandung, and Riau to understand the primary technical issues they face.The resulting tool measures approximately 400 mm long, 110 mm wide, and 150 mm tall, and is constructed from polypropylene, which is resistant to chemical damage. It features a built-in system to ventilate harmful gases and adjustable voltage control. Testing the tool using copper plating on bracelets demonstrated that it operates 25% faster than conventional methods and produces a smoother, shinier finish. The compact size allows it to be used efficiently in tight workspaces, and the dedicated ventilation system provides protection for workers against hazardous fumes. Furthermore, this tool is cheaper than comparable tools currently on the market, enhancing affordability for small businesses. This innovation is expected to enhance SME autonomy, lower production costs, and facilitate greater design diversity within the Indonesian jewelry industry. Future research should validate its efficacy across a broader range of applications, including micro-jewelry. This collaboratively developed portable tool offers a sustainable and technologically innovative solution to bolster the advancement of Indonesia's creative industr
Fundamentals of Supply Chain Management
No full textThe author would like to express his gratitude to Allah SWT for His abundant blessings and grace, which have enabled this book entitled "Fundamentals of Supply Chain Management" to be compiled and completed successfully. This book covers a
range of fundamental concepts to advanced strategies in supply chain management, including supply structure configuration, business relationships, technology integration, and customer orientation. This book can serve as a bridge of understanding for students, practitioners, and decision makers who want to manage supply chains more effectively and adaptively
amid global challenges. This book still has many shortcomings in its compilation. The author would like to thank the various parties who have helped in the completion of this book. Hopefully, this book will serve as a clear and accessible reference and literature
source
A Comparative Study of Regression Testing Techniques: An Industry-Oriented Evaluation of Efficiency, Coverage and Cost
No full textRegression testing is an essential component of software maintenance, aimed at ensuring that newly introduced changes do not negatively impact the existing functionality of a system. In today's fast-paced industrial environments, particularly those employing agile methodologies and Continuous Integration/Continuous Deployment (CI/CD) pipelines, the choice of regression testing technique significantly influences project timelines, resource allocation, and product quality. This research investigates and compares five widely adopted regression testing types: Corrective, Retest-All, Selective, Progressive, and Complete Regression Testing. This study's primary objective is to assess each technique's industrial suitability based on key evaluation metrics such as time efficiency, cost of execution, test coverage, automation/tool support, scalability, and risk of fault omission. We adopted a qualitative scoring methodology, grounded in a comprehensive review of several scholarly articles and industry reports. Each testing type was critically analyzed and benchmarked using a comparison matrix to highlight its strengths and limitations. The analysis reveals that while each regression testing method serves distinct use cases, Selective Regression Testing strikes the best balance between efficiency and coverage for modern industrial needs, particularly in projects with frequent releases and constrained testing budgets. The novelty of this study lies in its holistic, literature-backed comparative framework, explicitly tailored to the industry context aspect often overlooked in prior academic evaluation
Global Sustainable Development: Ideological and Political Education-Based Theoretical Deconstruction and Practical Paths
No full textThis project takes ideological and political education as the starting point, combines the global Sustainable Development Goals, analyzes the value foundation and educational paths of sustainable development at the theoretical level, and proposes a practical framework. Through multi - dimensional research methods, it analyzes the core role of ideological and political education in cultivating sustainable development awareness and promoting social actions, constructs a three - dimensional model of “value guidance – knowledge transformation – practical participation”, and builds a scientific basis chain for the transformation of ideological and political education theory into sustainable development practic
Mobility and Orientation Guidance for Individuals with Visual Impairments using AI
No full textIn this study, we developed an intelligent device and a smart application to improve the daily activities of the visually impaired individuals. Low-vision or blind people often face a number of barriers in the course of completing everyday tasks. Learning about roadways, purchasing commodities, reading written books, and digesting new information is significantly harder. To this end, a gadget was created to counter these obstacles. People with deficient eyesight or complete blindness can now enjoy the effect of reading books and articles in real-time using OCR and AI-powered technology. They can also recognize things, goods, and people, including visual information like facial expressions. In addition, haptic feedback through bone-conducting headphones gives multilingual notifications of either vehicle movement or road condition
Herbal Plant Identification Using Deep Learning
No full textFrom traditional medicine to today’s research in pharmacology, herbal plants are seen as very important. Yet, correctly identifying herbal species is challenging since many species share the same features and must be classified by experienced taxonomists. Technological advances such as deep learning have provided a way to automate this work with improved accuracy. The proposed system identifies herbal plants by analyzing their images using Convolution Neural Networks (CNNs), which are known for being effective in computer vision. To ensure the dataset is strong, I used thousands of clear leaf pictures from various herbal plant species that were taken in many environmental settings. Before training, the images were processed in stages by normalizing them, creating variations, and separating important objects. To find the most suitable CNN, VGG16, ResNet50, and MobileNetV2 were assessed based on their accuracy, how efficient they are, and whether they could be used on mobile phones. By using transfer learning, the model could take advantage of previously trained models on huge image collection
The Requirement Analysis of An Offline Automated Invigilation System with Gmail Alert Integration
No full textExamination malpractice remains a major concern for academic institutions, impacting on the fairness and credibility of evaluations. To address this, we analyze and propose an Offline Automated Invigilation System with Gmail Integration that leverages computer vision and machine learning to detect and prevent unethical behavior during offline exams. The system features three detection modules: YOLO for identifying mobile phones, Support Vector Machines (SVM) for tracking abnormal head movements, and Haar Cascade for real-time eye movement analysis. These technologies work together to monitor students, detect suspicious behavior, and capture evidence, which is then sent via Gmail alerts to examination authorities. Designed to operate without internet connectivity, the system ensures effective invigilation even in remote or resource-limited environments. By reducing human dependency and automating the detection process, this solution enhances accuracy, scalability, and integrity in offline examination settings
Animal Detection for Crop Protection Using Deep Learning: Insights from YOLO V3, R-CNN, Random Forest
No full textCrop damage caused by animals is a significant challenge faced by farmers worldwide. Traditional methods for crop protection are often ineffective and labor-intensive. This paper explores the use of deep learning for real-time animal detection in agricultural settings. A deep learning model is trained on a dataset of images containing various animal species commonly found in agricultural environments. The model is then deployed on a camera-based system to detect and classify animals in real-time, providing farmers with timely alerts and enabling proactive measures to protect their crops. The proposed system offers a promising solution for improving crop protection efficiency and reducing losses due to animal damage. Results demonstrate a 95% accuracy in detecting animals, significantly outperforming traditional methods
A Data-Driven Engine Starter System Using ESP32 With Multi-Layer Authentication and Alerts
No full textThe Data-Driven Engine Starter System using ESP32 is designed to enhance engine security by integrating multi-layer authentication mechanisms, including password input, fingerprint recognition, and RFID/NFC technology. This system prevents unauthorized engine access, ensuring only authenticated users can operate it. In addition to robust authentication, the system leverages IoT connectivity to provide real-time alerts and monitoring, allowing users to control and oversee engine activity through a mobile app or web interface. By incorporating failsafe mechanisms and cloud-based logging, the system guarantees operational reliability and security, making it suitable for automotive, industrial, and fleet management applications. The system further enhances reliability through IoT connectivity, allowing remote monitoring, control, and alerts via a dedicated mobile app or web interface