UTAR Institutional Repository (Universiti Tunku Abdul Rahman)
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Application development of university smart assistant
Get PDFThe rapid advancement of mobile technology has significantly impacted various industries,
including education. Traditional university resource management systems often suffer from
inefficiencies, such as scheduling conflicts, underutilized spaces, and difficulties in
navigating large campuses. To address these challenges, this project presents the
development of a University Smart Assistant application, which integrates smart scheduling
conflict for booking and Augmented Reality (AR) to enhance resource booking and
navigation. The Smart Scheduling Assistant module analyses current availability to
recommend optimal booking times, reducing scheduling conflicts and improving resource
utilization. The AR Navigation module provides clear, arrow directions, and also voice
guidance, helping users locate their reserved facilities efficiently. This application aims to
streamline resource management, improve the user experience, and set a new standard for
booking and navigation in university, allow user to book. The methodology used to develop
this mobile application is RAD (Rapid Application Development)
Exploring the potential of blockchain technology in property management
Get PDFAs Malaysia’s property management sector undergoes digital transformation under Construction 4.0, adopting blockchain technology is essential to improve transparency, security, and efficiency. Although blockchain has proven benefits globally, its adoption in property management remains unclear. Existing literature often focuses on isolated applications such as property transactions and rental management. This study addresses that gap by exploring blockchain’s potential to integrate and transform the entire property management lifecycle, while also identifying inefficiencies and adoption challenges. The literature review identified 28 inefficiencies and 24 blockchain potentials across six key aspects, which were land administration, property transactions, leasing and renting, property administration, property financialization, and property maintenance. Additionally, 21 adoption challenges were categorized into five main areas, which were legal and
regulatory, cost and liquidity, security and privacy, technical limitations, and institutional challenges. A quantitative research methodology was used, and an
online questionnaire was distributed among property developers in the Klang Valley, yielding 119 valid responses. Data were analysed using Cronbach's Alpha, Arithmetic Mean, Mann-Whitney U, Kruskal-Wallis, and Spearman’s Correlation tests. This study’s Arithmetic Mean results reveal maintenance inefficiencies and lack of transparency as the most pressing issues, with blockchain’s strongest potential in transparent asset tracking and predictive maintenance. The critical implementation challenges are technical limitations
and security concerns, particularly interoperability and privacy protection difficulties. Mann-Whitney U test shows the public sector has greater awareness of these inefficiencies and potentials and views legal, cybersecurity,
and smart contract challenges as more severe. Kruskal-Wallis analyses found significant differences across age, experience, job position, and company size, highlighting the complexity of blockchain integration in property management.
Spearman’s correlations emphasized transparency and predictive maintenance as potential priorities, while digital identity and immutability posed major adoption challenges. These findings underscore the need for a strategic
approach to blockchain adoption and provide recommendations for stakeholders and policymakers to navigate this transformative landscape.
Keywords: Blockchain, Property Management, Real Estate Management, Smart Contract, Tokenisation
Subject Area: TH3301-3411 Maintenance and repai
Application of smart technologies in construction project management
Get PDFThe integration of smart technologies in construction project management has emerged as a transformative approach to optimising time, cost, and quality, addressing long-standing challenges in project efficiency and productivity.
Malaysia’s National Construction Policy 2030 emphasises the adoption of digital technologies to modernise the sector, promoting automation and advanced data-driven solutions. This study examines the application of Building Information Modelling (BIM), Internet of Things (IoT), Artificial Intelligence (AI), and automation tools in enhancing project planning, resource allocation, communication, and risk mitigation. Moreover, existing literature has highlighted the growing application of smart technologies across multiple industries including healthcare, education, agriculture, and general construction, emphasizing their role in enhancing efficiency, sustainability, and innovation. Studies by Jakobsen et al. (2023), Khan et al. (2024), and Pandey et al. (2022) illustrate the broad potential of smart technologies in various sectors. Within construction, prior research (e.g., Carolina Hernández García et al., 2024; Nilimaa, 2023) has focused on the technological adoption at a general level,
such as eco-friendly materials and safety systems. However, there is a noticeable gap in understanding how smart technologies specifically impact construction project management practices such as planning, scheduling, cost
control, and quality assurance. Few studies provide empirical evidence directly linking smart technologies with measurable improvements in project performance. This study aims to fill that gap by focusing on how digital tools contribute to key project management functions within the Malaysian
construction industry. A quantitative research approach is employed, using a structured questionnaire survey to gather insights from experienced industry professionals in Malaysia’s construction sector. The data is analysed through
descriptive and inferential statistical techniques, including reliability analysis, correlation tests, and factor analysis, to identify key factors influencing the effective adoption of smart technologies. A total of 110 responses were collected and analysed through descriptive and inferential statistical techniques, including reliability analysis, correlation tests, and factor analysis, to identify key factors influencing the effective adoption of smart technologies. The
findings reveal that smart technologies enhance project planning through improved scheduling, resource optimization, and stakeholder coordination. Cost reductions stem from minimized budget overruns, reduced material waste, and
automation-driven productivity gains. Quality improves via automated defect detection, BIM-driven accuracy, and standardized workflows, while risk mitigation benefits from real-time safety monitoring and AI-driven analytics.
However, challenges such as high initial investment costs, limited technical expertise, resistance to change, and the lack of standardized implementation frameworks hinder the widespread adoption of these technologies. Statistical
analysis confirms a strong correlation between smart technology implementation and project performance, with cost, training, and organizational readiness as key influencing factors. The findings are expected to provide empirical insights into the impact of digital innovations on improving project performance, enabling practitioners to make informed decisions in adopting technology-driven solutions. Additionally, the study contributes to the development of strategic frameworks for integrating smart technologies into
construction project management, aiding policymakers and industry leaders in overcoming implementation barriers. The research offers a practical roadmap for fostering more efficient, cost-effective, and high-quality construction
practices, ensuring greater predictability and control over project outcomes.
Keywords: Smart technologies, construction project management, time-cost quality, digital innovation, project performanc
A chatbot for teaching software testing CTFL syllabus
Get PDFSoftware testing is a vital process in software development, ensuring product quality by minimizing defects and preventing errors that affect usability. The ISTQB Certified Tester Foundation Level (CTFL) syllabus introduces fundamental concepts of software testing, serving as an important resource for students and lecturers. This project develops a web application with an integrated chatbot specifically designed to teach the CTFL syllabus. Developed using robust Laravel backend and React front end, integrating a large-language-model-driven chatbot to provide concise explanations, practical examples, and automatically generated quiz questions to reinforce user understanding. The development followed V-Model methodology, conducting different kind of testing including unit, integration, system, and user acceptance to ensure the web application to implement all the stated requirements from users, and to reinforce its core educational objectives through systematic validation. In the results of conducted testings, the web application is proven to have outstanding performance without defects affecting the usage. By combining natural language interaction with structured syllabus content, the system offers an engaging and accessible learning tool that enhances comprehension, supports teaching, and better prepares learners for CTFL certification and implement professional practice in the work field.
Keywords: Software testing, CTFL, chatbot, web application, large language model, learning tool
Subject Area: QA76.75-76.765 Computer softwar
Deep learning for multi-attribute vehicle recognition in vehicle access control system
No full textVehicle recognition systems are becoming increasingly essential for intelligent transportation, traffic surveillance, and security applications. For the purpose to identify vehicle attributes in real-time, this research provides a hybrid vehicle recognition system that is implemented as a web and mobile application. It combines deep learning and computer vision techniques. To extract license plates, colors, makes, models, and production years of vehicles, the system mainly uses EasyOCR and YOLOv8 with multi-attribute detection. A refined GPT-4o visual-language model (VLM) acts as a fallback, improving recognition reliability in edge instances when YOLOv8 and EasyOCR would not yield reliable results. The approach involves capturing pictures of vehicles from cameras or user uploads, processing them using the pipeline for detection and OCR, then using the GPT-4o VLM to verify the outcomes. The system's modular design provides seamless connection with web and mobile platforms, enabling real-time performance and scalability. It is expected to work reliably across a variety of lighting situations, angles, and occlusions. The study shows a potential approach for enhancing the recognition of vehicle attributes. Future research will involve adding more unusual vehicle kinds to the dataset, refining the model inference for edge devices, and integrating predictive analytics for anomaly detection and vehicle tracking.
Keywords: vehicle recognition; YOLOv8; EasyOCR; GPT-4o; deep learning; computer vision; license plate recognition
Subject Area: T58.5-58.64 Information technolog
Mobile receipt scanner for easy expense sharing
No full textThe development of a bill splitting application is due to the increased complexity of shared cost dsitribution among social groups which require manual calculation to be done. This project presents a mobile application to simplify the process of bill splitting by implementing Optical Character Recognition (OCR) and Artificial Intelligence (AI). The development of the application will be guided by Rapid Application Development (RAD) while employing Tesseract as the OCR framework with DeepSeek as the AI tool to help with the success of this project. Additionally, the application is built with the React Native framework pairing it with MySQL database to manage user, events, and item tables. Crucial features regarding the application is multiple splitting methods which are the “equal” method and “pay for what you eat”, real-time collaboration among participants to help out with the cost management, and also AI-based calculation to help calculate and summarize the event’s cost. This application offers user a practical and user friendly solution to tackle one of the common real-world challenges. The application is easily scalable with future enhancements through different technologies such as advanced machine learning and integration with popular payment platforms. The project concludes with combining OCR and AI technologies to provide an user friendly approach to allow user collaborate with each other to manage their expenses in an efficient manner.
Keywords: mobile application; optical character recognition; artificial intelligence; cost management; bill splitting
Subject Area: QA76 Computer Scienc
风雨中的家国情怀：傅承得与沙末赛益诗作的比较研究 : Homeland Sentiments Amid Storms - A comparative study of Poh Seng Titt’s and A. Samad Said’s Poetry
No full text本研究聚焦于傅承得《赶在风雨之前》和沙末赛益（A. Samad Said）《含羞种子》 （Benih Semalu）两部诗集，综合运用文本细读法和诗史互见的结合，从历史记 忆重构以及意象的运用两个维度，探析两位诗人何以在政治抒情诗中表达对民 族创伤的关怀。通过比较两位诗人对 1969 年 513 事件、1987 年茅草行动的刻 画，剖析了事件的起因，及其对群体所产生的深远影响，力求还原历史真相。 研究亦以“数字意象”、“自然意象”与“人物意象”三类核心象征展开论述。 傅承得愤懑且尖锐批判国家政策的不平衡，激情直白描绘马来西亚华社受政治 压制，进而被边缘化的处境；沙末赛益则巧妙运用乡村生活和童年回忆的隐喻， 突出国族的韧性和对国家未来的美好憧憬。研究指出，尽管两者诗风截然不同， 但皆以小诗形式抵制官方单一历史叙述，将个人创伤化为集体记忆。然而作品 中也表现艺术上的局限性。傅承得的诗歌容易陷入悲观主义，且意象单一，而 沙末赛益的诗歌则过于晦涩，或削弱其批判力量。这种对比，为马华文学与马 来文学的比较研究提供新的见解，展现两部诗集在诗坛的独特价值。 【关键词】《赶在风雨之前》、沙末赛益、《含羞种子》（Benih Semalu）、历史记 忆重
The relationship between neuroticism, self-compassion and phone addiction among undergraduate students in Malaysia
Get PDFPhone addiction has emerged as a prevalent concern in the digital age, particularly among university students. The purpose of this study is to examine the relationship between phone addiction, neuroticism and self-compassion among undergraduate students in Malaysia. Therefore, the present study examined the relationship of self-compassion, neuroticism, and phone addiction among undergraduate students in Malaysia, as well as tested whether neuroticism and self-compassion predict phone addiction. This study is a correlational design using a cross-sectional research design and purposive sampling to recruit participants online through the survey method. This study applied three instruments to assess self-compassion, neuroticism and phone addiction, which were the Self-Compassion Scale-Short Form, Big Five Inventory-Neuroticism, and Smartphone Addiction Scale-Short Version. The survey was distributed online to 110 undergraduate participants in Malaysia between 18 to 25 years old. The result showed that there were significant relationships between self-compassion, neuroticism, and phone addiction among undergraduates in Malaysia. Moreover, the result showed that self-compassion has a negative relationship with phone addiction and was able to predict phone addiction, but neuroticism was unable to predict phone addiction among undergraduates in Malaysia. In summary, self-compassion can be further examined as an intervention toward undergraduate students with phone addiction
Mapping Bai En as male feminization figure in social networking site Facebook: Focus group studies on selected Malaysian Chinese youth in Klang Valley
Get PDFThe Malaysian Chinese community is deeply influenced by traditional gender norms, shaped by both cultural and national policies. In Malaysia, LGBT issues are heavily prohibited, with homosexuality considered a criminal offense. Within the Chinese context, being LGBT is often viewed as shameful and dishonorable to the family, and LGBT individuals are perceived as abnormal. Older generations tend to resist accepting the LGBT community, while younger generations are generally more open-minded toward embracing new ideas and culture, including the LGBT identities. The rise of social media has provided the LGBT community with a safer and freer space to express themselves, affirm their rights and explore their gender identities. However, this has also led to negative effects, such as discrimination, marginalization, and the commodification of LGBT culture within the entertainment industry. LGBT subcultures are deeply intertwined with societal moral panics and the hegemony of capitalism, which prioritizes profit over cultural heritage. Through the findings, respondents aligned with integrated theories that successfully mapped Bai En as a male feminization social media influencer. By forming focus group discussions, Bai En was analyzed across various categories and caused impacts. Ultimately, Bai En play a significant role within the Malaysian Chinese community, especially among youth. However, respondents agreed that while he promotes LGBT subcultures, his style is not universally accepted and has generated mixed public perceptions
Smart condominium simulation using low code programming
Get PDFThis project provides a smart condominium simulation architecture with a goal to reduce the gap between user interactions, real-time sensor data, and automated functionalities within the simulated environment. This architecture focusses the accessibility and user-friendliness by using low-code programming.
One of the key contributions is the development of a scalable smart condominium model. The platform's modular design allows the combining of multiple devices, sensors, and functionality, which ensuring its ability to grow and develop with the development of smart condominium technology. Additionally, the use of Scalable Vector Graphics (SVG) helps to design pleasant and flexible simulation object representations.
Then, another way to point out the user-friendliness is the applying of the low-code programming platform Node-RED. With this platform, individuals with different levels of coding experience can simulate out the functions and interactions between the smart home devices. It brings the ability to instantly interact with the simulation, operate virtual equipment, establish the automation rules based on simulated sensor data, and track the effects of their actions, the platform places a high priority on an interactive user experience.
In the nutshell, this project enhances the field by developing an architecture for smart home simulation that is more flexible. This platform helps to develop a more sustainable and effective smart home technologies to explore the potential of smart homes