UCSI University

The proliferation of non-cooperative aerial targets, particularly low altitude-slow-speed small RCS drones, presents a complex challenge for airspace security. Detection and identification of non-cooperative aerial objects is an intensive area of research. The aim of this article is to carry out a structured review of UAV/drones, fixed wing aircraft and other non-cooperative aerial targets’ detection and classification using machine learning (ML) algorithms. This article presents a systematic review of 184 recent studies (2019–2025) covering five key sensing modalities: Radar (RCS, Micro-Doppler, HRRP), Passive Sensing (5G/Wi-Fi/Radio Frequency (RF)), Acoustic sensing, Computer Vision and multi-modal sensing. Although individual sensing modalities have been extensively studied, existing reviews often lack a holistic operational assessment of multi-modal integration. Additionally, the review work introduces a novel operational suitability framework that maps each modality against critical deployment constraints, including detection range, Line of Sight (LOS) requirements, and environmental robustness. Furthermore, authors critically analyze the transition from classical statistical methods and outdated deep learning architectures to advanced deep learning architectures, specifically highlighting the emergence of vision transformers (ViT) and niche technologies such as integrated sensing and communications (ISAC). Finally, the review identifies persistent gaps in artificial intelligence (AI) based non-cooperative target recognition research and proposes a roadmap for future research in multi-modal machine learning (MML) and sensor fusion pipelines. Moreover, this review work would direct the research effort for further enhancing the aerospace, human safety, and important installations’ security.

Purpose This study examines how artificial intelligence (AI)-based personalization, the Internet of Things (IoT)-enabled rooms, augmented reality (AR) and virtual reality (VR) experiences, and sustainable smart technologies influence guests' digital well-being, experiential value, and loyalty to smart hotels across Southeast Asia. It also explores the moderating role of digital literacy in shaping these relationships. Design/methodology/approach Data were collected from 552 guests who stayed in smart hotels in Bali (Indonesia), Kuala Lumpur (Malaysia) and Phuket (Thailand). Partial least squares structural equation modeling was used to test the hypothesized relationships among smart hotel technologies, digital well-being, experiential value, loyalty, and digital literacy. Findings The results show that AI personalization, IoT-enabled rooms, AR/VR experiences and sustainable technologies significantly enhance digital well-being. Digital well-being further increases experiential value and intention to reuse smart hotel services. digital literacy strengthens the relationship between digital well-being and reuse intention, demonstrating its importance in shaping positive smart hospitality experiences. Research limitations/implications The study's limitations include a sample skewed toward younger, digitally literate travelers, limiting generalizability to older cohorts. The use of convenience sampling may also introduce bias, and the cross-sectional design restricts causal inference. Differences in smart hotel technology usage, language, and digital literacy across destinations could further influence outcomes. Additionally, reliance on self-reported data raises concerns about common method variance. The model's modest explanatory power for reuse intention suggests that other factors, such as service quality and cultural norms, may play stronger roles. Future research should address these limitations using longitudinal designs and more diverse samples. Practical implications The findings provide guidance for hospitality managers, tourism planners, and technology developers. Designing intuitive, sustainable, and user-friendly smart systems can enhance guests' well-being and loyalty. Social implications The study highlights the social implications of smart hotel technologies by promoting digital well-being, which extends beyond individual benefits to a broader public good. Guests who experience less digital fatigue are more likely to engage in cultural, local, and eco-friendly activities, fostering greater community involvement. For example, AR and AI systems can direct tourists to local markets, cultural tours, and sustainable practices, benefiting host communities. These practices align with SDGs 8 and 12, encouraging responsible consumption and equitable growth. Ultimately, the integration of digital well-being supports a more inclusive and socially responsible tourism ecosystem. Originality/value To the best of the authors' knowledge, this paper presents the first empirical evidence from Southeast Asia demonstrating how smart hotel technologies enhance digital well-being and loyalty through experiential value. By integrating Service-Dominant Logic, the Experience Economy, and Digital Well-Being Theory, a human-centered framework for value co-creation in smart hospitality is advanced.

The rapid expansion of the e-commerce industry in Malaysia has led to a significant increase in packaging consumption, particularly plastic, which contributes to growing environmental concerns. Although sustainable packaging alternatives are accessible and consumer awareness regarding environmental protection is increasing, a gap exists between consumers’ awareness and their actual purchasing behavior concerning products with sustainable packaging. This study aims to identify and analyze the key factors influencing the intention to purchase products with sustainable packaging in the context of e-commerce. Based on the Theory of Planned Behavior (TPB), the research investigates the role of customer perception, government initiatives, subjective norms, willingness to pay, and environmental awareness. A quantitative research design was employed, and data were gathered through structured questionnaires distributed to 384 respondents. The data were analyzed using the Statistical Package for the Social Sciences (SPSS). The results demonstrate that customer perception, government involvement, willingness to pay, and environmental awareness significantly influence consumer purchase intention. However, subjective norms do not demonstrate a significant effect. These findings offer important insights for e-commerce businesses and policymakers seeking to promote sustainable consumption behavior and implement effective strategies for environmental sustainability. By applying these insights, stronger cooperation between businesses, packaging manufacturers, and policymakers can accelerate the transition toward sustainable packaging. This, in turn, will help reduce plastic waste, benefiting both the environment and the economy.