ASROSAINTEK (Jurnal Sains, Informatika dan Teknologi)

THE ROLE OF ARTIFICIAL AUTONOMY IN THE INTERNET OF THINGS (IoT) ERA: A REVIEW OF PRIMITIVES, SENSING, THINKING, AND ACTION

2026-06-10T05:08:44+07:00

The rapid development of the Internet of Things (IoT) has triggered an urgent need for systems capable of autonomous action in complex and dynamic environments. In this context, artificial autonomy plays a key role as a key driver of adaptive intelligence embedded in IoT devices. This article presents a conceptual overview of the role of artificial autonomy by dividing it into four main pillars: primitives, sensing, thinking, and acting. This review describes how autonomous systems evolve from primitive control structures to intelligence capable of understanding context, making data-driven decisions, and executing responsive actions. Furthermore, it discusses the challenges of integrating autonomy into the IoT ecosystem, such as resource constraints, data security, and the need for interoperability and reliability. This review is expected to provide a foundation for the development of more intelligent, efficient, and autonomous IoT systems in the future. The Internet of Things (IoT) is a technology that connects various devices so they can communicate with each other and operate automatically. In this development, artificial autonomy plays a crucial role because it enables devices to make decisions and act without human intervention. This article discusses the role of artificial autonomy in four main aspects: basic capabilities (primitives), environmental sensing, information processing (thinking), and concrete actions. The discussion covers how smart devices can respond to situations autonomously and the challenges they face, such as technological limitations, security, and system reliability. This study provides an initial overview of the importance of artificial autonomy in supporting the advancement of a smarter and more efficient IoT.

A SYSML-BASED MODEL-BASED SYSTEMS ENGINEERING APPROACH FOR MANUFACTURING AUTOMATION SOFTWARE DEVELOPMENT: A SYSTEMATIC LITERATURE REVIEW

2026-06-18T04:41:02+07:00

Model-Based Systems Engineering (MBSE) has become an important approach for developing software-intensive manufacturing automation systems. This study examines the application of Systems Modeling Language (SysML) as a model-based framework to support the design, development, and validation of manufacturing automation software. SysML provides a standardized and visual modeling environment that enhances system specification, requirements traceability, and communication among multidisciplinary stakeholders. As a result, SysML-based MBSE has gained increasing attention as an effective methodology for managing the complexity of modern industrial systems and supporting digital transformation initiatives within Industry 4.0 environments (Estefan, 2021; Friedenthal et al., 2022; Holt & Perry, 2023; Vogel-Heuser et al., 2023). Through a systematic literature review and modeling analysis, the study identifies key benefits of SysML-based MBSE, including improved system traceability, modular architecture design, better integration of hardware and software components, and more effective verification and validation processes. The findings indicate that MBSE supported by SysML contributes to the development of reliable, scalable, and maintainable automation systems while supporting the adoption of Industry 4.0 technologies, such as Digital Twins and Cyber-Physical Systems (CPS). Furthermore, recent studies highlight that the integration of MBSE with emerging digital technologies improves interoperability, engineering efficiency, and lifecycle management across manufacturing environments (Lee et al., 2022; Tao et al., 2022; Ghosh et al., 2023; Korotkin et al., 2024; Borky & Bradley, 2025; Zhang et al., 2026).