18th Asian Conference on Intelligent Information and Database Systems
13-15 April 2026, Kaohsiung, Taiwan
Submit to this session
13-15 April 2026, Kaohsiung, Taiwan
AMAS 2026
Special Session onAdvanced Manufacturing and Agricultural Systems
at the 18th Asian Conference on Intelligent Information and Database Systems (ACIIDS 2026)13-15 April 2026, Kaohsiung, Taiwan
Special Session Organizers
Prof. Chao-Chun Chen
National Cheng Kung University
Taiwan
E-mail: chencc@imis.ncku.edu.tw
Prof. Chao-Lieh Chen
National Kaohsiung University of Science and Technology
Taiwan
E-mail: frederic@nkust.edu.tw
Prof. Narn-Yih Lee
National Cheng Kung University
Taiwan
E-mail: nylee@gs.ncku.edu.tw
Dr Yung-Chien Chou
Department of Mechatronics Engineering
Taiwan
E-mail: ycc@cc.ncue.edu.tw
National Cheng Kung University
Taiwan
E-mail: chencc@imis.ncku.edu.tw
Prof. Chao-Lieh Chen
National Kaohsiung University of Science and Technology
Taiwan
E-mail: frederic@nkust.edu.tw
Prof. Narn-Yih Lee
National Cheng Kung University
Taiwan
E-mail: nylee@gs.ncku.edu.tw
Dr Yung-Chien Chou
Department of Mechatronics Engineering
Taiwan
E-mail: ycc@cc.ncue.edu.tw
Objectives and topics
The global manufacturing and agricultural sectors are entering a new era of digital transformation driven by intelligent information systems, AI-powered analytics, and cyber-physical integration. These industries are evolving into interconnected ecosystems that depend on intelligent data systems to achieve automation, adaptability, and sustainability.
In advanced manufacturing, the rise of Industry 4.0 and the Industrial Internet of Things (IIoT) has created data-rich environments where machines, sensors, and control systems continuously interact. Leveraging this data through machine learning, deep learning, and optimization algorithms enables predictive maintenance, process optimization, quality assurance, and real-time decision-making. However, these advancements bring challenges such as integrating heterogeneous data, ensuring privacy and security, achieving interoperability across legacy systems, and maintaining transparency in AI-driven decisions.
Meanwhile, agriculture is undergoing its own digital revolution—often referred to as Agriculture 4.0—where precision farming, smart irrigation, drone-based monitoring, and autonomous equipment generate vast streams of data. Intelligent use of this information supports yield prediction, early disease detection, resource efficiency, and environmental sustainability. Agricultural data systems must also contend with dynamic, unstructured, and context-sensitive information shaped by weather, soil conditions, and biological variability.
The convergence of these two domains presents unique opportunities for cross-sector innovation. Advances in AI, IoT, edge computing, digital twins, data fusion, and cyber-physical systems can be mutually beneficial—lessons from industrial automation can enhance smart farming, while agricultural resilience and sustainability can inform greener industrial practices.
In advanced manufacturing, the rise of Industry 4.0 and the Industrial Internet of Things (IIoT) has created data-rich environments where machines, sensors, and control systems continuously interact. Leveraging this data through machine learning, deep learning, and optimization algorithms enables predictive maintenance, process optimization, quality assurance, and real-time decision-making. However, these advancements bring challenges such as integrating heterogeneous data, ensuring privacy and security, achieving interoperability across legacy systems, and maintaining transparency in AI-driven decisions.
Meanwhile, agriculture is undergoing its own digital revolution—often referred to as Agriculture 4.0—where precision farming, smart irrigation, drone-based monitoring, and autonomous equipment generate vast streams of data. Intelligent use of this information supports yield prediction, early disease detection, resource efficiency, and environmental sustainability. Agricultural data systems must also contend with dynamic, unstructured, and context-sensitive information shaped by weather, soil conditions, and biological variability.
The convergence of these two domains presents unique opportunities for cross-sector innovation. Advances in AI, IoT, edge computing, digital twins, data fusion, and cyber-physical systems can be mutually beneficial—lessons from industrial automation can enhance smart farming, while agricultural resilience and sustainability can inform greener industrial practices.
The scope of this special session includes, but is not limited to the following topics:
- Data-centric and AI-driven system architectures
- Intelligent data systems for manufacturing and agriculture
- Adaptive and transparent industrial operations
- Sustainability in digital transformation
- Smart food production systems
- Cross-sector collaboration models
- Decision-support and intelligent information frameworks
- Future trends in data and knowledge integration
ACIIDS 2026 important dates
Paper submission: December 15, 2025 (hard deadline)
Notification of acceptance: January, 2026
Camera-ready papers: February, 2026
Registration & payment: February, 2026
Conference date: April 13-15, 2026
Notification of acceptance: January, 2026
Camera-ready papers: February, 2026
Registration & payment: February, 2026
Conference date: April 13-15, 2026