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Autonomous Decision-Making and Domain-Specific Intelligence in Edge–Cloud IoT Applications

Anum MehmoodCollege of Food Science and Engineering, Hainan University, Haikou City, ChinaBabayev ShavkatDepartment of Taxation and Taxation, Tashkent State University of Economics, Tashkent, UzbekistanMamatkhujaev OtabekDepartment of International Scientific Journals and Ratings, Alfraganus University, Tashkent, UzbekistanAkbar ToyirovDepartment of Information Technology and Exact Sciences, Termez University of Economics and Service, Termez, UzbekistanMukhammad KhabibullaevDepartment of Computer Science, Urgench State University, Urgench, UzbekistanSabirov SardorDepartment of General Professional Sciences, Mamun University, Khiva, Uzbekistan

2026

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ABI

Annotatsiya

This paper explores the concept of autonomous decision-making and domain-specific intelligence in Edge–Cloud IoT applications. It examines how artificial intelligence and machine learning techniques can be deployed across edge and cloud layers to support context-aware, adaptive, and autonomous operations. The study highlights architectural frameworks, decision-making mechanisms, and application-specific intelligence models that enhance system responsiveness, reliability, and resource efficiency. Furthermore, it discusses key challenges, including interoperability, security, data management, and computational constraints, and presents potential strategies to address them. The findings demonstrate that combining edge and cloud intelligence enables scalable, resilient, and intelligent IoT ecosystems capable of meeting the requirements of modern smart applications such as healthcare, industrial automation, smart cities, and autonomous transportation systems.

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DOI: 10.4018/979-8-2600-0615-3.ch002

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