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An Adaptive Geo-Intelligent System Integrating AI and IoT for Sustainable Smart Manufacturing
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Author(s): Duggirala Aravind (ASET College of Science and Technology, India), N. V. Suresh (ASET College of Science and Technology, India), R. N. Ravikumar (Marwadi University, India), E. Eswara Reddy (CMR University, India), Vanathi GopiKrishna (Avichi College of Arts and Science, India)and Kasukurthi Aravind (ASET College of Science and Technology, India)
Copyright: 2027
Pages: 36
Source title:
GIS Applications for Enhancing Sustainable Operational Performance of Manufacturing Industries
Source Author(s)/Editor(s): Kamalakanta Muduli (Papua New Guinea University of Technology, Papua New Guinea), Sujoy Kumar Jana (Papua New Guinea University of Technology, Papua New Guinea), Rashmi Prava Das (CV Raman Global University, Odisha, India)and Indrajit Pal (Asian Institute of Technology, Thailand)
DOI: 10.4018/979-8-3373-7941-8.ch001
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Abstract
The chapter introduces an adaptive geo-intelligent system that combines Geographic Information Systems (GIS), Artificial Intelligence (AI), and Internet of Things (IoT) in order to aid the spatially enabled decision-making in the current manufacturing context. The framework uses sensor data based on location, predictive analytics, and geo-AI models to track the movements of energy, emissions, materials and equipment performance. Through the generation of persistent spatial-temporal intelligence, it enhances the minimization of waste, mitigation of risks, supply chain responsiveness, and compliance with the environment. The chapter also outlines the principles of architecture design, implementation journey, and application use cases of sustainable manufacturing operations. Future research topics lead to the opportunities of digital twins, autonomous optimisation, the creation of scalable geo-intelligent networks of Industry 5.0 ecosystems.
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