Subhas Sarma Neog
Papers
1
Total Citations
16
H-Index
1
About
Subhas Sarma Neog is a researcher at the forefront of industrial automation and predictive maintenance, with a particular focus on the challenges of implementing Industry 4.0 solutions in remote and resource-constrained environments. His most-cited work, "Implementation of Predictive Maintenance Systems in Remotely Located Process Plants under Industry 4.0 Scenario" (2019), has garnered 16 citations and addresses a critical gap in the literature: how to deploy advanced, data-driven maintenance strategies in settings where connectivity, infrastructure, and technical expertise are limited. Neog’s contributions lie in bridging theoretical frameworks with practical, scalable architectures—combining IoT sensor networks, edge computing, and machine learning models to enable real-time fault detection and prognosis without relying on constant cloud access. This work has implications for industries ranging from oil and gas to agriculture, where remote assets are common. By tackling the intersection of operational reliability and digital transformation, Neog has established himself as a key voice in making Industry 4.0 accessible beyond well-connected factories, offering a roadmap for safer, more efficient, and cost-effective plant operations in the world’s most challenging locations.
Research Focus
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Top Papers
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