Inoj Neupane
Papers
2
Total Citations
14
H-Index
2
About
Inoj Neupane is a rising researcher at the forefront of intelligent indoor positioning systems, with a focused expertise in fusing Wi-Fi fingerprinting with machine learning to solve critical localization challenges. His work directly addresses the limitations of GPS in complex indoor environments, a key bottleneck for the Internet of Things (IoT) and the emerging Industry 5.0 paradigm. Neupane’s major contributions include pioneering the use of Convolutional Neural Networks (CNNs) for resource-constrained IoT devices, demonstrating how deep learning can achieve high-accuracy indoor localization without requiring expensive hardware. His research also introduces novel concepts for human-robot collaboration in smart factories, where precise indoor positioning is essential for safety and efficiency. Both of his most-cited papers, published in 2023 and 2024, have already garnered 7 citations each, signaling growing recognition in the field. By bridging the gap between advanced AI and practical, low-power IoT systems, Neupane is laying the groundwork for the next generation of context-aware, autonomous environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2Indoor Positioning Using Wi-Fi and Machine Learning for Industry 5.07 citations · 2023