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Mohapatra, N.P., Pattanaik, S.R., Mohapatra, A. and Mishra, S.K., 2024, February. Smart Automated parking system employing Internet of Things and machine learning methods to detect vehicles. In 2024 International Conference on Emerging Systems and Intelligent Computing (ESIC) (pp. 763-767). IEEE.
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Mohapatra, N.P. and Patjoshi, R.K., Energy Harvesting Clustering Methodology for Lifetime Enhancement of Wireless Sensor Networks.
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Mohapatra, N.P. and Nayak, M., 2023, March. An Energy-Saving Approach for Routing in Wireless Sensor Networks with ML-Based Faulty Node Detection. In International Conference on Advances in IoT and Security with AI (pp. 309-322). Singapore: Springer Nature Singapore.
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Mohapatra, N.P. and Nayak, M., 2023. An Energy-Saving Approach for Routing. Advances in IoT and Security with Computational Intelligence: Proceedings of ICAISA 2023, Volume 1, 755, p.309.
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Priyadarsini, N., Nanda, P., Devi, S. and Mohapatra, S., 2022. Sarcopenia: an age-related multifactorial disorder. Current Aging Science, 15(3), pp.209-217.
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Mohapatra, N.P., Jena, M. and Dash, S.K., 2016. Improved Stability with Improved Energy Efficient Stable Election Method for Wireless Sensor Networks. International Journal, 5(4).
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Mohapatra, N.P., Jena, J. and Sahu, S.K., 2015. Improving the Life of the Wireless Sensor Network using Energy Harvesting Clustering. International Journal of Computer Applications, 114(10), pp.37-43.
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Mohapatra, N.P., Pattanaik, S.R., Abebe, M. and Chiang, M.J., 2025. 4 Computational. Computational Intelligence in Industry 4.0 and 5.0 Applications: Trends, Challenges and Applications, p.101.
Industry 4.0 and 5.0 applications will revolutionize production, enabling smart manufacturing machines to interact with their environments. These machines will become self-aware, self-learning, and capable of real-time data interpretation for self-diagnosis and prevention of production issues. They will also self-calibrate and prioritize tasks to enhance production quality and efficiency.
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