Anandan, R., Gopalakrishnan, S., Pal, S. & Zaman, N. (eds) Industrial internet of things (IIoT): intelligent analytics for predictive maintenance (Wiley, 2022).
Ong, K. S. H., Wang, W., Hieu, N. Q., Niyato, D. & Friedrichs, T. Predictive maintenance model for IIoT-based manufacturing: A transferable deep reinforcement learning approach. IEEE Internet Things J. 9 (17), 15725–15741 (2022).
Rieger, T., Regier, S., Stengel, I. & Clarke, N. Fast predictive maintenance in industrial internet of things (iiot) with deep learning (dl): A review. In CEUR workshop proceedings (Vol. 2348, p. 69). (2019).
Hore, U. W. & Wakde, D. G. Intelligent Predictive Maintenance for Industrial Internet of Things (IIoT) Using Machine Learning Approach. In International Conference on Intelligent Cyber Physical Systems and Internet of Things (pp. 897–913). Cham: Springer International Publishing. (2022), August.
Wang, H., Zhang, W., Yang, D. & Xiang, Y. Deep-learning-enabled predictive maintenance in industrial internet of things: Methods, applications, and challenges. IEEE Syst. J. 17(2), 2602–2615 (2022).
Alhuqayl, S. O., Alenazi, A. T., Alabduljabbar, H. A. & Haq, M. A. Improving predictive maintenance in industrial environments via IIoT and machine learning. International J. Adv. Comput. Sci. & Applications, 15(4). (2024).
Zheng, H., Paiva, A. R. & Gurciullo, C. S. Advancing from predictive maintenance to intelligent maintenance with ai and iiot. arXiv preprint arXiv:2009.00351. (2020).
Alabadi, M., Habbal, A. & Guizani, M. An innovative decentralized and distributed deep learning framework for predictive maintenance in the industrial Internet of Things. IEEE Internet Things Journal (2024).
Rajawat, A. S. et al. Cognitive adaptive systems for industrial internet of things using reinforcement algorithm. Electronics 12 (1), 217 (2023).
Jia, Z. & Ren, L. A cloud-edge adaptive framework for equipment predictive maintenance in IIoT. In IECON 2024-50th Annual Conference of the IEEE Industrial Electronics Society (pp. 1–6). IEEE. (2024), November.
Bellavista, P., Della Penna, R., Foschini, L. & Scotece, D. Machine learning for predictive diagnostics at the edge: An IIoT practical example. In ICC 2020–2020 IEEE International Conference On Communications (ICC) (pp. 1–7). IEEE. (2020), June.
Hafez, L., Elakkad, E. & Gamil, M. A Study on the Impact of Logistics Service Quality on the Satisfaction and Loyalty of E-Shoppers in Egypt. Open J. Bus. Manag. 9, 2464–2478. https://doi.org/10.4236/ojbm.2021.95133 (2021).
Rosati, R. et al. From knowledge-based to big data analytic model: A novel IoT and machine learning based decision support system for predictive maintenance in Industry 4.0. J. Intell. Manuf. 34(1), 107–121 (2023).
Ong, K. S. H., Wang, W., Niyato, D. & Friedrichs, T. Deep-reinforcement-learning-based predictive maintenance model for effective resource management in industrial IoT. IEEE Internet Things J. 9 (7), 5173–5188 (2021).
Gomide, I. et al. Experimental Study on the Behavior of a Solar-Assisted Heat Pump Operating Under Different Water Demand Conditions. Proceedings of COBEM 2025 https://doi.org/10.26678/ABCM.COBEM2025.COB2025-0463 (2025).
Xiong, D. D. et al. Nitidine chloride inhibits the progression of hepatocellular carcinoma by suppressing IGF2BP3 and modulates metabolic pathways in an m6A-dependent manner. Mol. Med. 31, 4747 (2025).
Youssef, M. H. et al. Relationship Between Obesity, Stress, and Age of Menarche Among Adolescent Female Students in Al-Madinah, Saudi Arabia. Cureus 17, e93739. https://doi.org/10.7759/cureus.93739 (2025).
Al-Anzi, F. S., Al-Anzi, A. F. & Sarath, S. Predictive maintenance in industrial IoT (IIoT). In International Conference on Medical Imaging, Electronic Imaging, Information Technologies, and Sensors (MIEITS 2024) (Vol. 13188, pp. 96–105). SPIE. (2024), June.
Manikandan, S., Elakiya, E., Rajheshwari, K. C. & Sivakumar, K. Efficient energy consumption in hybrid cloud environment using adaptive backtracking virtual machine consolidation. Sci. Rep. 14, 22869 (2024).
Manivannan, R., Manikandan, S., Vadivel, R. & Sophana Jennifer, S. Location based access privileges and controlling the clustering in sustainable 5G challenges. Salud, Ciencia y Tecnología – Serie de Conferencias [Internet]. 3 [cited 2024 Mar. 21];3:402 (2024) Jan.
El-kenawy, E.-S.M., Alhussan, A. A., Mattar, E. A. & Radwan, M. Feature selection and hyperparameter tuning in transformer-based deep learning models for photovoltaic power forecasting using the Swordfish Movement Optimization Algorithm (SMOA). Int. J. Electr. Power Energy Syst. https://doi.org/10.1016/j.ijepes.2025.111509 (2026).
El-Sayed, M. et al. Smart City electricity load forecasting using greylag goose optimization-enhanced time series analysis (Arabian Journal for Science and Engineering, 2025).

