Research on the Application of Wireless Sensor Networks in Smart Home Environments: Challenges, Strategies, and Prospects
DOI:
https://doi.org/10.54097/dm0hnw06Keywords:
Smart home, Wireless sensor, networks.Abstract
Wireless Sensor Networks (WSNs) have become a crucial component in the telecommunications sector, with significant potential for innovation, particularly in smart home environments. This paper provides an overview of the research progress and current status of WSNs in smart home applications, emphasizing their background, significance, and underlying theories. The study analyzes recent literature, highlighting the latest methods and trends in WSNs for smart homes, and identifies key challenges such as ethical privacy concerns, technological standards, and interoperability issues. The application of WSNs in smart homes encompasses remote control, monitoring, activity recognition, and security, with researchers continuously seeking breakthroughs to optimize these networks. However, challenges remain, including the integration of various wireless protocols, energy efficiency management, and the safeguarding of security and privacy. Addressing these challenges is critical for advancing the application of WSNs in smart homes, and further research is necessary to overcome the existing limitations and enhance their effectiveness in this domain.
Downloads
References
[1] H. Zhang, M. Li, M. Yang, C. Zhou, Dual Mode Data Acquisition and Analysis Based on Deep Learning for Smart Home Networks, IEEE Internet of Things Journal 11 (2024) 1 - 10.
[2] M. A. Jamshed, K. Ali, Q. H. Abbasi, M. A. Imran, M. Ur Rehman, Challenges, applications and future of wireless sensors in internet of things: a review, IEEE Sensors Journal 22 (2022) 5482-5494.
[3] B. Akhmetzhanov, D. Yedilkhan, A. Medeshova, K. Rabie, N. Zhakiyev, Multi-Layer Integration of Heterogeneous Wireless Sensor Networks for Smart Home Optimization, Procedia Computer Science 231 (2024) 666 - 671.
[4] J. Zhu, D. Wang, Y. Zhao, Design of smart home environment based on wireless sensor system and artificial speech recognition, Measurement: Sensors 33 (2024) 101090.
[5] O. Alibrahim, S. Padmanaban, M. Khan, O. Khattab, B. Alothman, C. Joumaa, Deep Transfer Learning-Enabled Energy Management Strategy for Smart Home Sensor Networks, IEEE Transactions on Industry Applications 59 (2023) 1 - 10.
[6] X. Zhu, Y. Huang, X. Wang, and R. Wang, "Emotion recognition based on brain-like multimodal hierarchical perception," Multimed. Tools Appl., vol. 83, no. 18, pp. 56039-56057, 2024.
[7] L. Cao, Z. Wang, Y. Yue, Analysis and prospect of the application of wireless sensor networks in ubiquitous power internet of things, Computational Intelligence and Neuroscience 1 (2022) 9004942.
[8] Z. Song, W. Ye, Z. Chen, Z. Chen, M. Li, W. Tang, Z. Fan, Wireless self-powered high-performance integrated nanostructured-gas-sensor network for future smart homes, ACS Nano 15 (2021) 7659 - 7667.
[9] N. Y. Philip, J. J. Rodrigues, H. Wang, S. J. Fong, J. Chen, Internet of Things for in-home health monitoring systems: Current advances, challenges and future directions, IEEE Journal on Selected Areas in Communications 39 (2021) 300 - 310.
[10] Wang R., Zhu J., Wang S., Wang T., Huang J., Zhu X. Multi-modal emotion recognition using tensor decomposition fusion and self-supervised multi-tasking. International Journal of Multimedia Information Retrieval, 2024, 13 (4): 39.
Downloads
Published
Issue
Section
License
Copyright (c) 2024 Highlights in Science, Engineering and Technology

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.







