Transforming IoT with Data Analytics: Emerging Trends and Persistent Challenges
- DOI
- 10.2991/978-94-6463-858-5_172How to use a DOI?
- Keywords
- Data Analytics; IoT; Edge Computing; AI; Machine Learning; Real-time Processing; Privacy; Data Security; Interoperability
- Abstract
The Internet of Things (IoT) represents a paradigm shift in the way data is generated, transmitted, and utilized. The inclusion of IoT technologies in different sectors has resulted in large amounts of data, requiring advanced data analytics approaches to derive useful insights. This paper presents a comprehensive review of latest developments and ongoing issues in IoT data analytics. It discusses innovations such as edge computing, the integration of artificial intelligence and machine learning, improvements in data security, efforts towards standardization, real-time data processing, and advanced visualization tools. Additionally, it explores persistent challenges such as data volume, quality, integration, scalability, latency, and privacy. In addition to highlighting the shortcomings and suggesting potential areas for future research, the study attempts to give a thorough knowledge of the present state of IoT data analytics.
- Copyright
- © 2025 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Jaina Patel AU - Shraddha Korvadiya AU - Chetan K. Verma AU - Dinesh Patel PY - 2025 DA - 2025/11/04 TI - Transforming IoT with Data Analytics: Emerging Trends and Persistent Challenges BT - Proceedings of International Conference on Computer Science and Communication Engineering (ICCSCE 2025) PB - Atlantis Press SP - 2060 EP - 2069 SN - 2352-538X UR - https://doi.org/10.2991/978-94-6463-858-5_172 DO - 10.2991/978-94-6463-858-5_172 ID - Patel2025 ER -