Information Retrieval for IoT and WoT: State-of-the-Art, Taxonomy Framework, and Evolutionary Directions Manta Caro, Héctor Cristyan Fernández Luna, Juan Manuel Systematic Literature Review Internet of Things Information Retrieval Taxonomy Search Engines Protocols Surveys Web of Things The explosive growth of Internet of Things (IoT) and Web of Things (WoT) technologies, characterized by a vast diversity of devices and data formats, producing vast volumes of information at a high pace in real time necessitates a paradigm shift in Information Retrieval (IR) systems. Traditional IR struggles to navigate the dynamic landscapes of these interconnected environments. This work proposes a multi-dimensional taxonomy framework to bridge this critical gap. Our framework not only unifies existing classification approaches but also delves into the analysis of traditional IR sub-tasks, thereby establishing a cohesive foundation for future advancements in IR tailored to the evolving IoT/WoT landscape. We further contribute by identifying key challenges and posing open research questions, thus propelling the development of next-generation IR techniques specifically tailored to the intricate search demands of the evolving IoT and WoT cyber-world. 2025-01-17T08:27:06Z 2025-01-17T08:27:06Z 2024-12-25 journal article C. Manta-Caro, A. Caputo and J. M. Fernández-Luna, "Information Retrieval for IoT and WoT: State-of-the-Art, Taxonomy Framework and Evolutionary Directions," in IEEE Internet of Things Journal, doi: 10.1109/JIOT.2024.3522219. https://hdl.handle.net/10481/99480 10.1109/JIOT.2024.3522219 eng http://creativecommons.org/licenses/by-nc-nd/4.0/ open access Attribution-NonCommercial-NoDerivatives 4.0 Internacional IEEE