Knowledge Mapping And Bibliometric Analysis Of ESP32-Based Iot Heat Index Monitoring For Smart Classrooms: Research Trends, Collaboration Networks, And Future Research Directions (2010–2025)

Abstract

Classrooms in tropical, resource-constrained settings are increasingly exposed to heat stress, and the ESP32 microcontroller has emerged as a low-cost platform for building the Internet of Things (IoT) sensing nodes needed to monitor it. However, the scholarly literature that would situate ESP32-based heat index monitoring for smart classrooms within the broader IoT research landscape remains fragmented. This study presents an expanded, large-scale bibliometric and science-mapping analysis of 17,831 IoT-related journal articles indexed on Lens.org between 2010 and 2025, processed with the bibliometrix/Biblioshiny R package and VOSviewer following a four-stage retrieval, preprocessing, analysis, and interpretation workflow. The dataset shows a 48.14% annual growth rate and an average of 33.94 citations per document, with annual output rising from fewer than 20 documents in 2010 to a peak of 3,547 in 2022, before dipping in 2023–2024 and rebounding to 2,911 in 2025. Logistic growth modeling estimates a publication saturation ceiling of 21,732 cumulative documents, with the field’s peak annual output already reached (2022.4) and 84.9% of variance explained. Sensors (Basel, Switzerland) dominates the source landscape with nearly 3,000 cumulative articles, while the Chinese Academy of Sciences leads institutional output (250 documents); at the individual-researcher level, output is led by Do-Hyeun Kim (37 documents), Rajesh Singh (27), and Zhong Lin Wang (26), and productive authorship clusters into nationally homogeneous co-authorship groups (Chinese, Korean) with minimal cross-cluster bridging. A country level choropleth of publication totals confirms this concentration at the macro scale, both the United States and China are the two major nodes of output with no publications from Southeast Asia indicated in light. Strategic thematic map identifies the themes "IoT, sensors, smart city" and "internet of things, energy efficiency, wireless sensor networks" as motor themes, while keyword co-occurrence map with its temporal overlay indicates a clear transition from network-infrastructure related keywords (2020–2021) to wearable, biosensing and well-being related keywords (2022–2023). Importantly, "heat index", "ESP32" and "smart classroom" never join the keyword network as high-frequency, independent keywords pointing to this application type as a nascent subspecialty within a rapidly evolving parent field. The study concludes with five concrete future-research directions — standardized sensor design, predictive analytics, energy-autonomous deployment, expanded tropical/Southeast Asian participation, and open longitudinal datasets — to help close this gap.