{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,17]],"date-time":"2025-12-17T13:07:29Z","timestamp":1765976849678,"version":"3.44.0"},"reference-count":42,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,9,24]],"date-time":"2025-09-24T00:00:00Z","timestamp":1758672000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Commun. Netw."],"abstract":"<jats:p>The rapid expansion of IoT devices has led to increasingly complex networks, such as Smart Campuses, where ensuring interoperability, scalability, and energy efficiency becomes crucial. Existing middleware solutions, such as Z-Wave and LoRaWAN, have proven effective in specific applications but fail to address the diverse demands of dense and heterogeneous Internet of Things (IoT) environments. The limited scalability of Z-Wave (232 devices) and the high latency of LoRaWAN (150\u00a0ms) highlight the need for a more comprehensive solution. This study presents a middleware designed to overcome these limitations through a modular, microservices-based architecture. The system enables dynamic protocol translation and adaptive resource management, demonstrating robust performance with 120 devices deployed and validated in a Smart Campus scenario. Additionally, simulations using NS-3 extended the evaluation to 500 virtual devices, supporting scalability analysis under varying traffic and heterogeneity conditions. The middleware incorporates optimization strategies, such as data compression and adaptive task prioritization, to improve energy efficiency and operational performance. Experimental validation in a controlled environment demonstrated a 26.7% reduction in power consumption for optimized nodes, achieving an average of 60\u00a0W compared to 80\u00a0W for non-optimized nodes. Response times averaged 130\u00a0ms on optimized nodes, outperforming LoRaWAN while achieving a 94% interoperability success rate. Deployment in a real Smart Campus confirmed the robustness of the middleware, maintaining consistent performance under dynamic conditions and in the presence of external interference.<\/jats:p>","DOI":"10.3389\/frcmn.2025.1672617","type":"journal-article","created":{"date-parts":[[2025,9,24]],"date-time":"2025-09-24T05:40:44Z","timestamp":1758692444000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Modular middleware for IoT: scalability, interoperability and energy efficiency in smart campus"],"prefix":"10.3389","volume":"6","author":[{"given":"Rommel","family":"Gutierrez","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"William","family":"Villegas-Ch","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jaime","family":"Govea","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2025,9,24]]},"reference":[{"key":"B1","first-page":"212","article-title":"Adaptation layer towards integration of ZigBee and IP stacks","volume-title":"2017 international conference on automatic control and dynamic optimization techniques (ICACDOT)","author":"Alaparthi","year":"2017"},{"key":"B2","doi-asserted-by":"publisher","first-page":"648","DOI":"10.3390\/s20030648","article-title":"LoRaWAN for smart city IoT deployments: a long-term evaluation","volume":"20","author":"Basford","year":"2020","journal-title":"Sensors Switz."},{"key":"B3","doi-asserted-by":"publisher","first-page":"2149","DOI":"10.1007\/s41870-023-01716-7","article-title":"Dynamic performance modeling framework for QoS-aware 5G-based IoT-edge systems","volume":"16","author":"Bebortta","year":"2024","journal-title":"Int. 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