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The rapid expansion of the Internet of Things (IoT) demands scalable, efficient, and user-friendly gateway solutions that seamlessly connect resource-constrained edge devices to cloud services. Low-cost, widely available microcontrollers, such as the ESP32 and its ecosystem peers, offer integrated Wi-Fi/Bluetooth connectivity, low power consumption, and a mature developer toolchain at a bill of materials cost of only a few dollars. For smart-home deployments where budgets, energy consumption, and maintainability are critical, these characteristics make MCU-class gateways a pragmatic alternative to single-board computers, enabling always-on local control with minimal overhead. This paper presents the design and implementation of an embedded IoT gateway powered by the ESP32 microcontroller. By using lightweight communication protocols such as Message Queuing Telemetry Transport (MQTT) and REST APIs, the proposed architecture supports local control, distributed intelligence, and secure on-site data storage, all while minimizing dependence on cloud infrastructure. A real-world deployment in an educational building demonstrates the gateway’s capability to monitor energy consumption, execute control commands, and provide an intuitive web-based dashboard with minimal resource overhead. Experimental results confirm that the solution offers strong performance, with RAM usage ranging between 3.6% and 6.8% of available memory (approximately 8.92 KB to 16.9 KB). The initial loading of the single-page application (SPA) results in a temporary RAM spike to 52.4%, which later stabilizes at 50.8%. These findings highlight the ESP32’s ability to serve as a functional IoT gateway with minimal resource demands. Areas for future optimization include improved device discovery mechanisms and enhanced resource management to prolong device longevity. Overall, the gateway represents a cost-effective and vendor-agnostic platform for building resilient and scalable IoT ecosystems.
Details
Software;
Interoperability;
Internet of Things;
Communication;
Data processing;
Smart buildings;
Architecture;
Automation;
Resource management;
Ecosystems;
Energy consumption;
Maintainability;
Data integrity;
Embedded systems;
Artificial intelligence;
Edge computing;
Cloud computing;
Decision making;
Random access memory;
Smart houses;
Energy efficiency;
Connectivity;
Data storage;
Environmental monitoring;
Wireless access points;
Queueing
; Papias Ioannis 2
; Christakis Konstantinos 2
; Dimitropoulos Nikos 2
; Marinakis Vangelis 2
1 HOLISTIC SA, 507 Mesogeion Av Ag. Paraskevi, 153 43 Athens, Greece
2 Decision Support Systems Laboratory, School of Electrical & Computer Engineering, National Technical University of Athens, 9 Iroon Polytechniou str., 157 80 Athens, Greece; [email protected] (I.P.); [email protected] (K.C.); [email protected] (N.D.); [email protected] (V.M.)