Published March 19, 2026 | Version v1
Journal article Open

Low-cost Smart Home Design and Evaluation for Internet of Things and Supervisory Control Education

  • 1. Department of Business Industry and Information Technology, Clovis Community College, Fresno, CA
  • 2. Department of Engineering Technology & Industrial Distribution, Texas A&M University, College Station, TX
  • 3. Department of Electrical & Computer Engineering, Texas A&M University, College Station, TX

Description

The rapid evolution of Industry 4.0 and the Industrial Internet of Things (IIoT) has created a significant demand for engineers and technicians skilled in embedded networking, system integration, and supervisory control. However, academic institutions often struggle to provide hands-on training in these areas due to the prohibitive cost and proprietary nature of commercial industrial training rigs. This paper presents the design and evaluation of a low-cost educational platform that utilizes a smart home context to demonstrate fundamental industrial SCADA (Supervisory Control and Data Acquisition) concepts. By leveraging commercial off-the-shelf (COTS) components—including ESP32 microcontrollers and Raspberry Pi servers arranged in an MQTT-centric architecture—the proposed framework bridges the gap between simple sensor-to-cloud prototyping and complex industrial automation. The study details the system design, which supports essential industrial functions such as alarm management, set-point control, and historical data trending via a standard publish–subscribe protocol. It embeds this platform in a structured laboratory sequence. Financial analysis demonstrates that the platform can be constructed for approximately $185 per station, representing a cost reduction of nearly 80% compared to entry-level commercial trainers. Entry-exit survey data from students indicate measurable gains in SCADA/IIoT knowledge, tool familiarity, and career interest, suggesting that this architecture offers a technically feasible, scalable, and pedagogically effective solution for engineering and technician programs seeking to deploy rigorous IIoT laboratory experiences to larger student cohorts without relying on restrictive vendor licenses.

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Additional details

Funding

U.S. National Science Foundation
Technician Training for Industry 4.0 Technologies 2202201