Development of microservices with machine learning algorithms for natural ventilation control in smart buildings

Building and Environment 2026 Open access

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Authors: Wei Zhang, Leslie Keith Norford, Wentao Wu
DOI: 10.1016/j.buildenv.2026.114420
Cited by: 1
References: 40

Abstract

• Develop novel microservices for smart control of natural ventilation and TABS • Microservices incorporate IoT network API and Edge computing Weather Forecast API • Machine learning algorithms effectively maintain indoor CO2 below 800-900 ppm • Augmented TABS control saves heating energy and prevents overheating (

Fields of Study & Subjects

Software System Performance and Reliability Air Quality Monitoring and Forecasting IoT and Edge/Fog Computing

Publication details

Journal / source
Building and Environment
Publisher
Elsevier BV
Volume
295
Pages
114420–114420
Publication date
27 February 2026
Language
EN