PLUG-N-HARVEST Architecture for Secure and Intelligent Management of Near-Zero Energy Buildings

This paper presents the PLUG-N-HARVEST architecture based on cloud AI systems and security-by-design IoT networks to manage near-zero ADBE constructions in both residential and commercial buildings. To demonstrate the PLUG-N-HARVEST architecture, three different real-world pilots have been considered in Germany, Greece and Spain.
Authors: Rafael Marin-Perez, Iakovos T. Michailidis, Dan Garcia-Carrillo, Christos D. Korkas, Elias B. Kosmatopoulos and Antonio Skarmeta
 
Journal Title: Sensors
 
ISSN: 1424-8220 (Print)
 
Publisher: MDPI AG
 
Abstract
 
Building Automation (BA) is key to encourage the growth of more sustainable cities and smart homes. However, current BA systems are not able to manage new constructions based on Adaptable/Dynamic Building Envelopes (ADBE) achieving near-zero energy-efficiency. The ADBE buildings integrate Renewable Energy Sources (RES) and Envelope Retrofitting (ER) that must be managed by new BA systems based on Artificial Intelligence (AI) and Internet of Things (IoT) through secure protocols. This paper presents the PLUG-N-HARVEST architecture based on cloud AI systems and security-by-design IoT networks to manage near-zero ADBE constructions in both residential and commercial buildings. To demonstrate the PLUG-N-HARVEST architecture, three different real-world pilots have been considered in Germany, Greece and Spain.
 
The paper describes the Spain pilot of residential buildings including the deployment of IoT wireless networks (i.e., sensors and actuators) based on Zwave technology to enable plug-and-play installations. The real-world tests showed the high efficiency of security-by-design Internet communications between building equipment and cloud management systems. Moreover, the results of cloud intelligent management demonstrate the improvements in both energy consumption and comfort conditions.
 

Figure: Architectural and hierarchical topology (credits: Rafael Marin-Perez, Iakovos T. Michailidis, Dan Garcia-Carrillo, Christos D. Korkas, Elias B. Kosmatopoulos and Antonio Skarmeta)

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
 
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