Providing Personalized Energy Management and Awareness Services for Energy Efficiency in Smart Buildings

Considering that the largest part of end-use energy consumption worldwide is associated with the buildings sector, there is an inherent need for the conceptualization, specification, implementation, and instantiation of novel solutions in smart buildings, able to achieve significant reductions in energy consumption through the adoption of energy efficient techniques and the active engagement of the occupants. Towards the design of such solutions, the identification of the main energy consuming factors, trends, and patterns, along with the appropriate modeling and understanding of the occupants’ behavior and the potential for the adoption of environmentally-friendly lifestyle changes have to be realized. In the current article, an innovative energy-aware information technology (IT) ecosystem is presented, aiming to support the design and development of novel personalized energy management and awareness services that can lead to occupants’ behavioral change towards actions that can have a positive impact on energy efficiency. Novel information and communication technologies (ICT) are exploited towards this direction, related mainly to the evolution of the Internet of Things (IoT), data modeling, management and fusion, big data analytics, and personalized recommendation mechanisms. The combination of such technologies has resulted in an open and extensible architectural approach able to exploit in a homogeneous, efficient and scalable way the vast amount of energy, environmental, and behavioral data collected in energy efficiency campaigns and lead to the design of energy management and awareness services targeted to the occupants’ lifestyles. The overall layered architectural approach is detailed, including design and instantiation aspects based on the selection of set of available technologies and tools. Initial results from the usage of the proposed energy aware IT ecosystem in a pilot site at the University of Murcia are presented along with a set of identified open issues for future research.

[1]  Opher Etzion,et al.  Event Processing in Action , 2010 .

[2]  Fermín Galán Márquez,et al.  Exploiting the FIWARE cloud platform to develop a remote patient monitoring system , 2015, 2015 IEEE Symposium on Computers and Communication (ISCC).

[3]  Eleni Fotopoulou,et al.  Linked Data Analytics in Interdisciplinary Studies: The Health Impact of Air Pollution in Urban Areas , 2016, IEEE Access.

[4]  K. Shadan,et al.  Available online: , 2012 .

[5]  Fermín Galán Márquez,et al.  Handling smart environment devices, data and services at the semantic level with the FI-WARE core platform , 2014, 2014 IEEE International Conference on Big Data (Big Data).

[6]  Enzo Baccarelli,et al.  Fog of Everything: Energy-Efficient Networked Computing Architectures, Research Challenges, and a Case Study , 2017, IEEE Access.

[7]  P. G. V. Naranjo,et al.  Big Data Over SmartGrid-A Fog Computing Perspective , 2016 .

[8]  Hugo Ordoñez,et al.  Comparing Drools and Ontology Reasoning Approaches for Automated Monitoring in Telecommunication Processes , 2016 .

[9]  Anita Burgun-Parenthoine,et al.  Comparing Drools and ontology reasoning approaches for telecardiology decision support , 2012, MIE.

[10]  Antonio F. Gómez-Skarmeta,et al.  A semantic approach towards implementing energy efficient lifestyles through behavioural change , 2016, SEMANTICS.

[11]  Antonio F. Gómez-Skarmeta,et al.  Towards Energy Efficiency Smart Buildings Models Based on Intelligent Data Analytics , 2016, ANT/SEIT.

[12]  Jaeho Kim,et al.  Standards-Based Worldwide Semantic Interoperability for IoT , 2016, IEEE Communications Standards.

[13]  Alejandro Sánchez,et al.  SmartPort: A Platform for Sensor Data Monitoring in a Seaport Based on FIWARE , 2016, Sensors.

[14]  Euripides G. M. Petrakis,et al.  Personalized Motion Sensor Driven Gesture Recognition in the FIWARE Cloud Platform , 2015, 2015 14th International Symposium on Parallel and Distributed Computing.

[15]  Jemal H. Abawajy,et al.  Economical and environmental operation of smart networked microgrids under uncertainties using NSGA-II , 2016, 2016 24th International Conference on Software, Telecommunications and Computer Networks (SoftCOM).

[16]  Tullie Circle,et al.  AMERICAN SOCIETY OF HEATING, REFRIGERATING AND AIR-CONDITIONING , 2013 .