Sensors pp 523-527 | Cite as

Innovative System and Method for Monitoring Energy Efficiency in Buildings

  • Grazia Fattoruso
  • Saverio De Vito
  • Ciro Di Palma
  • Girolamo Di Francia
Conference paper
First Online:
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 162)

Abstract

Improving energy efficiency (EE) in buildings may significantly reduce the environmental impact of buildings as well as may result in a financial cost saving to consumers. With this contest, ENEA has developed an innovative intelligent sensing system, @lisee, for achieving energy efficiency in buildings (households, officies, campus, data centers, etc.) by a real time, distributed and continued monitoring of not only energy usage by all electrical devices but also safety and operative conditions of the several building settings, making the users aware and enabling user-controlled policies for electrical appliances. The proposed system consists in an multi-level architecture of intelligent wireless multi-sensor network realized by ZigBee-compliant and mesh based topology and sensor nodes for measuring power usage of any electric devices, locally estimating indoor air quality, controlling housing comfort and evaluating EE performance in data center. The gathered data are mining by sensor fusion techniques and modeling for building global power consumption profiles and 3D images of the sensed environment.

Keywords

Energy Efficiency Sensor Node Improve Energy Efficiency Electrical Device HVAC System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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References

  1. 1.
    Fattoruso G, Di Palma C, De Vito S, Casola V, Di Francia G (2012) Wireless energy meters for distributed energy efficiency applications sensors and microsystems. LN Electr Eng 109:199–203Google Scholar
  2. 2.
    De Vito S, Piga M, Martinetto L, Di francia G (2009) CO, NO2 and NOx urban pollution monitoring with on-field calibrated electronic nose by automatic bayesian regularization. Sens Actuator B Chem 143:182–191CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Grazia Fattoruso
    • 1
  • Saverio De Vito
    • 1
  • Ciro Di Palma
    • 1
  • Girolamo Di Francia
    • 1
  1. 1.ENEA Portici Research Centre – UTTP/Basic Materials and Devices DepartmentNaplesItaly

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