Um Sistema de Controle Neuro-Fog para Infraestruturas Residenciais via Objetos Inteligentes

In recent years, the use of the fog computing paradigm is increasingly present in studies and services offered by a smart city, as the intelligent home systems which are one of the services to be highlighted. However, such paradigm brings two major challenges within the context of intelligent homes: how to extract the data that will be used in the decision-making process efficiently, and how to enable interoperability among the devices. Thus, this work proposes ImPeRIum, an intelligent decision system which forms a fog computational environment to manage the applications of the residence. ImPeRIum was evaluated in both the simulated environment and the real environment. When compared with other works in literature, ImPeRIum showed an advance in the state of the art and It obtained three promising results: (i) high hit rate with a low delay in the decision-making process; (ii) efficient in the information dissemination with a low overhead in infrastructure; and (iii) robustness in processing with a low energy consumption.

[1]  Alan Valejo,et al.  ResiDI: Towards a smarter smart home system for decision-making using wireless sensors and actuators , 2018, Comput. Networks.

[2]  Xiangyu Wang,et al.  Context-aware inference in ubiquitous residential environments , 2014, Comput. Ind..

[3]  Richard Werner Nelem Pazzi,et al.  An Energy-Aware System for Decision-Making in a Residential Infrastructure Using Wireless Sensors and Actuators , 2015, 2015 IEEE 14th International Symposium on Network Computing and Applications.

[4]  John A. Stankovic,et al.  CityGuard: A Watchdog for Safety-Aware Conflict Detection in Smart Cities , 2017, 2017 IEEE/ACM Second International Conference on Internet-of-Things Design and Implementation (IoTDI).

[5]  Manjiri Pathak,et al.  Smart Home System using Android Application , 2015 .

[6]  Albert Y. Zomaya,et al.  A control and decision system for smart buildings using wireless sensor and actuator networks , 2014, Trans. Emerg. Telecommun. Technol..

[7]  Nadeem Javaid,et al.  Home Appliances Coordination Scheme for Energy Management (HACS4EM) Using Wireless Sensor Networks in Smart Grids , 2014, ANT/SEIT.

[8]  Anne-Marie Kermarrec,et al.  The many faces of publish/subscribe , 2003, CSUR.

[9]  Leandro A. Villas,et al.  An intelligent approach for improving energy efficiently in smart grids , 2013 .

[10]  Jo Ueyama,et al.  A Low-Cost Smart Home Automation to Enhance Decision-Making based on Fog Computing and Computational Intelligence , 2018, IEEE Latin America Transactions.

[11]  Jo Ueyama,et al.  ResiDI: An Intelligent Decision Platform for Residential Infrastructure Using Wireless Sensors and Actuators , 2015, 2015 XXXIII Brazilian Symposium on Computer Networks and Distributed Systems.

[12]  Teddy Mantoro,et al.  Web-enabled smart home using wireless node infrastructure , 2011, MoMM '11.

[13]  Kire Trivodaliev,et al.  A review of Internet of Things for smart home: Challenges and solutions , 2017 .

[14]  Alex R. Pinto,et al.  NodePM: A Remote Monitoring Alert System for Energy Consumption Using Probabilistic Techniques , 2014, Sensors.

[15]  Sneha A. Dalvi,et al.  Internet of Things for Smart Cities , 2017 .