Wireless Sensor Network-Based 3D Home Control System for Smart Home Environment

This paper introduces a proposed 3d home control system that provides realistic home control service for users. We implemented the 3d home control system between usercentered virtual reality and the real world based on wireless sensor networks. This implemented system consists of smart devices that are equipped with virtual reality, the hardware for a real-world representation, and the synchronization software. The main point of virtual reality is that users are able to control home appliances similar to embellishing their home structure. Communication between the components, we designed the own communication protocol and used the wireless personal area network-based Zigbee module. Some experiments were conducted using the proposed model. As a result of the experiment, the proposed home control system performed well as it was designed to.

[1]  Elgar Fleisch,et al.  PowerPedia: changing energy usage with the help of a community-based smartphone application , 2011, Personal and Ubiquitous Computing.

[2]  Zeungnam Bien,et al.  Learning Structure of Human Behavior Patterns in a Smart Home System , 2010 .

[3]  Sara Rankohi,et al.  Review and analysis of augmented reality literature for construction industry , 2013 .

[4]  Wan-Ki Park,et al.  Design and Implementation of ZigBee based URC Applicable to Legacy Home Appliances , 2007, 2007 IEEE International Symposium on Consumer Electronics.

[5]  Qian Zhang,et al.  Probabilistic Field Coverage using a Hybrid Network of Static and Mobile Sensors , 2007, 2007 Fifteenth IEEE International Workshop on Quality of Service.

[6]  Jorge Sá Silva,et al.  A framework for Wireless Sensor Networks performance monitoring , 2012, 2012 IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM).

[7]  Peter E.D. Love,et al.  Augmented Reality in built environment: Classification and implications for future research , 2013 .

[8]  Omar Said,et al.  Scaling of wireless sensor network intrusion detection probability: 3D sensors, 3D intruders, and 3D environments , 2015, EURASIP J. Wirel. Commun. Netw..

[9]  Deying Li,et al.  Minimum-Delay POIs Coverage in mobile wireless sensor networks , 2013, EURASIP J. Wirel. Commun. Netw..

[10]  Mirza Mansoor Baig,et al.  Smart Health Monitoring Systems: An Overview of Design and Modeling , 2013, Journal of Medical Systems.

[11]  Bin Ma,et al.  Deploying Wireless Sensor Networks under Limited Mobility Constraints , 2007, IEEE Transactions on Mobile Computing.

[12]  Mark Weiser,et al.  The computer for the 21st Century , 1991, IEEE Pervasive Computing.

[13]  Bruce H. Thomas,et al.  An object-oriented software architecture for 3D mixed reality applications , 2003, The Second IEEE and ACM International Symposium on Mixed and Augmented Reality, 2003. Proceedings..

[14]  Manuel Ricardo,et al.  QoS-based management of biomedical wireless sensor networks for patient monitoring , 2014, SpringerPlus.

[15]  Hong Linh Truong,et al.  Towards a Framework for Monitoring and Analyzing QoS Metrics of Grid Services , 2006, 2006 Second IEEE International Conference on e-Science and Grid Computing (e-Science'06).