An architectural framework for mobile device interaction with consumer home network appliances

Author(s):  
Brijesh Kumar ◽  
Constantine Katsinis
2013 ◽  
Vol 71 (10) ◽  
pp. 988-1002 ◽  
Author(s):  
Eli R. Hooten ◽  
Sean T. Hayes ◽  
Julie A. Adams

Author(s):  
Shiwei Cheng ◽  
Qianjing Wei ◽  
Zhangwei Zhang ◽  
Wenjie Qi ◽  
Honggang Cai

2013 ◽  
Vol 846-847 ◽  
pp. 309-312
Author(s):  
Jing Li ◽  
Fei Fei Wang

Smart home generally creates a communication network for the family to provide necessary information accesses in the home network operating system. Under the controls of the hardware and the corresponding implemental agency, all the home network appliances control and monitoring are achieved. As the smart home becomes more advanced and complex, its urgent to search for an effective management model. In this paper, we propose a compatible smart home system management model and make some future development assumptions.


2013 ◽  
Vol 5 (3) ◽  
pp. 23-41 ◽  
Author(s):  
Hamed Ketabdar ◽  
Amin Haji-Abolhassani ◽  
Mehran Roshandel

The theory of around device interaction (ADI) has recently gained a lot of attention in the field of human computer interaction (HCI). As an alternative to the classic data entry methods, such as keypads and touch screens interaction, ADI proposes a touchless user interface that extends beyond the peripheral area of a device. In this paper, the authors propose a new approach for around mobile device interaction based on magnetic field. Our new approach, which we call it “MagiThings”, takes the advantage of digital compass (a magnetometer) embedded in new generation of mobile devices such as Apple’s iPhone 3GS/4G, and Google’s Nexus. The user movements of a properly shaped magnet around the device deform the original magnetic field. The magnet is taken or worn around the fingers. The changes made in the magnetic field pattern around the device constitute a new way of interacting with the device. Thus, the magnetic field encompassing the device plays the role of a communication channel and encodes the hand/finger movement patterns into temporal changes sensed by the compass sensor. The mobile device samples momentary status of the field. The field changes, caused by hand (finger) gesture, is used as a basis for sending interaction commands to the device. The pattern of change is matched against pre-recorded templates or trained models to recognize a gesture. The proposed methodology has been successfully tested for a variety of applications such as interaction with user interface of a mobile device, character (digit) entry, user authentication, gaming, and touchless mobile music synthesis. The experimental results show high accuracy in recognizing simple or complex gestures in a wide range of applications. The proposed method provides a practical and simple framework for touchless interaction with mobile devices relying only on an internally embedded sensor and a magnet.


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