JST Vol. 21 (1) Jan. 2013 - Pertanika Journal - Universiti Putra ...

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Az Azrinudin Alidin and Fabio Crestani particular dimension. Besides, these patterns need to be general and consistent in interpreting the dimension when implemented in a later stage. Fig.4 shows the accelerometer axes. The axes are influenced by gravitation force. By examining this force, the orientation of the iPhone can be detected. Then, by collecting the force value over time, the user’s activities can be recognized by analyzing the iPhone orientation. For this experiment, iPhone accelerometer and microphone data are collected and analyzed to collect a prior pattern that recognizes the user’s activities and the surrounding sounds. The initial results of recognizing the user’s activities are presented in Fig.5, Fig.6 and Fig.7, and the result of analyzing the surrounding sounds is depicted in Fig.8. In this experiment, the iPhone is always placed inside the front pocket of the user’s trousers because most of the users often place their smartphones inside the trouser front pocket. The accelerometer data are collected when the user is doing simple activities like sitting, standing and walking. These accelerometer patterns will be used as a reference to automatically recognize the context dimensions of the user’s activity in this research. Fig.5 shows the pattern for recognizing the sitting activities. The x, y, z axes of the accelerometer indicated the orientation of the iPhone. If z axis is equivalent to -1, the screen of the iPhone is facing up and if z axis is equivalent to 1, the screen of the iPhone is facing down. Since the user is sitting, the values of the x and y axes indicate that the user is practically not making any movement. Fig.6 indicates the pattern when the user is standing. The graph indicates when the user is standing and the user will somehow move a little bit, as indicated by the x and z axes. The orientation of the iPhone is in portrait orientation when y axis is equivalent to -1 or portrait upside down when the y axis equal to 1. On the other hand, a pattern of accelerometer data when the user is walking is shown in Fig.7. The accelerometer axes are greatly fluctuating and unstable compared to the graphs when the user is sitting and standing. When the user is walking, the user’s steps cause the accelerometer to record greater gravitation force as shown in the y axis. Besides, the user’s steps when walking also cause the iPhone to receive a vibration, as suggested by the values from the x axis. Hence, the system can automatically distinguish these activities by recognizing the fluctuating pattern of the accelerometer axes. This process will not require too much processing power, which can be implemented inside the iPhone without draining its battery life. Fig.4: The iPhone accelerometer axes 234 Pertanika J. Sci. & Technol. 21 (1): 283 - 298 (2013)
Context Modelling for Just-In-Time Mobile Information Retrieval (JIT-MobIR) Fig.5: Accelerometer pattern for the sitting activity Fig.6: Accelerometer pattern for the standing activity Fig.7: Accelerometer pattern for the walking activity Pertanika J. Sci. & Technol. 21 (1): 283 - 298 (2013) 235
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Journal of Science & Technology Jou
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International Advisory Board Adarsh
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Selected Articles from UPM-Malaysia
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ISSN: 0128-7680 © 2013 Universiti
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Aspect of Fatigue Analysis of Compo
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Application of Anthropometric Dimen
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Different Media Formulation on Bioc
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Heng, S. C., Ibrahim, Z. B., Suleim
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CONCLUSION Heng, S. C., Ibrahim, Z.
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Y. Yusuf, J. M. Juoi, Z. M. Rosli,
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Surface Roughness Y. Yusuf, J. M. J
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DISCUSSION Y. Yusuf, J. M. Juoi, Z.
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Modelling of Motion Resistance Rati
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The Empirical Method Modelling of M
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Assessment of Heavy Metal Pollution
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TABLE 1: Size of mussels in average
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TABLE 5: Heavy metal concentrations
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Physico-Chemical and Electrical Pro
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TABLE 1: (continued) Physico-Chemic
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Norhashila Hashim et al. effectiven
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Statistical Analysis Norhashila Has
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Norhashila Hashim et al. Post-hoc a
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Norhashila Hashim et al. Cubero, S.
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S. Ismail and K. A. Mohd Atan 4 4 p
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S. Ismail and K. A. Mohd Atan The f
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Lemma 1.1 The equation S. Ismail an
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CONCLUSION S. Ismail and K. A. Mohd
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INTRODUCTION Tajau, R. et al. A hig
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Tajau, R. et al. the acrylate’s c
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Tajau, R. et al. double bond) and C
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Tajau, R. et al. Ulanski, P., & Ros
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Aji, I. S., Zinudin, E. S., Khairul
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Aji, I. S., Zinudin, E. S., Khairul
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CONCLUSION Aji, I. S., Zinudin, E.
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D. Bachtiar, S. M. Sapuan, E. S. Za
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TABLE 1: (continue) 4 D. Bachtiar,
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N. Maizatul, I. Norazowa, W. M. Z.
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REFERENCES N. Maizatul, I. Norazowa
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CBIR Using Colour and Shape Fused F
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Toward Automatic Semantic Annotatin
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Page 258 and 259: Hasiah Mohamed@Omar, Azizah Jaafar
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