Various Advanced Statistical Analyses of Index Values Extracted from Outdoor Agricultural Workers Motion Data
We have been grouping and developing various kinds
of practical, promising sensing applied systems concerning
agricultural advancement and technical tradition (guidance). These
include advanced devices to secure real-time data related to worker
motion, and we analyze by methods of various advanced statistics and
human dynamics (e.g. primary component analysis, Ward system
based cluster analysis, and mapping). What is more, we have been
considering worker daily health and safety issues. Targeted fields are
mainly common farms, meadows, and gardens. After then, we
observed and discussed time-line style, changing data. And, we made
some suggestions. The entire plan makes it possible to improve both
the aforementioned applied systems and farms.
 Y. Fujii, T. Nanseki, H. Kobayashi, and K. Nishitani, “Information
management and cultivation of employee capabilities at large-scale paddy field farms: a case study of raising rice seedlings,” Agricultural
Information Research, vol. 21(3), pp. 51-64, 2012.
 Y. Fujii, T. Nanseki, H. Kobayashi, and T. Kojima, “The characteristics
of expert know-how in agricultural planning on large-scale paddy field
farms: a case study of a corporate farm in shiga prefecture,” Agricultural
Information Research, vol. 22(3), pp. 142-158, 2013.
 T. Nanseki, S. Takeuchi, and Y. Shinozaki, “Business development, ICT
use, and personal training in agricultural corporations: an analysis of
nationwide questionnaire survey,” Agricultural Information Research,
vol. 22(3), pp. 159-173, 2013.
 A. Shinjo and M. Kudo, “The practical use of IT in agriculture: the
movement into high-value-added crops and integrated solutions,” The
Journal of the Institute of Electronics, Information, and Communication
Engineers, vol. 96(4), pp. 280-285, 2013.
 S. Kawakura and R. Shibasaki, “Supporting systems for agricultural
workers’s skill and security,” Proceedings of ACRS 2013, pp. 71-77,
 P. Mistry, P. Maes, and L. Chang, in Massachusetts Institute of
Technology. WUW-wear Urworld: a wearable gestural interface.
Available: http://dspace.mit.edu/handle/1721.1/61366, 2009.
 L. Bao, “physical activity recognition from acceleration data under
semi-naturalistic conditions,” unpublished master thesis, MIT, Boston,