Image acquisition system for agricultural context-aware computing
Keywords:
image acquisition, agriculture, context-aware computingAbstract
Abstract: Context-aware computing is a new mode originated from ubiquitous computing. Its emergence brings a substantial change to traditional computing and related service. Image is a pervasive tool for context awareness. A large number of applications are developed based on images analysis. In this paper, an image acquisition system is presented for agricultural context-aware computing. The potential use of the system includes production evaluation, precise management and assistant control. The system includes four modules: the camera system, the control system, mechanism, and communication. The system can be easily installed in target crop fields. The camera system is composed of a binocular stereo camera and a color camera. Two cubic images and a corresponding texture image are collected for each plant in the process of data acquisition. An accessorial software system is developed to control and manage the capture system. Experiments show that the presented system is effective for image acquisition of agricultural context-aware computing. Keywords: image acquisition, agriculture, context-aware computing DOI: 10.3965/j.ijabe.20140704.008 Citation: Xiao B X, Wang C Y, Guo X Y, Wu S. Image acquisition system for agricultural context-aware computing. Int J Agric & Biol Eng, 2014; 7(4): 75-80.References
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[2] He Y. Zhao C J, Wu D, Nie P C, Feng L. Fast detection technique and sensor instruments for crop-environment information: A review. Science in China Series F: Information Science, 2010; 40(s1): 1–20. (In Chinese)
[3] Xiao B X, Guo X Y, Guo X D, Du J J. An intelligent decision model and system for maize precise production and management. ICIC Express Letters, Part B: Applications, 2012; 3(4): 1363–1368.
[4] Zhang N Q, Wang M H, Wang N. Precision agriculture-a worldwide overview. Computers and Electronics in Agriculture, 2002; 36(1): 113–132.
[5] Zhou L L, Song L T, Xie C J, Zhang J. Applications of Internet of Things in the facility agriculture. Proc. of Advances in Information and Communication Technology, springer, 2011; 392: 297–303.
[6] Zhang F J. Research on applications of Internet of Things in agriculture. Lecture Notes in Electrical Engineering, 2013; 209: 69–75.
[7] Cui D, Li M Z, Zhu Y, Cao W X, Zhang X J. Monitoring crop growth status based on optical sensor. Proc. of First IFIP TC 12 International Conference on Computer and Computing Technologies in Agriculture (CCTA 2007), 2007; 1397–1401.
[8] Cheng K, Cheng X L, Shang X N, Teng S W. Design of Plant Growth Status Analyzer Based on Photoelectric Technology. Proc. of International Conference on Electronics and Optoelectronics (ICEOE), 2011; 426–429.
[9] Patel N K, Patnaik C, Dutta S, Shekh A M, Dave A J. Study of crop growth parameters using Airborne Imaging spectrometer data. Int J Remote Sens, 2001; 22: 2401-2411.
[10] Dey A. Providing Architectural Support for Building Context Aware Applications, PhD Thesis. Atlanta: Georgia Institute of Technology, 2000.
[11] Chen H. An Intelligent Broker Architecture for Pervasive Context-Aware Systems, PhD Thesis. Baltimore County: University of Maryland, 2004.
[12] Gu J Z. Context aware computing. Journal of East China Normal University (Natural Science), 2009; 9(5): 1–20. (In Chinese)
[13] Hu S Q, Wang H O, She C D, Wang J F. AgOnt: Ontology for Agriculture Internet of Things. Proc. of Advances in Information and Communication Technology, 2011, 344: 131–137.
[14] Zhang C L, Shen W Z. Application of Internet of Things in agriculture. Journal of Northeast Agricultural University, 2011; 42(5): 1–5. (In Chinese)
[15] Zhang L, Yu H, Ma X M. Information system platform for quality and security of agricultural products based on Internet of Things. Science in China Series F: Information Science,
2010; 40(s1): 216–225. (In Chinese)
[16] Brosnan T, Sun D W. Inspection and grading of agricultural and food products by computer vision systems-a review. Computers and Electronics in Agriculture, 2002; 36(2-3): 193–213.
[17] Lin K Y, Xu L H, Wu J H. Advances in the application of computer-vision to plant growth monitoring. Transactions of the CSAE, 2004; 20(2): 279–283. (In Chinese)
[18] Yang H Y, Tang G J. Target visibility and measure precision analysis of stereo vision systems. Systems Engineering and Electronics, 2012; 34(9): 1889–1894. (In Chinese)
[19] Xiong Y J. Shen M X, Sun Y W, Xu Y, Lin X Z. Design on system of acquisition and wireless transmission for farm land image. Transactions of the Chinese Society for Agricultural Machinery, 2011; 42(3): 184–187. (In Chinese)
[20] Li Y F. Studies on method of getting geometrical shape data of vegetal leaves based on image processing (Degree). Northeast Agricultural University, 2006.
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Published
2014-08-25
How to Cite
Boxiang, X., Chuanyu, W., Xinyu, G., & Sheng, W. (2014). Image acquisition system for agricultural context-aware computing. International Journal of Agricultural and Biological Engineering, 7(4), 75–80. Retrieved from https://ijabe.migration.pkpps03.publicknowledgeproject.org/index.php/ijabe/article/view/987
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Information Technology, Sensors and Control Systems
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