Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 30379
A Survey on Ambient Intelligence in Agricultural Technology

Authors: C. Angel, S. Asha

Abstract:

Despite the advances made in various new technologies, application of these technologies for agriculture still remains a formidable task, as it involves integration of diverse domains for monitoring the different process involved in agricultural management. Advances in ambient intelligence technology represents one of the most powerful technology for increasing the yield of agricultural crops and to mitigate the impact of water scarcity, climatic change and methods for managing pests, weeds and diseases. This paper proposes a GPS-assisted, machine to machine solutions that combine information collected by multiple sensors for the automated management of paddy crops. To maintain the economic viability of paddy cultivation, the various techniques used in agriculture are discussed and a novel system which uses ambient intelligence technique is proposed in this paper. The ambient intelligence based agricultural system gives a great scope.

Keywords: Ambient intelligence, Agricultural Technology, precise farming, smart agriculture

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1107778

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1490

References:


[1] Diane J. Cook, Juan C. Augusto, Vikramaditya R. Jakkula “Ambient intelligence: Technologies, applications, and opportunities”, Pervasive and Mobile Computing (2009) 277_298, ScienceDirect.
[2] ibutton. http://www.maxim-ic.com/products/ibutton/ibuttons/
[3] Vladimir M. Koleshko, Anatolij V. Gulay, Elena V. Polynkova, Viacheslav A. Gulay and Yauhen A. Varabei (2012). “Intelligent Systems in Technology of Precision Agriculture and Biosafety, Intelligent Systems”, Prof. Vladimir M. Koleshko (Ed.), ISBN: 978-953- 51-0054-6, InTech.
[4] Koleshko V. M., Gulay A. V. & Luchenok S.A. (2006), “Sensory System for Soil Express Diagnostics in Technology of Precision Agriculture”, Proceedings of Scientific and Practical Conference on Sensory Electronics and Microsystem Technologies, Russia, Odessa, June, 2006.
[5] http://www.eurekalert.org/pub_releases/2013-02/f-sa022213.php
[6] NitaBhalla “http://in.reuters.com/article/2014/09/16/foundation-indiafarming- climate-change-idINKBN0HB19920140916”
[7] Lutful Karim, Alagan Anpalagan, Nidal Nasser, Jalal Almhana “Sensorbased M2M Agriculture Monitoring Systems for Developing Countries: State and Challenges”, Network Protocols and Algorithms, ISSN 1943- 3581 2013, Vol. 5, No. 3.
[8] Kim Y., Evans R.G. and Iversen W.M., “Remote Sensing and Control of an Irrigation System Using a Distributed Wireless Sensor Network,” Instrumentation and Measurement, IEEE Transactions on, vol.57, no.7, pp.1379-1387, July 2008. http://dx.doi.org/10.1109/TIM.2008.917198
[9] Shock C. C., David R. J., Shock C. A., and Kimberling C. A., “Innovative, automatic, low-cost reading of watermark soil moisture sensors”, in Proc. Irrig. Assoc. Tech. Conf., Falls Church, VA, 1999, pp. 147–152.
[10] Miranda F.R., Yoder R., and Wilkerson J.B., “A site-specific irrigation control system”, presented at the ASAE Annu. Int. Meeting, Las Vegas, NV, Jul. 27–30, 2003. doi: http://dx.doi.org/10.13031/2013.13740.
[11] Wall R.W. and King B.A., “Incorporating plug and play technology into measurement and control systems for irrigation management”, presented at the ASAE/CSAE Annu. Int. Meeting, Ottawa, ON, Canada, Aug. 2004.
[12] Wark T., Corke P., Sikka P., Klingbeil L., Ying Guo, Crossman, C., Valencia P. and Swain D.; Bishop-Hurley G., “Transforming Agriculture through Pervasive Wireless Sensor Networks,” Pervasive Computing, IEEE, vol.6, no.2, pp.50-57, April-June 2007. http://dx.doi.org/10.1109/MPRV.2007.47
[13] http://southwestfarmpress.com/aggps-autopilot-links-satellites-farmtractors
[14] http://www.speakingtree.in/spiritual-blogs/seekers/selfimprovement/ swath-control-and-variable-rate-technology
[15] Christos Goumopoulos, “Pervasive Computing in Agriculture”.
[16] Prof. Samir Kumar Bandyopadhyay, Mr. Pritimoy Sanyal, “Application of intelligent Techniques towards improvement of crop productivity”, International Journal of Engineering Science and Technology (IJEST), ISSN : 0975-5462 Vol. 3 No. 1 Jan 2011.
[17] Sanyal P, Bhattacharya U, Parui S.K, Bandyopadhyay S.K and Patel S, “Color Texture Analysis of Rice Leaves to Diagnose Deficiency in the Balance of Mineral Levels Towards Improvement of Crop Productivity”, 10th International Conference on Information Technology, National Institute of Technology, Rourkela, India,2007, IEEE Computer Press.
[18] Yang C.C, Prasher S.O, Landry J.A, Perret J and Ramaswamy H.S, “Recognition of weeds with image processing and their use with fuzzy logic for precision farming”, Canadian Agricultural Engineering, Vol. 42, No. 4, 2000
[19] Pilarski, Happold T M, Pangels H, Ollis M, Fitzpatrick K and Stentz A, “The Demeter system for automated harvesting”, Autonomous Robots, Vol:13(1), pp: 9-20, 2002.
[20] Tian L, Slaughter D C and Norris R F, “Machine Vision Identification Of Tomato Seedlings For Automated Weed Control”, http://www.age.uiuc.edu/faculty/lft/papers/tomato.pdf
[21] Polder G, van der Heijden G W A M and Young I T, “Hyperspectral Image Analysis for Measuring Ripeness of Tomatoes”, ASAE International Meeting, 2000.