FarmGuide- One-stop solution to farmers
Abstract
Agriculture and the allied sectors largely
contribute to the livelihood of more than 70% rural population in
India. Indian economy is highly influenced by these sectors which
contribute to 18% of our country’s GDP. But the farmers, who
are the backbone of this system, suffer severe losses and the
suicide rate keep rising with more than 12,000 suicides per year.
The main reasons for this include lack of awareness about
market trends, ideal sowing dates as well as crop diseases that
affect the yield.
With the help of Cognitive implications and the
predictive analysis using artificial intelligence, this situation can
be improved. This paper emphasises on creating a one-stop
solution that can provide assistance to the farmers at different
stages; from sowing to selling their product. The paper mainly
focuses on three modules namely: Sowing dates prediction, Crop
Disease detection, and Market Intelligence along with Buying
selling Portal. As for the farmers, they do not need any special
tools other than mobile phones with an internet connection to use
these features, thereby making it practical and cost-effective.
Availability of such a platform can increase the
productivity in the farms and thereby can be a boon to Indian
Agriculture.
References
Economy".Internet:https://www.omicsonline.org/openaccess/
agriculture-role-on-indian-economy-2151-6219-
1000176.php?aid=62176, July 28, 2015 [Oct. 29, 2018].
[2]. "Agriculture Marketing - Problems of agriculture
marketing in India". Internet:
https://www.allexamnotes.com/2017/05/agricultural-marketingproblems/,
May.2, 2017 [Oct. 29, 2017].
[3]. Amandeep Singh, Maninder Lal Singh, “Automated
Color Prediction of Paddy Crop Leaf using Image Processing”,
2015 IEEE International Conference on Technological Innovations
in ICT for Agriculture and Rural Development (TIAR 2015).
[4]. Y. Lecun, L. Bottou, Y. Bengio, P. Haffner, “Gradientbased
learning applied to document recognition”, Proceedings of
the IEEE ( Volume: 86 , Issue: 11 , Nov 1998 ).
[5]. Karen Simonyan, Andrew Zisserman, “Very Deep
Convolutional Networks for Large-Scale Image Recognition”,
Cornell University Library, Submitted on 4 Sep 2014 (v1), last
revised 10 Apr 2015 (this version, v6).
www.asianssr.org 4
[6]. “ImageNet Classification with Deep Convolutional
Neural Networks”,https://papers.nips.cc/paper/4824-imagenetclassification-
with-deep-convolutional-neural-networks.pdf.
[7]. Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun,
“Deep Residual Learning for Image Recognition”, Cornell
University Library, Submitted on 10 Dec 2015.
[8]. Christian Szegedy, Wei Liu, Yangqing Jia, Pierre
Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan,
Vincent Vanhoucke, Andrew Rabinovich, “Going Deeper with
Convolutions”, Cornell University Library, Submitted on 17 Sep
2014.
[9]. "Convolutional Neural Networks". Internet:
https://github.com/mbadry1/DeepLearning.ai-
Summary/tree/master/4-%20Convolutional%20Neural
%20Networks#deep-convolutional-models-case-studies,[Oct. 29,
2017].
[10]. Board, James. (2002). A Regression Model to Predict
Soybean Cultivar Yield Performance at Late Planting Dates.
Agronomy Journal - AGRON J. 94. 10.2134/agronj2002.0483.
[11]. ResNet, AlexNet, VGGNet, Inception: Understanding
various architectures of Convolutional
Networks".Internet:https://cv-tricks.com/cnn/understand-resnetalexnet-
vgg-inception/, Aug.3, 2018 [Oct. 29, 2018].
[12]. Kenji Hato, Kojiro Fujii, Yukikazu Murakami, “Trial
of an Automatic Schedule for Farming and Crop Prediction”, 2015
Ninth International Conference on Complex, Intelligent, and
Software Intensive Systems, 2015.
[13]. https://www.crowdai.org/challenges/1
[14]. Sachin D. Khirade, A.B.Patil, “Plant Disease Detection
using Image Processing”, 2015 International Conference on
Computing Communication Control and Automation, 2015
[15]. G. Blanchard. “Statistical performance of support
vector machines".Internet:
https://ai.google/research/pubs/pub45416,2008 [Oct. 29, 2018].
[16]. David P. Hughes, Marcel Salathé, “An open access
repository of images on plant health to enable the development of
mobile disease diagnostics”, 2015 Cornell University Library
Open Access Repository.
[17]. K. P. Ferentinos, “Deep learning models for plant
disease detection and diagnosis”, Computers and Electronics in
Agriculture, 145, 311–318.
[18]. "Digital Agriculture: Farmers in India are using AI to
increase crop yields". Internet: https://news.microsoft.com/enin/
features/ai-agriculture-icrisat-upl-india/,[Oct. 29, 2017].
To ensure uniformity of treatment among all contributors, other forms may not be substituted for this form, nor may any wording of the form be changed. This form is intended for original material submitted to AJCT and must accompany any such material in order to be published by AJCT. Please read the form carefully.
The undersigned hereby assigns to the Asian Journal of Convergence in Technology Issues ("AJCT") all rights under copyright that may exist in and to the above Work, any revised or expanded derivative works submitted to AJCT by the undersigned based on the Work, and any associated written, audio and/or visual presentations or other enhancements accompanying the Work. The undersigned hereby warrants that the Work is original and that he/she is the author of the Work; to the extent the Work incorporates text passages, figures, data or other material from the works of others, the undersigned has obtained any necessary permission. See Retained Rights, below.
AUTHOR RESPONSIBILITIES
AJCT distributes its technical publications throughout the world and wants to ensure that the material submitted to its publications is properly available to the readership of those publications. Authors must ensure that The Work is their own and is original. It is the responsibility of the authors, not AJCT, to determine whether disclosure of their material requires the prior consent of other parties and, if so, to obtain it.
RETAINED RIGHTS/TERMS AND CONDITIONS
1. Authors/employers retain all proprietary rights in any process, procedure, or article of manufacture described in the Work.
2. Authors/employers may reproduce or authorize others to reproduce The Work and for the author's personal use or for company or organizational use, provided that the source and any AJCT copyright notice are indicated, the copies are not used in any way that implies AJCT endorsement of a product or service of any employer, and the copies themselves are not offered for sale.
3. Authors/employers may make limited distribution of all or portions of the Work prior to publication if they inform AJCT in advance of the nature and extent of such limited distribution.
4. For all uses not covered by items 2 and 3, authors/employers must request permission from AJCT.
5. Although authors are permitted to re-use all or portions of the Work in other works, this does not include granting third-party requests for reprinting, republishing, or other types of re-use.
INFORMATION FOR AUTHORS
AJCT Copyright Ownership
It is the formal policy of AJCT to own the copyrights to all copyrightable material in its technical publications and to the individual contributions contained therein, in order to protect the interests of AJCT, its authors and their employers, and, at the same time, to facilitate the appropriate re-use of this material by others.
Author/Employer Rights
If you are employed and prepared the Work on a subject within the scope of your employment, the copyright in the Work belongs to your employer as a work-for-hire. In that case, AJCT assumes that when you sign this Form, you are authorized to do so by your employer and that your employer has consented to the transfer of copyright, to the representation and warranty of publication rights, and to all other terms and conditions of this Form. If such authorization and consent has not been given to you, an authorized representative of your employer should sign this Form as the Author.
Reprint/Republication Policy
AJCT requires that the consent of the first-named author and employer be sought as a condition to granting reprint or republication rights to others or for permitting use of a Work for promotion or marketing purposes.
GENERAL TERMS
1. The undersigned represents that he/she has the power and authority to make and execute this assignment.
2. The undersigned agrees to indemnify and hold harmless AJCT from any damage or expense that may arise in the event of a breach of any of the warranties set forth above.
3. In the event the above work is accepted and published by AJCT and consequently withdrawn by the author(s), the foregoing copyright transfer shall become null and void and all materials embodying the Work submitted to AJCT will be destroyed.
4. For jointly authored Works, all joint authors should sign, or one of the authors should sign as authorized agent
for the others.
Licenced by :
Creative Commons Attribution 4.0 International License.
