Abstract:
Sustainable agriculture is an important field where not much attention is given though it is highly necessary, so as to monitor the growth of crops for their efficient gr...Show MoreMetadata
Abstract:
Sustainable agriculture is an important field where not much attention is given though it is highly necessary, so as to monitor the growth of crops for their efficient growth in most nutritious ways. For effective growth of crops, lot of chemicals like fertilizers and pesticides are used, however, excessive usage of them results in damage to land and water resources. The attack of pests is a major criteria which affect crop yield. Various crop monitoring technologies are available which are highly expensive and not all farmers can afford. Moreover in India, farmers are not capable of understanding the operation and handling of such sophisticated technology. In this paper, we propose a system which is cheaper and easy to operate with multiple application. The proposed system uses a technology which utilizes machine learning and ANN algorithms using UAV that helps us to locate regions that are affected by diseases and pesticides so that we can particularly focus on the regions that are affected and apply chemicals only in that particular area, with the entire system being cost effective. For this purpose, we divide the entire area into n x n segments and using image processing, the segmented areas are analysed and processed using Ardupilot and a central operating system to monitor using python and open CV, giving the simplest user interface for monitoring purposes.
Date of Conference: 13-14 December 2018
Date Added to IEEE Xplore: 01 July 2019
ISBN Information:
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Unmanned Aerial Vehicles ,
- Pest Detection ,
- Open Computer Vision ,
- Image Processing ,
- Pesticides ,
- Artificial Neural Network ,
- Crop Yield ,
- Water Resources ,
- Sustainable Agriculture ,
- Pest Attacks ,
- Affect Crop Yield ,
- Support Vector Machine ,
- Internet Of Things ,
- Test Phase ,
- Global Positioning System ,
- Motion Detection ,
- Luminosity ,
- Means Clustering ,
- Pixel Matrix ,
- Presence Of Pests
- Author Keywords
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Unmanned Aerial Vehicles ,
- Pest Detection ,
- Open Computer Vision ,
- Image Processing ,
- Pesticides ,
- Artificial Neural Network ,
- Crop Yield ,
- Water Resources ,
- Sustainable Agriculture ,
- Pest Attacks ,
- Affect Crop Yield ,
- Support Vector Machine ,
- Internet Of Things ,
- Test Phase ,
- Global Positioning System ,
- Motion Detection ,
- Luminosity ,
- Means Clustering ,
- Pixel Matrix ,
- Presence Of Pests
- Author Keywords