Record Details

<p>Detecting Crop Health using Machine Learning Techniques in Smart Agriculture System</p>

Online Publishing @ NISCAIR

View Archive Info
 
 
Field Value
 
Authentication Code dc
 
Title Statement <p>Detecting Crop Health using Machine Learning Techniques in Smart Agriculture System</p>
 
Added Entry - Uncontrolled Name Shukla, Rati ; GIS Cell, MNNIT Prayagraj, Allahabad, Uttar Pardesh, India
Dubey, Gaurav ; ABES Engineering College, Ghaziabad, Uttar Pradesh, India
Malik, Pooja ; Shiv Nadar University, Greater Noida, India, 4Amity University, Noida, India
Sindhwani, Nidhi ; Amity University, Noida, India
Anand, Rohit ; G B Pant Engineering College, New Delhi, India
Dahiya, Aman ; Maharaja Surajmal Institute of Technology, New Delhi, India
Yadav, Vikash ; ABES Engineering College, Ghaziabad
 
Uncontrolled Index Term Feature extraction, Image segmentation, Internet of things, Unmanned aerial vehicles
 
Summary, etc. <p>The crop diseases can’t detected accurately by only analysing separate disease basis. Only with the help of making comprehensive analysis framework, users can get the predictions of most expected diseases. In this research, IOT and machine learning based technique capable of processing acquisition, analysis and detection of crop health information in the same platform is introduced. The proposed system supports distinguished services by monitoring crop and also managed its data, devices and models. This system also supports data sharing and communication with the help of IOT using unmanned aerial vehicle (UAV) and maintains high communication standards even in bad communication environment. Therefore, IOT and machine learning ensures the high accuracy of disease prediction in crop. The proposed integrated system is capable of detecting health of crop through analysis of multi-spectral images captured through the IOT associated UAV. The various machine learning is also applied to test the performance of our system and compared with the existing disease detection methods.</p>
 
Publication, Distribution, Etc. Journal of Scientific and Industrial Research (JSIR)
2021-10-06 12:01:33
 
Electronic Location and Access application/pdf
http://op.niscair.res.in/index.php/JSIR/article/view/44034
 
Data Source Entry Journal of Scientific and Industrial Research (JSIR); ##issue.vol## 80, ##issue.no## 08 (2021): Journal of Scientific and Industrial Research
 
Language Note en