Crop Disease Detection and Monitoring System
L. R. Priya1, G. Ignisha Rajathi2, R. Vedhapriyavadhana3
1L.R.Priya, Professor in the Department of Electronics and Communication Engineering, Francis Xavier Engineering College, Tirunelveli., India.
2G. Ignisha Rajathi*, Assistant Professor, Department of Computer Science and Business Systems, Sri Krishna College of Engineering and Technology, Coimbatore, India.
3Dr. R. Vedhapriyavadhana, Professor in the Department of Electronics and Communication Engineering, Francis Xavier Engineering College, Tirunelveli, India.
Manuscript received on November 20, 2019. | Revised Manuscript received on November 26, 2019. | Manuscript published on 30 November, 2019. | PP: 3050-3053 | Volume-8 Issue-4, November 2019. | Retrieval Number: D7857118419/2019©BEIESP | DOI: 10.35940/ijrte.D7857.118419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Plants are liable to diseases that affect the growth of the plant, which successively affects the economy of the farmer. The symptoms of plant diseases are discernible in parts of a plant such as leaves, stem. Using an automatic disease detection system helps in early-stage detection and allows to treat the plant, thus preventing loss of crop. So, in our proposed system, we have introduced a crop disease detection and monitoring system. Disease detection is done using K-means clustering. Other subsystems include periodic monitoring of the temperature, humidity and soil moisture content. Based on the input of the soil moisture sensor, the motor is switched on and off for watering the plants. The actions taken are recorded and sent as a message to the farmer using the Wi-Fi Module.
Keywords: Disease Detection, Remote Control, Image Processing, Internet of Things.
Scope of the Article: Neural Information Processing.