| Title | A Survey on Pest and Disease Monitoring of Crops |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Deepika, P., Kaliraj, S. |
| Conference Name | 2021 3rd International Conference on Signal Processing and Communication (ICPSC) |
| Keywords | Agriculture, Computer vision, Damage Assessment, Deep Leaning, Deep Learning, Disease Monitoring, Pest Monitoring, Product design, pubcrawl, quality assessment, Resiliency, Resistance, Signal processing, Training |
| Abstract | Maintenance of Crop health is essential for the successful farming for both yield and product quality. Pest and disease in crops are serious problem to be monitored. pest and disease occur in different stages or phases of crop development. Due to introduction of genetically modified seeds the natural resistance of crops to prevent them from pest and disease is less. Major crop loss is due to pest and disease attack in crops. It damages the leaves, buds, flowers and fruits of the crops. Affected areas and damage levels of pest and diseases attacks are growing rapidly based on global climate change. Weather Conditions plays a major role in pest and disease attacks in crops. Naked eye inspection of pest and disease is complex and difficult for wide range of field. And at the same time taking lab samples to detect disease is also inefficient and time-consuming process. Early identification of diseases is important to take necessary actions for preventing crop loss and to avoid disease spreads. So, Timely and effective monitoring of crop health is important. Several technologies have been developed to detect pest and disease in crops. In this paper we discuss the various technologies implemented by using AI and Deep Learning for pest and disease detection. And also, briefly discusses their Advantages and limitations on using certain technology for monitoring of crops. |
| DOI | 10.1109/ICSPC51351.2021.9451787 |
| Citation Key | deepika_survey_2021 |
A Survey on Pest and Disease Monitoring of Crops