IOT-Based Cotton Whitefly Prediction Using Deep Learning

Table 1

Relevant prediction methods in the previous study.

Study	Year	Sensor/method used	Objective
Li et al. [22]	2008	No sensors/ISODATA iterative self-organizing data analyzed technique algorithm	Prediction of disease/insect pests for Guangdong vegetables
Wei and Lin [23]	2009	No sensor/fuzzy radial basis function neural network	Pest predicting
Li et al. [24]	2010	No sensor/maximum likelihood algorithm	Forecast model for vegetable pests
Raghavendra [12]	2014	No sensor/multiple linear regression and generalized linear model	Prediction of pests in cotton
Lee et al. [25]	2017	No sensor/correlation between pests and weather	Prediction for multiple crops
Li et al. [26]	2020	Image processing	Crop pest recognition in natural scenes using convolutional neural networks
Liu and Wang [27]	2020	Image processing	Tomato diseases and pests detection based on improved Yolo V3 convolutional neural network
Xiao et al. [28]	2019	No real time/use weather dataset	Occurrence prediction of pests and diseases in cotton on the basis of weather factors by long short term memory network
Türkoğlu and Hanbay [29]	2019	No sensor/image processing	Plant disease and pest detection using deep neural network
He et al. [30]	2019	Camera and light source/imaging system	Detect oilseed rape pests based on deep learning