Novel Real-Time Video Surveillance Framework for Precision Pesticide Control in Agribusiness
Agribusiness has turned out to be considerably more than just a method to bolster consistently developing populaces. Plants have progressed toward becoming an imperative wellspring of vitality, and are a basic piece in the puzzle to take care of the issue of an unnatural climatic change. The economic changes of the mid 1990s set the phase for an improved and developing part by the private area of agriculture. Economic development quickened, especially after 2000, with major modernizing impacts on agriculture, cultivating and agri-food esteem chains . Private agribusiness organizations are at the front line of overwhelming interest in agricultural R&D and mechanical development . To improvise and expand agribusiness, one of the step is to control the pests on growing plants. We are proposing a framework for controlling pests on the growing plants of tomato in agribusiness using Real-Time Video Surveillance and image processing technique. In the proposed work, video is captured, converted to suitable color models, and pre-processed. From the obtained video, pests are quantified. Pesticides can be sprayed on the plants of tomato for controlling pests and improve yield in agribusiness.
KeywordsBegomoviruses in whitefly Video processing technique Automated tests management Image analysis Object detection Object segmentation Object extraction
- 1.Abdullah, N.E., Rahim, A.A., Hashim, H., Kamal, M.M.: Classification of rubber tree leaf diseases using multilayer perceptron neural network. In: 5th Student Conference on Research and Development 2007, SCOReD 2007, pp. 1–6. IEEE (2007)Google Scholar
- 2.Birthal, P.S., Chand, R., Joshi, P.K., Saxena, R., Rajkhowa, P., Khan, M., Khan, M.A., Chaudhary, K.R.: Formal versus informal: efficiency, inclusiveness, and financing of dairy value chains in India. International Food Policy Research Institute (2016)Google Scholar
- 4.Ferroni, M., Zhou, Y.: The private sector and India’s agricultural transformation. Glob. J. Emerg. Mark. Econ. 0974910117716406 (2017)Google Scholar
- 10.Raut, S., Fulsunge, A.: Review on fruit disease detection using image processing techniques. Int. J. Innov. Emerg. Res. Eng. 4(4) (2017). e-ISSN 2394 - 3343. p-ISSN 2394 – 5494Google Scholar
- 12.Senthilrajan, A.: Pest control in paddy using segmentation in image processing. Eng. Sci. Int. Res. J. ISSN. 2320–4338Google Scholar