Agriculture pest detection using video processing technique

Wadhai, Monika; Gohokar, V. V.; Khaparde, Arti

doi:10.1109/infop.2015.7489444

Cited by 10 publications

(5 citation statements)

References 3 publications

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“…Another computational method was artificial neural networks. Wadhai et al (2015) introduced a pest detection system in greenhouses using image processing and neural networks exclusively applicable to greenhouse whitefly (Trialeurodes vaporariorum) and aphids.…”

Section: Related Workmentioning

confidence: 99%

A method for counting and classifying aphids using computer vision

Lins

Rodriguez

Scoloski

et al. 2020

Computers and Electronics in Agriculture

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Section: Related Workmentioning

confidence: 99%

A method for counting and classifying aphids using computer vision

Lins

Rodriguez

Scoloski

et al. 2020

Computers and Electronics in Agriculture

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“…The agent architecture of the current approach includes the following agent types: Sensor agent: This agent has the possibility of detecting bugs and fumigating a crop area. In real world, this detection would be accomplished with computer vision (CV) techniques as commonly done in the precision agriculture literature [ 23 ]. This agent can communicate with other sensor agents to warn them of the existence of bugs.…”

Section: Methodsmentioning

confidence: 99%

ABS-SmartComAgri: An Agent-Based Simulator of Smart Communication Protocols in Wireless Sensor Networks for Debugging in Precision Agriculture

García‐Magariño

Lacuesta

Lloret

2018

Sensors

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Smart communication protocols are becoming a key mechanism for improving communication performance in networks such as wireless sensor networks. However, the literature lacks mechanisms for simulating smart communication protocols in precision agriculture for decreasing production costs. In this context, the current work presents an agent-based simulator of smart communication protocols for efficiently managing pesticides. The simulator considers the needs of electric power, crop health, percentage of alive bugs and pesticide consumption. The current approach is illustrated with three different communication protocols respectively called (a) broadcast, (b) neighbor and (c) low-cost neighbor. The low-cost neighbor protocol obtained a statistically-significant reduction in the need of electric power over the neighbor protocol, with a very large difference according to the common interpretations about the Cohen’s d effect size. The presented simulator is called ABS-SmartComAgri and is freely distributed as open-source from a public research data repository. It ensures the reproducibility of experiments and allows other researchers to extend the current approach.

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“…Expert systems that use surveillance cameras to detect suspicious behavior have also received attention from researchers (Arroyo, Yebes, Bergasa, Daza, & Almazán, 2015;Lee, Leong, Lai, Leow, & Yap, 2018). In addition, expert systems based on computer vision technology and video information are used in agriculture for counting (Wadhai, Gohokar, & Khaparde, 2015), tracking (Chuang, Hwang, Ye, Huang, & Williams, 2017), and behavioral analysis of animals (Pasupa, Pantuwong, & Nopparit, 2015).…”

Section: Expert Systems Based On Computer Vision Technology and Surve...mentioning

confidence: 99%

“…. In addition, expert systems based on computer vision technology and video information are used in agriculture for counting (Wadhai, Gohokar, & Khaparde, 2015), tracking (Chuang, Hwang, Ye, Huang, & Williams, 2017), and behavioral analysis of animals (Pasupa, Pantuwong, & Nopparit, 2015).…”

mentioning

confidence: 99%