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An Intelligent Vision Based Sensing Approach for Spraying Droplets Deposition Detection

1
College of Electronic Engineering, South China Agricultural University, Guangzhou 510642, China
2
The Department of Electrical, Computer, Software, and Systems Engineering, Embry-Riddle Aeronautical University, Daytona Beach, FL 32114, USA
3
The Department of Engineering at Jacksonville University, Jacksonville, FL 32211, USA
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(4), 933; https://doi.org/10.3390/s19040933
Received: 30 September 2018 / Revised: 8 January 2019 / Accepted: 12 January 2019 / Published: 22 February 2019
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Abstract

The rapid development of vision sensor based on artificial intelligence (AI) is reforming industries and making our world smarter. Among these trends, it is of great significance to adapt AI technologies into the intelligent agricultural management. In smart agricultural aviation spraying, the droplets’ distribution and deposition are important indexes for estimating effectiveness in plant protection process. However, conventional approaches are problematic, they lack adaptivity to environmental changes, and consumes non-reusable test materials. One example is that the machine vision algorithms they employ can’t guarantee that the division of adhesive droplets thereby disabling the accurate measurement of critical parameters. To alleviate these problems, we put forward an intelligent visual droplet detection node which can adapt to the environment illumination change. Then, we propose a modified marker controllable watershed segmentation algorithm to segment those adhesive droplets, and calculate their characteristic parameters on the basis of the segmentation results, including number, coverage, coverage density, etc. Finally, we use the intelligent node to detect droplets, and then expound the situation that the droplet region is effectively segmented and marked. The intelligent node has better adaptability and robustness even under the condition of illumination changing. The large-scale distributed detection result indicates that our approach has good consistency with the non-recyclable water-sensitive paper approach. Our approach provides an intelligent and environmental friendly way of tests for spraying techniques, especially for plant protection with Unmanned Aerial Vehicles. View Full-Text
Keywords: droplets; intelligent node; vision sensor; adaptability; Unmanned Aerial Vehicles droplets; intelligent node; vision sensor; adaptability; Unmanned Aerial Vehicles
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Wang, L.; Yue, X.; Liu, Y.; Wang, J.; Wang, H. An Intelligent Vision Based Sensing Approach for Spraying Droplets Deposition Detection. Sensors 2019, 19, 933.

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