International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 08 Issue: 04 | Apr 2021
p-ISSN: 2395-0072
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Efficient Field Monitoring Autonomous Drone (FMAD) with pesticide sprayer and anomaly detection in crops Saikat Duttaroy1, Milind U Nemade2, Sushant Devgonde1, Vivek Parmar1, Deepak Gounder1 1Student,
Electronics Engineering, K J Somaiya Institute of Engineering and Information Technology, Mumbai. of Dept., Electronics Engineering, K J Somaiya Institute of Engineering and Information Technology, Mumbai. ---------------------------------------------------------------------***---------------------------------------------------------------------2 Head
Abstract - Agricultural production is one of the key factors
aerial view of the field helps the farmer to monitor the field and to get the appropriate data. The proposed system uses the multispectral image processing technique to monitor the health of the crops. This technique can differentiate between the healthy crop and the infected crop. It sends the data of the infected crops to the farmer, and then the farmer can take the appropriate action on it. The spraying mechanism installed in the proposed system can be controlled remotely. This variable spraying speed mechanism helps to increase accuracy and efficiency. This reduces the time and efforts of the farmer.
in the stability of the global economy. Correct and timely use of pesticides and proper observation of the crops provides an additional favorable atmosphere for crops to grow that eventually results in good agricultural production. FMAD is a system that is capable of spraying pesticides automatically over the agricultural land and also collect images and record videos of the field for further monitoring using various spectral imaging techniques. FMAD as a system is very low cost and has very little maintenance as compared to the other systems available. FMAD increases the efficiency and also minimizes the manual work of the farmer to spray pesticides and monitor the field which indeed becomes very beneficial for the farmer. Key Words: Agriculture, Drones, Pesticides, Spectral Imaging, Smart Agriculture, Autonomous Drone.
The next section explains the literature survey of the existing systems. Section III explains the problem definition of the FMAD system while the proposed system explanation is mentioned in Section IV. Ariel, feature extraction and cost analysis of the system is given in Section V followed by results and conclusion in Section VI and VII respectively.
1. INTRODUCTION
2. LITERATURE SURVEY
Agriculture is a key aspect of the whole country. It plays a very vital role in the global economy. So, it is very important to look to boost up agricultural production and it can be boosted by using smart techniques which will help to detect and monitor diseases in plants and spraying pesticides and medicines at the proper time.
In construction and infrastructure inspection applications, unmanned aerial vehicles (UAVs) can be used for real-time monitoring construction project sites [1]. The project managers can monitor the construction site using UAVs with better visibility about the project progress without any need to access the site [2]. Moreover, UAVs can also be utilized for high voltage inspection of the power transmission lines. In the papers [3]–[4], the authors used UAVs to perform autonomous navigation for the power lines inspection. The UAVs were deployed to detect, inspect and diagnose the defects of the power line infrastructure.
Identification of plant diseases is the key to preventing the losses in the yield and quantity of the agricultural product. The studies of plant diseases mean the studies of visually observable patterns seen on the plant. Health monitoring and disease detection on the plant are very critical for sustainable agriculture. It is very difficult to monitor plant diseases manually. It requires a tremendous amount of work, expertise in plant diseases and also requires excessive processing time. Hence, image processing is used for the detection of plant health. Disease detection involves steps like image acquisition, image pre-processing, image segmentation, feature extraction, and classification. This paper discussed the methods used for the detection of plant diseases using their images. This paper also discussed some segmentation and feature extraction algorithm used in plant disease detection.
In paper [5], the authors designed and implemented a fully automated UAV-based system for real-time power line inspection. More specifically, multiple images and data from UAVs were processed to identify the locations of trees and buildings near the power lines, as well as to calculate the distance between trees, buildings, and power lines. Furthermore, the Thermal infrared camera was employed for poor conductivity detection in the power lines. Drones can also be used to monitor the various facilities and infrastructure, including gas, oil, and water pipelines. In paper [6], it was suggested by the authors that the development of a small drone enabled with a gas controller system will be capable of detecting air and gas content.
The proposed system here allows the farmer to see the aerial view of the field while spraying pesticides over the field. The
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