Drone Development and Embellishing It into Crop Monitoring and Protection Along with Pesticide Spraying Mechanism

2021 ◽  
pp. 199-210
Author(s):  
Smita Agrawal ◽  
Preeti Kathiria ◽  
Vishwam Rawal ◽  
Trushit Vyas
Keyword(s):  
Crop Monitoring

scholarly journals A State-of-the-Art Analysis of Obstacle Avoidance Methods from the Perspective of an Agricultural Sprayer UAV’s Operation Scenario

Agronomy ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1069
Author(s):  
Shibbir Ahmed ◽  
Baijing Qiu ◽  
Fiaz Ahmad ◽  
Chun-Wei Kong ◽  
Huang Xin
Keyword(s):  
Collision Avoidance ◽  
Obstacle Avoidance ◽  
State Of The Art ◽  
Obstacle Detection ◽  
Crop Monitoring ◽  
Data Intensive ◽  
Structural Details ◽  
Dynamic Operating ◽  
New Generation ◽  
The Internet Of Things

Over the last decade, Unmanned Aerial Vehicles (UAVs), also known as drones, have been broadly utilized in various agricultural fields, such as crop management, crop monitoring, seed sowing, and pesticide spraying. Nonetheless, autonomy is still a crucial limitation faced by the Internet of Things (IoT) UAV systems, especially when used as sprayer UAVs, where data needs to be captured and preprocessed for robust real-time obstacle detection and collision avoidance. Moreover, because of the objective and operational difference between general UAVs and sprayer UAVs, not every obstacle detection and collision avoidance method will be sufficient for sprayer UAVs. In this regard, this article seeks to review the most relevant developments on all correlated branches of the obstacle avoidance scenarios for agricultural sprayer UAVs, including a UAV sprayer’s structural details. Furthermore, the most relevant open challenges for current UAV sprayer solutions are enumerated, thus paving the way for future researchers to define a roadmap for devising new-generation, affordable autonomous sprayer UAV solutions. Agricultural UAV sprayers require data-intensive algorithms for the processing of the images acquired, and expertise in the field of autonomous flight is usually needed. The present study concludes that UAV sprayers are still facing obstacle detection challenges due to their dynamic operating and loading conditions.

Erratum to The effect of dew on the use of RADARSAT-1 for crop monitoring

2002 ◽  
Vol 81 (2-3) ◽  
pp. 456
Author(s):  
D Wood ◽  
H McNairn ◽  
R.J Brown ◽  
R Dixon
Keyword(s):  
Crop Monitoring

A Node and Network Level Self-Recovering Distributed Wireless Sensor Architecture for Real-Time Crop Monitoring in Greenhouses

2011 ◽  
Vol 54 (4) ◽  
pp. 1521-1527
Author(s):  
G. M. Striemer ◽  
D. L. Story ◽  
A. Akoglu ◽  
M. Kacira
Keyword(s):  
Real Time ◽  
Wireless Sensor ◽  
Crop Monitoring

Rice Crop Monitoring in South China With RADARSAT-2 Quad-Polarization SAR Data

2011 ◽  
Vol 8 (2) ◽  
pp. 196-200 ◽  
Author(s):  
Fan Wu ◽  
Chao Wang ◽  
Hong Zhang ◽  
Bo Zhang ◽  
Yixian Tang
Keyword(s):  
South China ◽  
Rice Crop ◽  
Crop Monitoring ◽  
Sar Data

Observations on Zambia’s Crop Monitoring and Early Warning Systems

2014 ◽  
Vol 6 (3) ◽  
Author(s):  
Gelson Tembo ◽  
Bernadette Chimai ◽  
Nathan Tembo ◽  
Mukelabai Ndiyoi
Keyword(s):  
Early Warning ◽  
Early Warning Systems ◽  
Warning Systems ◽  
Crop Monitoring ◽  
Monitoring And Early Warning
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