## 4 Role of UAV in Precision Pest Management  
Precision pest management can be used for monitoring the crops which identify the pest-affected places using remote sensing technologies, and control mechanisms such as pesticide spraying will be acted accordingly from prevention of diseases. For achieving this, both the technologies should be mounted on the UAV. The Unmanned aerial vehicle can also be used for spraying fertilizer and pesticides on agricultural fields [9]. The UAV has a significant feature with good speed and accuracy in spraying system of the fertilizer and pesticides. The main parts of UAV used for spraying are:  
* Pressure nozzle;
* Spraying controller;
* Pesticide box;
* Hall-flow sensor;
* Small diaphragm pump;
* Field-map interpretation system. A sprayer is connected with UAV for spraying pesticides or fertilizers. It can be sprayed through the nozzle into droplets under pressure. The suitable pressure is produced to spray the fluid with the help of the spray motor. The spraying controller uses the Hall-flow sensor for estimating the fluid flow inside the system and initiates the nozzle of the sprayer. UAVs used for spraying purpose can be varied with their Speed, Payload, and number of nozzles used for spraying. UAV-based fertilizer and pesticide spraying methodology has more efficiency than the traditional systems. It reduces the human contact with hazardous gases. A limited amount of human power is required. The UAV reduces the time and expenses. A detailed study is made on pest detection using Remote Sensing technology. Tables 3-6 show the pest detection in various types of crops, and the observations are analyzed through the captured spectral images by the UAV, Manned Aircraft, Satellite, and ground-based technology. Further in the Table 3, technical specification of the UAV is mentioned while capturing the images of the crops in different agricultural fields and locations. Figure 9: Octo copter. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**References**} & \multirow{2}{*}{**Crop Name**} & \multicolumn{5}{c}{**Parameters**} \\ \cline{2-7}  & & **Type of UAV** & **Camera** & \begin{tabular}{c} **No. of** \\ **Rotors** \\ \end{tabular}  & **Pest Name** & **Observations** \\ \hline [PERSON] & & & & & & \\ [PERSON] et al., 2021 & Rice & Multi-Rotor & \begin{tabular}{c} RGB, \\ Multispectral \\ \end{tabular}  & 4 & Leaf hopper & \begin{tabular}{c} Visual inspection of \\ images \\ \end{tabular}  \\ \hline [PERSON], [PERSON] et al., 2021 & Pine & Multi-Rotor & Multispectral & 6 & \begin{tabular}{c} Bursaphelenchus \\ xylophilus \\ \end{tabular}  & Visual Images \\ \hline [PERSON], [PERSON] & & & & & & \\ [PERSON] et al., 2021 & Maize & Multi-Rotor & Multispectral & 6 & Lepidoptera & Visual Images \\ \hline [PERSON] & & & & & & \\ [PERSON] et al., 2021 & Lemon & Multi-Rotor & Hyperspectral & 4 & Phytophthoraoma Gummosis & \begin{tabular}{c} Visual inspection of \\ images \\ \end{tabular}  \\ \hline [PERSON] et al., 2021 & Rice & Multi-Rotor & Hyperspectral & 4 & Ustilaginoidea virens & Damage assessments \\ \hline [PERSON] et al., 2021 & Grapevine & Multi-Rotor & Hyperspectral & 4 & \begin{tabular}{c} Grapevine vein-clearing \\ virus \\ \end{tabular}  & Visual Images \\ \hline [PERSON] et al., 2021 & Wheat & Multi-Rotor & Hyperspectral & 4 & Fusarium head blight & \begin{tabular}{c} Visual inspection of \\ images \\ \end{tabular}  \\ \hline [PERSON] et al., 2021 & Pine & Multi-Rotor & Multispectral & 6 & Bursaphelenchusxylophilus & Damage assessments \\ \hline [PERSON] et al., 2021 & Wheat & Multi-Rotor & Hyperspectral & 4 & \begin{tabular}{c} Pathogen Fusarium \\ graminearum \\ (Gibberellazee) \\ \end{tabular}  & Visual Images \\ \hline [PERSON] et al., 2021 & Wheat & Multi-Rotor & Hyperspectral & 4 & \begin{tabular}{c} Puccinia striiformis \\ \end{tabular}  & Disease Monitoring \\ \hline [PERSON] & & & & & & \\ et al., 2020 & Olive & Multi-Rotor & Multispectral & 6 & \ \begin{tabular}{c} Xylella fastidiosa \\ \end{tabular}