# IoT-Based Cotton Plant Pest Detection and Smart-Response System
## 4 Simulations
### Assumption and Operation  
We supposed that the simulated UAV was based on the AGT-15 Drone sprayer, which is considered an advanced spraying drone for agriculture, which is a hexacopter with a Multi liter spray tank.  
We have just shown in our simulation that:  
* Each cluster has sensors connected to the nearest base station via the LoRa Communication module.
* The whole proposed system will currently have one drone/UAV that is connected to the base station, and as soon as a message from a sensor arrives, it goes there and sprays according to the coordinates given by the base. (However, we have proposed multiple drone operations in our predictive Algorithm. An advanced camera-equipped drone has also been proposed, which will be part of our system in the future.)
* In our simulation, some clusters and base stations are connected by a single hop, while some are connected by double or multiple hops.
* In this simulation, in some clusters, we operated the drones on the base's signals, while in some places, we tried to operate the drones manually.
* Everything in the simulation is pre-determined; for example, how long will the simulation last? How long will it take for the drone to reach the sensor (if it is reached automatically by the sensor's messages), how long will it take for us to arrive there (if we operate UAV manually), or how long will it take for the worm to circulate in the entire field?
* Drones that arrive on a single hop will certainly spend less time to reach, but drones that access a sensor or worm on a double hop will have a longer time. (The same thing will happen in the real scene drone that arrives from a distance will have a longer arrival time, while a nearby drone will quickly reach its target.
* According to the design topology, following the sensor signals, the drone will move into specific clusters and spray on insects or infected plants. Figures 9 and 10 show drones and worms hovering in different clusters of the field, and when the worm enters a cluster, the simulator points it out, as seen in Figure 10.
* The simulator has limitations, so now we can only deliver drones to clusters from which the message of insect identification has come. We are not yet able to chase insects or send drones to a specific place where the worm is flying at the moment.
* We have also created a specific path for the flying moth in the simulation through which the moth/insect passes, and the clusters it passes through generate signals of its presence, and accordingly, the drone follows it. The simulator identifies the worms and the presence of the drone, and when the worm enters, a cluster simulator highlights this particular cluster so that both the moth and the drone operation can be seen.
* After the spray operation, the drones return to their designated hangars and then wait for the next signals.
* If the field is large, then more drones will have to be used, but if the field is small, then only a small number of sensors and drones can work. Nowadays, there are a lot of companies making spray drones, so their price has also come down a lot.
* Our drones do not yet have cameras, but in the future, if we equip our spray drones with cameras, we will be able to see the insects and chase them and destroy them on the spot.
* One of the problems with our system may be that the signals are from an insect that is not harmful, and we have to eliminate it with our drones or spurs. This problem can also be solved when we put cameras on our drones and see if it is a harmful worm or not.
* But if the Meth/Worm is not found there, how will the drone chase it or return after spraying the plants? This is a question to which we are looking for an answer.