Smart Agricultural Drone for controlling crops diseases and analysis water requirement

With the development of information technology, Internet-of-Things (IOT) and low-altitude remote-sensing technology represented by Unmanned Aerial Vehicles (UAVs) are widely used in environmental monitoring fields. In agricultural modernization, IOT and UAV can monitor the incidence of crop diseases

2025-06-28 16:35:04 - Adil Khan

Project Title

Smart Agricultural Drone for controlling crops diseases and analysis water requirement

Project Area of Specialization Electrical/Electronic EngineeringProject Summary

With the development of information technology, Internet-of-Things (IOT) and low-altitude remote-sensing technology represented by Unmanned Aerial Vehicles (UAVs) are widely used in environmental monitoring fields. In agricultural modernization, IOT and UAV can monitor the incidence of crop diseases and pests from the ground micro and air macro perspectives, respectively. IOT technology can collect real-time weather parameters of the crop growth by means of numerous inexpensive sensor nodes. While depending on spectral camera technology, UAVs can capture the images of farmland, and these images can be utilize for analyzing the occurrence of pests and diseases of crops. In this work, we attempt to design an agriculture framework for providing profound insights into the specific relationship between the occurrence of pests/diseases and weather parameters & when the drone detect the crop disease, it will spray automatically and also the need for the water in the field will be sensed.

Project Objectives

Android control: A UAV drone can be controlled through mobile app.

Indicating flight parameters: Outlining and evaluating the surveillance area and uploading GPS info into the drone navigation system.

 Autonomous flights: A UAV drone carries out a flight pattern according to the pre-established parameters and collects the required data.

Data upload: The drone submits the data it has captured for processing and analysis.

Information output: After the data has been processed, it is sent to farmers in a readable format. The report contains insightful info which accounts for better farm management decisions. 

Project Implementation Method

Literature Review: To study the sensor integration, its  working capability and GUI application.

Sensor and Module Integration: Initially import required sensors and modules and then integrate with Drones.

Image processing: Image processing is a method to perform some operations on an image, to enhance or extract. It is a rapid growing technology and a part of an artificial intelligence.

Programming: To write pseudo code then convert it into real programming language, remove all bugs.

Prototype model: Before go for real drone structure designing, apply all possible features and algorithm on prototype model.

Simulation: We will have the proper simulation and calculated result earlier, but implementing it on real system will be our main task.

PCB Designing: To design electronic circuit and implement it on PCB,

Solid Works Design:  To make drone design on software to overcome the physical flows before go for hardware.

Implementation of Hardware Design: To apply solid work design on hardware, drone frame will be robust and made up of carbon fiber.

Assembly:  Fix all components, sensors, PCB and miscellaneous equipment on drone.

Field Testing: After testing we will be finalizing the hardware with proper presentations and with best accurate working.

Report Writing:  After performing all above task in given time we will be writing report in which we will describe each and every working component in best understanding formats.

Benefits of the Project

Smart farms use drones for agriculture spraying, which helps limit human contact with fertilizers, pesticides and other harmful chemicals. Drones can handle this task faster and more efficiently than vehicles and airplanes; they are also a great alternative for farms that still use manual labor.

Drones are also irreplaceable when it comes to spot treatment. They can detect infected areas with sensors and cameras and work on them while leaving the healthy part of the field intact. This not only saves time and increases safety, but also helps reduce expenses.

Technical Details of Final Deliverable

The final deliverable will consist of six motor UAV drones carbon fiber body structure having brushless motor and pixhawk flight controller (GPS, Telemetry, pi camera, sensors and modules). And pesticide medicine bottle also installed in our system pi camera detect the disease in crops and take medicine on time. Complete agriculture drone with battery will be submit in working condition.

Final Deliverable of the Project HW/SW integrated systemCore Industry AgricultureOther Industries Medical , Transportation Core Technology Internet of Things (IoT)Other Technologies Artificial Intelligence(AI), RoboticsSustainable Development Goals Decent Work and Economic Growth, Climate ActionRequired Resources
Item Name Type No. of Units Per Unit Cost (in Rs) Total (in Rs)
Total in (Rs) 79400
Raspberry pi 3 B+ Equipment155005500
Pixhawk flight controller 2.4.8 Equipment190009000
Brushless motor BR 2212 980kv Equipment613007800
ESC motor controll 30 amp favourite Equipment616009600
Power module XT60 Equipment1800800
Anti vibration flight controller Equipment1400400
Transmitter and receiver Radio link AT9s Equipment11300013000
Lipo battery 5200 mah 4 cell Equipment240008000
Battery balance charger Equipment135003500
Propeller carbon fiber 1045 Equipment62001200
GPS module M8N with stand Equipment125002500
Telemetry 3DR 500MW 915MHZ/433MHZ Equipment123002300
PI camera Equipment125002500
Buck converter Equipment1300300
Single relay bunch module Equipment1400400
pressure water pump Equipment110001000
Medicine Tank Equipment1700700
Water pipe Equipment1200200
Nozzle spray Equipment3300900
Hardware structure design Miscellaneous 155005500
Nut bolt Miscellaneous 1500500
PCB designing Miscellaneous 120002000
panaflex stand design Miscellaneous 118001800

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