design and fabrication of Unmanned Aerial vehicle for precise agriculture activities

Implementing artificial intelligence based autonomous control system that could control the Unmanned aerial vehicle to identify crop well-being status to conclude whether to shower insecticide or not. Crop will be observed by the optical camera attached to the UAV. Airborne microprocessor wil

Project Title

design and fabrication of Unmanned Aerial vehicle for precise agriculture activities

Project Area of Specialization

Mechanical Engineering

Project Summary

Implementing artificial intelligence based autonomous control system that could control the Unmanned aerial vehicle to identify crop well-being status to conclude whether to shower insecticide or not.

Crop will be observed by the optical camera attached to the UAV. Airborne microprocessor will determine condition of the plants according to the database provided and will decide to spray on the plants with the help of attached spraying system. The drone will search for the crops autonomously on desired area with the help of in-built system. Thus, increasing efficiency as well as saving time.

Project Objectives

Objective of this project is to provide sustainable solution to the agricultural problems of Pakistan which intends to increase the agricultural production with the optimum usage of resources and also environment friendly and time saving. In order to achieve this objective we further divided our project into sub-tasks which are as:

• 1: Automation of UAV.
• 2: Detection of crops
• 3: spraying of fertilizers/pesticides

First step towards achieving the overall objective of project is automation of UAV. In this step we will be working on the automated flight of drone. Drone automation will make agriculture free of labor. We just have to provide a path on agricultural land and drone will fly autonomously and performs its tasks.

After successful automation of our UAV we will focus on the detection part of our project, as it will be necessary for the drone to detect crops and spray fertilizers. This step is important for optimum utilization of resources. We will use machine learning and artificial intelligence to perform this task.

Our final objective is spraying of fertilizers on the detected crops. For this, we will make a separate spraying mechanism and will integrate it with our drone such that sprayer spray fertilizers only when drone detect crops on agricultural land.

Project Implementation Method

This project is divided into 3 different portions: automation, spraying mechanism and crop detection.

Automation of UAV:

Pixhawk is used as an autopilot for our UAV. Mission planner software is used to communicate to pixhawk in order to give commands. For selected coordinates: waypoint based command will be generated, which will contain all of the necessary data in order for UAV to work autonomously.

Spraying mechanism:

Firstly spraying mechanism will be designed and fabricated. Then it will be integrated drone. To operate spraying mechanism, external supply will be given to pixhawk in the AUX port and analogue output will be taken from pixhawk then this output will be given to spraying mechanism, in order to perform spraying upon signal.

Crop detection: 

Detection of crop will be performed using machine learning and artificial intelligence. First step will be training of UAV. It will be trained using dataset of hundreds of images of crops so that it can easily detect crops. Convolutional neural networks and deep learning techniques will be used to perform it. Arduino mega integrated with optical camera and pixhawk will be used for this task. Integration of Arduino with pixhawk is done in order to perform 2 way communication. Pixhawk will ask Arduino to take and process images while Arduino will inform pixhawk whether to spray on that specific crop or not.

Benefits of the Project

Precision agriculture implies new technologies in agriculture to increase crop yield and profitability and also reduces the amount of other inputs like (land, water, fertilizer, herbicides and insecticides).

Precise agriculture will lead to:

• Increase in yield production
• Reduction in the utilization of resources and use optimum resources
• Dissemination of modern farm practices to improve quality, quantity and reduced cost of production.
• Saves time of farmer

So when our project will be successfully completed then farmer with just one click can operate his farm. He does not need to send large sum of labor in the field to detect defects in crops, drone itself will detect defects and supply fertilizers/insecticides and it will also take much less time as compared to time taken by manual labor to spray the whole field.  So it do not only save time but also protect labor from hazards of insecticides. Moreover in the days of intense summer where intensity of sun is very high and human being cannot work in such weather, we can use this drone. So for countries like Pakistan drone technology for agriculture can be very beneficial considering that agriculture is considered a backbone of Pakistan.

Technical Details of Final Deliverable

Our project divides into 3 main physical parts that are Hex copter, spraying mechanism, camera system.

Hex Copter:

Hovering is the most important requirement for precise agriculture. To full fill this need our group selected multirotor. Among them hex copter was selected based on weight lift off capability.

Hex copter is consisted on the following things.

• Hex Copter frame model S550 of 550gram with 550mm distance between motors.
• Six RC motors of model Emax MT2216-810KV each with 63gram weight, 1100gram thrust and 10 X 45 carbon fiber prop. With max current of 13A
• 30 Amps Electronic speed controllers.
• Pixhawk 2.4.8 autopilot is used which has following specifications:

1. • Processor:
2. 32bit STM32F427 Cortex M4 core with FPU.
3. 32-bit STM32F103 failsafe co-processor.
4. 168 MHz
5. 128 KB RAM.
6. 2 MB Flash.

• Sensors:

1. ST Micro L3GD20H 16 bit gyroscope.
2. ST Micro X4HBA 303H 14 bit accelerometer/magnetometer.
3. Invensense MPU 6000 3-axis accelerometer/gyroscope.
4. MEAS MS5607 barometer.

• 14.5Vs Lipo battery of 5200mAh with 75C of c-rating and 650gram in weight.
• Carbon fiber landing gears of 200gram of landing gear.

Total weight of the UAV is 1.7Kg. With thrust to weight ratio of 1 it has capability of lifting 4.9Kg as payload.

Spraying mechanism:

It is consisted on a tank with a weight of 120gram which has capacity of 1.5 liters, a 9W rated pump with flowrate of 0.0455 liters/s which works on 12 Volts. A separate battery is used to power pump which is 3S lipo with 1300mAh capacity.

Crop detection system:

It consist of two further components:

• A camera
• Arduino

Camera we select to perform our task is EKEN h9

It has following specifications:

• Video quality: 4K 25 fps 2.7K 30 fps 1080p 60 fps 720p 120 fps
• Photo quality: 12 MP, 8 MP, 5MP & 4MP
• Processor: SOC: Sunplus 6350 Chipset: OV4689
• Camera Lens: Fish Eye: 17 mm 170 degree wide angle
• Resolution: 4.0 megapixel

Arduino Mega will be used as micro controller for the detection of crops.

Final Deliverable of the Project

Hardware System

Core Industry

Agriculture

Other Industries

Core Technology

Robotics

Other Technologies

Artificial Intelligence(AI)

Sustainable Development Goals

Good Health and Well-Being for People

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com