This document presents a project to develop a smart sprayer technology using an all-terrain agricultural robot integrated with AI algorithms and IoT principles. The objectives are to design the robot body, analyze it for various loads, identify sensors to detect plant features and spray/not spray, develop AI algorithms to process sensor data and detect plant issues, and develop software to control the sensors. The methodology involves CAD modeling, testing, integrating AI algorithms for tasks like disease detection, integrating IoT sensors for feedback and control, and evaluating the prototype. The expected outcomes are an all-terrain robot built with a spraying mechanism, integrated with AI and IoT technologies to help optimize fertilizer and pesticide use.

1. JSS ACADEMY OF TECHNICAL EDUCATION BENGALURU
DEPARTMENT OF MECHANICAL ENGINEERING
Smart sprayer technology to reduce fertilizer/pesticides
ALL TERRAIN AGRICULTURAL ROBOT INTEGRATED WITH
AI BASED ALGORITHMS AND IoT PRINCIPLES
UNDER THE GUIDANCE OF:
 MRS. ROOPA D. N
 DR. ANANDKUMAR R. ANNIGERI
PRESENTED BY:
• MANJUNATH N (1JS19ME045)
• GIRISH S (1JS19ME025)
• NIHAR S (1JS19ME050)
• DILEEP Y (1JS19ME023)

2. Problem Definition:
To Develop a technology to optimize the use of fertilizer/pesticides / Neutrients
Objectives:
1. Develop the physical structure (body) of the sprayer (Robot.
2. Analyze the structure for various loading conditions
3. Identify the sensors to
1. Height and width of the tree
2. Detect leaves/fruits/objects other than plants (eg. Person, pump, pole etc…)
3. Sensor to auomateShould spray
4. Should not spray if it finds objects other than plant/tree (ex. Person, pump, pole etc..
4. Develop AI ML algorithm to process data
1. To detect leaves/fruits/ under the attack of insects
2. If tree/leaves appear dead, it should not spray but move forward.
5. Develop a software to control the Sensors

3. Problem
Develop agricultural robot based on AI algorithms and IOT
Objectives:
1. To design to body
2. To analyze for various loads and materaials
3. Identify Sensors -
4. Fabricate

4. Recognition of real life problem
Problem definition
Fabrication of Physical Model
METHODOLOGY
 Development of CAD model
 Testing and analysis of CAD
model
Integration of AI based algorithms
Implementation of various AI based
algorithms such as leaf disease
detection using Image processing.
Integration of various IoT based
sensors for feedback and control
Testing and evaluation of the model
Final presentation
Define Objectives

5. EXPECTED OUTCOMES:
All terrain agricultural robot is built on desai mechanism
AI based algorithms are integrated with the model
IoT based sensors are implemented for feedback and control
The developed prototype is tested and evaluated

6. REFERENCES
 Mr. J. Rajesh ,Mr. R. Dinesh, Mr. S. Gowtham, Mr. K. Iniyavan Autonomous Adjustable
Pesticide Spraying Device for Agricultural Application ( IJERT) on 3 March 2019.
 Design and Implementation of Semi-autonomous Anti-pesticide Spraying and Insect Repellent
Mobile Robot for Agricultural Applications, 2018 5th International Conference on Electrical
and Electronics Engineering
 Ankit Singh, Abhishek Gupta, Akash Bhosale, Sumeet Poddar, “Agribot: An Agriculture
Robot”, International Journal of Advanced Research in Computer and Communication
Engineering Vol. 4, Issue 1, January 2015.

7.  Fuentes, A., Yoon, S., Kim, S. C., & Park, D. S. (2017). A robust deep-learning-based detector for
real-time tomato plant diseases and pests recognition. Sensors, 17(9), 2022.
 Xue, J., Zhang, L., & Grift, T. E. (2012). Variable field-of-view machine vision based row guidance
of an agricultural robot. Computers and Electronics in Agriculture, 84, 85-91.
 A.A.C.Fernando, and C.Ricardo, “Agricultural Robotics , Unmanned Robotic Service Units in
Agricultural Tasks”,lEEE Industrial Electronics Magazine, pp. 48-58, Sep 2013.
 A. Guillet, R. Lenain, and B. Thuilot, Off-road Path racking of a Fleet of WMR with Adaptive and
Predictive Control, IEEE Int. Conf. on Intelligent Robots and Systems, (IROS) Tokyo (Japan), 2013.

8. THANK YOU