LATEST PROJECTS
Project | 01
Development Of Flexible Autonomous Car System Using Machine Learning and Blockchain
The Objective of this System is to develop an autonomous car using Convolution Neural Network and at the same time Securely Store, Receive and Transmit Highly Confidential Data.
Hardware : Raspberry Pi 3 Software/Language: Python
Technology: Convolution Neural Networks, Block Chain
Domain: Robotics - Autonomous Cars
Role Played: Team Leader
Components used: Raspberry Pi 3 Model B, Pi Camera Module, L293D Breakout Board(motor driver),Toy RC car, Lithium ion Battery pack
This Project was presented at SPRINGER SYMINTECH 2018 event held at Fave Hotel, Langkawi, Malaysia sponsored by EDAS, SPRINGER and MALTESAS.
This Paper contains implementation of Block Chain into the autonomous car system to negate all the disadvantage of regular DSRC and also attain the advantage of using a Block Chain.
Certificate: Link
Project | 02
Application Of UAV For Pest, Weeds And Disease Detection Using Open Computer Vision
This project is being done at Hyoristic Innovations, a drone research startup at Chennai. I am part of the team doing work on Image Processing Aspect.
Hardware : Nox R2.19 FLight Controller
Software/Language: Python
Technology: Computer Vision - Image Processing
Domain: Robotics - Quadcopter
Role Played: Team Leader
Components used: Nox R2.19 FLight Controller, Logitech HD PRO Webcam C920 , RF Joystick , LiPo battery
The objective of the project is to locate regions that are affected by diseases so that we can particularly focus on the regions that are affected and carry out remedies required only in that particular area. For this purpose, we divide the entire area into n segments and using image processing, the segmented images are Pre-processed and analyzed using open CV.
The farmer can easily monitor Large area after initial plantation and irrigation to check which area of their lands is being affected by disease, pests and weeds.
Here, a camera, interfaced with a UAV and is used to keep our area under constant surveillance.
Certificate: Link
Project | 03
Project | 03
Project | 03
Autonomous Downscaled Model Car Using Neural Networks and Machine Learning
This project was done to prove my interest on autonomous cars and show I have what it takes to do research on the subject
Hardware : Raspberry Pi 3 Software/Language: Python
Technology: Neural Networks
Domain: Robotics - Autonomous Cars
Role Played: Team Leader
Components used: Raspberry Pi 3 Model B, Pi Camera Module, L293D Breakout Board(motor driver),Toy RC car, Lithium ion Battery pack
This Project was presented at IEEE SS12 2018 prelims event held at Jeppiar Institute of Technology, Chennai.
The work includes design of an RC toy car, that can drive autonomously on a given map in which it has been trained rigorously. It involves training the car on the map while capturing photos of the environment and co-relating them to generate a neural network model using machine learning. The RC car has driven autonomously on the given map successfully. Obstacle avoidance has been implemented using ultrasonic sensor and the RC car successfully stops when it faces an obstacle. Haar-cascade image processing has been used successfully to identify stop signs and red traffic signal, so as to make the car stop.
Patent To Be Published
Patent | 01
TITLE: "Development Of Flexible Autonomous Car System Using Machine Learning and Blockchain”
SECTION: Intellectual Property India Patent
Application No : 201841045731