Project Title – Detector Image processing algorithm implementation using PROASIC3E FPGA and VHDLProject Description-The project's goal is to create and implement an image processing algorithm using a Field Programmable Gate Array (FPGA) platform. The primary goal will be to create efficient algorithms capable of real-time processing for applications such as object identification, picture enhancement, and segmentation FPGAs have parallel processing capabilities, making them ideal for high-performance image processing workloads.Key Tasks Performed- >ADC characterization and hardware testing for Wide-field optical view and quantum technology demonstration in space. >CDC, FIFO, and SRAM implementation on PROASIC FPGA board with interfacing of the clock to ADC and TEC.>Implemented MATLAB and SIMULINK on Raspberry Pi 5 for maximum intensity image in the optical receiver.>Hardware test system for memory verification using NI PXI board and ProASIC3E FPGA.

Completed Projects:The company worked with Charusat University on the following projects in collaboration:1) Security Surveillance System comprising of a mobile outdoor Ground Robot in combination with Aerial Surveillance using a Drone2) Warehouse Material Handling Tugger and Personal Mobility VehicleWork during internship was involved but not limited to:a) Creating Test Plans for Components and Products besides assisting in the actual Testing Procedure;b) Product and Domain research as required for ongoing projects at the company;c) Documentation of Product Development processes;d) Assist in the Application Engineering processes involved in EE & EC domains as and when required in the field of Robotics & Electric Mobility

Worked on two main projects based on full-stack development and API use:1.Python web app to automate twitter: This web application automates the messages entered by the user in the website. The website is made using Flask micro framework of python.Using the Google Sheets API, and gspread library of the python the data entered by the user is stored in the google sheets as a reference database.2. Deployment of ML models through flask.• Deployed and created an app on Heroku with the help of Git Repository • Predicting Salary with different attributes of data through Simple Regression model and built a website with the help of flask that can input the data of the user and display the predicted salary through the machine learning model and created an app on Heroku open platform for users to access the model.During the internship and interaction with my fellow colleagues, I got to know many procedures and standards of how a software tech industry works.