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RESUME

Professional Summary

Hello there! I'm an ambitious and enthusiastic student with a thirst for knowledge and a drive to excel.

Seeking new challenges and diverse environments, I'm passionate about personal and professional growth. With a strong academic foundation, I'm eager to gain practical experience and contribute to a dynamic organization. My proactive nature, effective communication, and exceptional multitasking abilities allow me to excel in managing tasks and meeting deadlines.

Currently pursuing a Bachelor's degree in LD College of Engineering in Instrumentation and Control Department (IC) , I actively participate in extracurricular activities to enhance my learning experience. Beyond academics, I stay updated on industry trends, attend webinars and workshops, and value professional networking. I believe in continuous self-improvement and lifelong learning.

Skills

 Artificial Intelligence    Machine Learning    OpenCV    Model Generation 
SCADA 
  P.L.C.    MATLAB    Content Creation 

Education

2021-2025

Bachelor of Engineering in Instrumentation and Control (I.C.)

L.D. College of Engineering, Ahmedabad | Expected Graduation: 2025

  • Pursuing a comprehensive curriculum specializing in Instrumentation and Control Engineering.

  • Consistently maintaining a high academic standard of 8.21 CPI, exemplifying dedication to learning and growth.

2021-2025

Minor Degree in Robotics - 115AO01

L.D. College of Engineering, Ahmedabad | Expected Graduation: 2025

  • Pursuing a comprehensive curriculum specializing in Robotics.

  • Exemplifying dedication to learning and growth.

2019-2021

Higher Secondary Education (HSC Board)

Parth School of Science and Competiton, Vadodara | Year of Completion: 2021

  • Attained a notable score of 78.82%

  • Demonstrated strong analytical and problem-solving skills in a challenging academic environment.

2017-2019

Secondary Education (SSC Board)

Bright Day School, Vadodara | Year of Completion: 2019

  • Achieved an impressive score of 77.83%

  • Displayed consistent commitment to academic excellence and a thirst for knowledge.

Laungauges

Hindi 🇮🇳

Native Speaker

Gujarati 🇮🇳

Mother Tounge

English 🇬🇧

Proficient speaker

German 🇩🇪 

Elementary proficiency

Projects

June 2024 - July 2024

VAHNINETRA: AI in Workplace Health & Safety

Associated with L.D. College of Engineering

  • A Fire Alarm System warns people when smoke, fire, carbon monoxide, or other fire-related or general notification emergencies are detected. These alarms may be activated automatically from smoke detectors and heat detectors or may also be activated via manual fire alarm activation devices such as manual call points or pull stations. Alarms can be either motorized bells or wall mountable sounders or horns.

  • PROBLEM STATEMENT: -
    The primary issue is the susceptibility to delayed alarms, which can lead to complacency and diminished trust in the alarm system, potentially resulting in inappropriate responses.

  • PROPOSE SOLUTION: -
    VAHNINETRA

January 2024 - June 2024

Mixing Process in Industries using Programmable Logic Control (P.L.C.)

Associated with L.D. College of Engineering

  • The mixing process in industries plays a pivotal role in achieving desired product quality by blending two or more liquids in specific proportions. This project focuses on automating the mixing process using a Programmable Logic
    Controller (PLC) to ensure accuracy, efficiency, and safety. The system comprises various components including tanks, agitator motors, solenoid valves, pipelines, level sensors, start and stop buttons, and indicator lights.

  • The PLC-based control system is designed to manage the entire mixing
    operation seamlessly. It monitors the levels of the liquids in the tanks using three level sensors: high-level sensor, low-level sensor, and level 1 sensor. Based on the sensor inputs, the PLC controls the opening and closing of three solenoid valves to regulate the flow of liquids through the pipelines. An agitator motor is activated to ensure uniform mixing of the liquids inside the tank.

  • The system features three indicator lights: fill, mix, and drain, to provide visual feedback on the current status of the mixing process. A start button initiates the mixing cycle, while a stop button halts the operation when required.

  • Overall, this PLC-based mixing system offers a reliable and efficient
    solution for industries looking to automate their liquid blending processes, ensuring consistent product quality while reducing manual intervention and minimizing errors.

September 2022 - May 2023

Garbage Monitoring System Using I.o.T.

Associated with L.D. College of Engineering

  • Developed an IoT-based Garbage Monitoring System to address solid waste management issues, improving waste detection, monitoring, and management processes.

  • Implemented real-time garbage level monitoring with three indicating LEDs on trash cans and a mobile app interface.

  • Contributed to efficient waste collection route planning, reducing manpower and fuel consumption.

  • Utilized monthly data analysis to prioritize garbage collection and optimize resources.

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Augest 2023 - Till present

Water Dispenser Using Bluetooth Module and Arduino UNO

Associated with L.D. College of Engineering

  • The "Bluetooth-controlled Water Dispenser using Arduino Uno and HC-05 Bluetooth Module" project aims to create a remote-controlled water dispenser for clean and hygienic water access.

  • It's suitable for diverse settings like offices, homes, and public spaces, minimizing human contact and contamination risks.

  • This system promotes water conservation and ensures easy, sanitary water dispensing, offering a sustainable solution for clean drinking water needs.

November 2023 - December 2023

Home Price Prediction ML Project

Associated with Bharat Intern

  • The Home Price Prediction project employs machine learning algorithms to forecast property prices.

November 2023 - December 2023

Iris Plant Classification ML Project

Associated with Bharat Intern

  • The Iris Plant Classification project utilizes machine learning to accurately categorize iris flowers into distinct species.

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