Ramkumar Muthusrinivasan

ACADEMIC PROJECTS

MY DOCTOR DATABASE [NOV 2022]

• The ‘My Doctor Database’ is a sophisticated web application that enables patients to search for doctors across various specializations. Patients can access and review doctor profiles, as well as share their ratings and comments.

• The doctor database was meticulously designed using Oracle database, with an entity relationship diagram utilized to visualize the database’s structure and relationships.

• The web application was developed using Python and Django, which facilitated the seamless connection between the database and the web application.

BANK LOAN DETERMINER [OCT 2022]

• The Logistic Regression Model was applied to a large dataset consisting of nearly a million records and 27 attributes in order to assess the creditworthiness of new loan applicants.

• Data wrangling was performed using Python, while the machine learning models were programmed in R.

• To determine the amount of loan to be advanced for eligible borrowers, multiple linear regression was utilized.

SMART SWITCH MODULE [DEC 2020]

A Smart Switch Module is a device that can turn a regular switch into a smart switch. This means that users can control their lights or devices in different ways

• Mobile App Control: Users can also control the smart switch using a mobile app. This app allows them to control the switch from anywhere and often includes features like scheduling and timers.

• Voice Control: By connecting the module to virtual assistant platforms like Alexa, Google Assistant, or Siri, users can control their devices using voice commands.

• Manual Control: The physical switch on the wall still works, so users can still control their devices manually if they prefer.

Overall, Smart Switch Modules are a cost-effective way to make existing home appliances and lighting systems smarter. They make it more convenient and energy-efficient to control devices in modern homes.

PLANT HEALTH MONITOR [DEC 2020]

• A Plant Health Monitor is a cutting-edge system or application that leverages machine learning and image recognition methodologies to accurately identify diseases in plants.

• Its primary objective is to assist farmers and agricultural experts in promptly detecting and effectively managing plant diseases, thereby mitigating the risk of disease propagation within crops.

• In essence, plant health monitors assume a pivotal role in contemporary agriculture by empowering farmers to safeguard their crops, minimize losses associated with diseases, and foster sustainable farming practices.

• They exemplify a valuable implementation of machine learning and technological advancements within the agricultural domain, aligning seamlessly with the overarching objective of enhancing food security and promoting agricultural sustainability.