Srikar Reddy C

SKILLS

PROJECTS

• Medsync Care

  MedSync Care is a comprehensive healthcare management platform designed to assist caretakers, patients, and healthcare professionals in managing and tracking medication schedules, prescriptions, and medical reports. Our platform ensures timely medication for patients and efficient care coordination.

  Key Features:

  • Automated notifications and logging for medication schedules.
  • Role-based access control for coordinated care.
  • Secure storage and renewal reminders for prescriptions.
  • Centralized and secure storage for medical reports.
  • Tools to track and analyze medication adherence.
  • Automated alerts for missed medications and emergencies.

  Tech used: React, ShadCN, Vite, Node.js, Express, MongoDB, MySQL, Kubernetes, Nginx, Docker, Docker-Compose, Github Actions(CI/CD)

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• Homelab Setup with Raspberry Pi

  Set up a secure homelab using Raspberry Pi, employing Twingate to enable remote access without the need for a VPN. Integrated the QUIK protocol for efficient user access control, ensuring a seamless and secure setup for hosting personal projects.

  Key Features:

  • Serves as a registration point for Connectors, enabling secure initialization and connection.
  • Registers hash-based Connector IDs to allow private and efficient connectivity without exposing network details.
  • Acts as a connection point for Clients to establish connections to Connectors.
  • Verifies legitimate Client requests and connects them directly to the requested Connector.
  • Establishes secure, certificate-pinned TLS tunnels without storing or exposing network information.

  Tech used: Raspberry Pi, Python, Twingate, QUIK Protocol, Docker

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• Micro Frontends: Implementing Polyglot

  Implemented a Micro Frontend architecture to integrate Angular (using Module Federation) and React frameworks (using Native Federation) into a legacy application. This approach enabled better runtime dependency sharing, reduced bundle sizes, and improved scalability for enterprise applications.

  Key Features:

  • Optimized performance with reduced build sizes by 60%.
  • Improved runtime sharing of dependencies between Angular and React federations.
  • Enhanced scalability and modular maintainability for enterprise-scale systems.

  Tech used: Angular, React, Webpack Module Federation, Vite Native Federation

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• Dynamic DNS Updater

  Developed a system that automatically updates a Dynamic DNS (DDNS) record whenever the public IP address changes. Ensured uninterrupted access to services hosted on a dynamic IP setup with efficient error handling and automated retries.

  Key Features:

  • Periodic polling to detect changes in external IP address.
  • Automated updates to DNS provider via API calls.
  • Robust error handling and retry mechanisms for seamless operation.

  Tech used: Python, REST APIs, Bash, Cron Jobs

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• Sentimental Analysis using Logistic Regression

  Sentiment analysis can be used to analyze web material from social media platforms, online products, companies, events, and personnel. It employs a variety of methodologies to determine a text's or sentence's sentiment. This project focuses on applying logistic regression for effective accuracy and predicting whether given reviews are positive or negative. Using natural language processing, we analyzed product reviews efficiently and achieved a high accuracy of 94% with the Logistic Regression Grid Search Model.

  Key Features:

  • Automatically classifies feedback into positive and negative sentiments.
  • Uses Logistic Regression with grid search for improved accuracy.
  • Analyzes large datasets of product reviews using natural language processing techniques.
  • Provides actionable insights to businesses for improving products and optimizing marketing strategies.
  • Facilitates intelligent systems to summarize product reviews effectively.

  Tech used: Python, TensorFlow, SK-Learn, Keras, Matplotlib, Pandas

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• Tactile Code Predictor using SVM and KNN Algorithm

  Designed tactile code recognition models using SVM and KNN, leveraging Kaggle datasets and real-life tactile images for training. The project aims to enhance communication for visually impaired individuals, enabling interpretation of tactile signs for those unfamiliar with ASL.

  Key Features:

  • Developed SVM and KNN models for efficient tactile code recognition.
  • Utilized Kaggle datasets and real-life tactile images for model training.
  • Enhanced accessibility for visually impaired individuals by interpreting tactile signs.
  • Implemented real-time image processing for accurate tactile code prediction.
  • Focused on bridging communication gaps for users unfamiliar with ASL.

  Tech used: Python, TensorFlow, MongoDB, Keras, SciKit-Learn, OpenCV, Matplotlib, Pandas

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• Smart Phone Manufacturer System

  Developed an Android and web-based application that provides detailed information on mobile phones, including manufacturing details, seller information, and specifications. Delivered a comprehensive tool for accessing smartphone data efficiently.

  Key Features:

  • Centralized database for storing detailed smartphone information.
  • Interactive UI for browsing mobile phone specifications and manufacturing details.
  • Real-time synchronization between Android and web platforms.
  • Role-based access for manufacturers and sellers to manage their products.
  • Efficient search and filter options for quick access to desired smartphone data.
  • Integrated with GetX architecture for state management and seamless user experience.

  Tech used: Flutter, Dart, Node.js, Express, GetX Architecture

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