https://github.com/DevS0ni/Veterinary-Clinic-Management-System

Welcome to my showcase project, the Veterinary Clinic Management System, where I developed a robust system for managing patient records and appointments within a veterinary clinic. This showcase provides an overview of the key features, implementation details, and a glimpse into the execution of the system.

C, Data Structures and Algorithms, Modular Approach

Import patient data from "patientData.txt."

Maintain a collection of patient records, each represented by the 

Up to 20 patients can be managed simultaneously.

Import appointment data from "appointmentData.txt."

Support for managing up to 50 appointments concurrently.

Utilize a menu-based user interface for easy interaction.

Display informative messages, such as the number of imported patient and appointment records.

: Aggregates patient and appointment data.

: Reads patient data from "patientData.txt" and populates the patient array.

: Reads appointment data from "appointmentData.txt" and fills the appointment array.

: Main menu function for user interaction.

The Veterinary Clinic Management System, a showcase project in my portfolio, demonstrates my skills in C programming and system design. This project not only fulfills the requirements of the assignment but also showcases my ability to create efficient and user-friendly solutions for real-world scenarios.

Veterinary Clinic Management System

https://github.com/DevS0ni/Assembly-Line-Simulation-Project

Developed a C++ simulation of an assembly line with multiple stations for processing customer orders. The project demonstrates proficiency in object-oriented programming and modular design.

C++, Object-Oriented Programming, Modular Approach

 for parsing input files and managing display formatting.

 class for representing assembly line stations.

 module to manage individual customer orders and item filling.

Ensured restricted copy and move operations for 

 class to represent active stations and fill customer orders.

 to configure and manage the assembly line.

C++ programming and object-oriented design.

Dynamic memory allocation and resource management.

Implementation of modular and interconnected classes.

GUI implementation for interactive user experience.

Additional features like order prioritization and real-time status updates.

Exploring parallel processing for assembly line optimization.

Configure input files for station linkages.

Monitor the simulation progress in the console.

This project demonstrates my ability to design and implement complex systems using C++ and showcases my skills in software development and problem-solving.

Assembly Line Simulation Project

Weather Data Analysis System - Ontario Weather Analysis Service

https://github.com/DevS0ni/Weather-Data-Analysis-System

 Developed a robust Ontario Weather Analysis Service, a command-line application written in C, to analyze and visualize weather data for the year 2023. The application provides comprehensive insights into precipitation patterns, allowing users to view records, sort by region, month, and location, and extract meaningful statistics.

C, Data Structures and Algorithms, Modular Programming Approach

 Implemented functions to view all weather records, sorted by region, month, and location, facilitating quick and efficient data analysis.

 Employed sorting algorithms to arrange records based on precipitation, both in descending order by region and ascending order by month.

 Created an intuitive main menu for easy navigation, allowing users to choose specific analyses and explore weather data effortlessly.

 Integrated a file import feature to read weather data from external files, enhancing the flexibility and scalability of the application.

 Implemented functions to calculate the total precipitation and average precipitation for regions and months, providing valuable statistical summaries.

Successfully handled diverse data sets, ensuring accurate analysis and reliable performance.

Incorporated user input validation and error handling, enhancing the robustness and user experience of the application.

 Standard I/O operations for reading and processing data from external files.

 Implemented sorting algorithms for efficient data organization.

 The Ontario Weather Analysis Service provides a powerful tool for meteorologists, researchers, and weather enthusiasts to gain deep insights into precipitation trends. The application's robust functionality and user-friendly design contribute to a seamless and efficient weather data analysis experience.

 Plans include incorporating additional features such as graphical visualization, extended data support, and real-time data integration to further enhance the application's capabilities.

Weather Data Analysis System

https://github.com/DevS0ni/Seneca-Library-Management-System

 The Seneca Library Management System is a comprehensive and user-friendly application designed to streamline the operations of a library. Developed through multiple milestones, this project aims to provide efficient tools for managing publications, handling user interactions, and ensuring the smooth functioning of a library environment.

 Manages the loading and saving of publication data from/to a file, ensuring persistent data storage.

 Dynamically stores Publication objects, allowing efficient management and retrieval of library records.

 Utilizes menus for various operations, offering users an intuitive way to interact with the library system.

 Provides options for selecting the type of publication during different operations, enhancing flexibility.

 Implements polymorphism to handle different types of publications (e.g., Book, Publication) within a unified structure.

 Ensures the integrity of publication data by validating inputs during creation and modification.

 Assigns unique library reference numbers to each publication, facilitating easy identification.

 Enables users to dynamically select publications based on specified criteria such as title, type, and availability.

 Utilizes a menu-driven interface for search operations, allowing users to interact seamlessly with the selection process.

 Manages date-related operations, providing a reliable framework for tracking publication dates and managing due dates for checkouts.

 Facilitate the loading of publications from a data file and the subsequent saving of changes, ensuring data persistence.

 Allows users to search for publications based on different criteria, including title and type, enhancing the discoverability of items in the library.

 Enable users to check out publications from the library and return them, ensuring proper handling of due dates and penalties for overdue items.

 Retrieves the address of a Publication object with a specified library reference number, supporting efficient access to individual publications.

NewPublication and RemovePublication Methods:

 Support the addition and removal of publications, maintaining the integrity of the library's collection.

Demonstrates the execution of critical operations, including adding new publications, removing publications, checking out items, and returning items.

Illustrates user interactions, such as searching for specific titles, confirming actions, and handling various scenarios, including aborting operations.

 The Seneca Library Management System represents a comprehensive and well-structured solution for library operations. With modular design, robust data handling, and a user-friendly interface, this project showcases the successful integration of various components to create an effective tool for managing library resources. Whether it's adding new publications, searching for items, or handling checkouts, the system provides a reliable platform for efficient library management.

Seneca Library Management System

IoT-Based Security System with Motion Detection

https://github.com/DevS0ni/Python-IOT-Based-Security-Surveillance-with-Motion-Detection

 Developed an Internet of Things (IoT) based security system using a Raspberry Pi 4, integrated with a camera module. The system detects motion and captures a surveillance video when motion is detected, subsequently sending a security alert email with the attached video file to the user.

 Implemented motion detection using a GPIO pin on the Raspberry Pi, allowing the system to identify and respond to movement in the monitored space.

 Utilized the Raspberry Pi Camera module to capture a 10-second surveillance video upon detecting motion. The video is stored in H.264 format for efficient storage and processing.

 Integrated email functionality to send a security alert to the user's specified email address. The email includes a descriptive subject, body text, and an attached MP4 video file of the detected motion.

 Implemented secure email transmission over the SMTP protocol using the Gmail server. The system requires the user's Gmail credentials for authentication.

 Managed file storage and deletion to optimize storage space. Old video files are removed to ensure the system operates efficiently.

 Served as the main processing unit for running the security system.

 Captured high-quality surveillance videos in real-time.

 Used for motion detection through a connected sensor.

 Employed for sending security alert emails.

 Developed the system using Python for GPIO control, camera operation, and email handling.

 Utilized for converting and processing H.264 video files into MP4 format.

The system is set up with a Raspberry Pi 4, connected to a camera module and a motion sensor.

The GPIO pin (pin 11) is configured to detect motion changes.

Users need to provide their Gmail credentials and specify the recipient's email address.

The system continuously monitors the space using the motion sensor.

When motion is detected, the Raspberry Pi Camera captures a 10-second video.

The video is converted to MP4 format using MP4Box for compatibility.

A security alert email is sent to the specified email address, including the attached video file.

Old video files are automatically removed for efficient storage management.

 This IoT-based security system provides an affordable and effective solution for users to monitor and receive timely alerts regarding motion detection in their designated spaces. It enhances security measures with real-time video surveillance and instant email notifications.

 Future enhancements may include integrating cloud storage for remote video access, implementing real-time monitoring through a web interface, and enhancing the system's scalability for broader applications.

IoT - Based Security Surveillance System with Motion Detection (Raspberry PI - Python)

https://github.com/DevS0ni/InkChronicle-Web-Blog-Application

The *InkChronicle* is a web application that allows users to create, manage, and view blog posts.
It includes features for user registration, authentication, and authorization.
Users can create and publish blog posts, manage post categories, and view a list of published posts.
The application also supports user login/logout functionality and keeps track of user login history.

JavaScript - Node.js, Tailwind CSS, HTML5, BootStrap, PostgreSQL, ElephantSQL, MongoDB

       Users can register for an account.
       Registered users can log in and log out of the system.
       User authentication is implemented using client sessions.
       Blog Post Management:

Users can create and publish blog posts.
Posts include a title, body, category, publication date, and a featured image.
Users can view a list of all published posts and filter them by category.
Latest published posts are displayed on the main blog page.

Users can view and manage post categories.
Categories can be added, and existing categories can be deleted.

The application uses the Handlebars template engine for rendering views.
The UI includes navigation links, active route highlighting, and a clean layout.
Client-side and server-side form validations are implemented.
Image Upload:

Cloudinary is integrated for image uploading and hosting.
User Login History:

The application keeps track of user login history, including the user's IP address and user-agent information.

Proper error handling is implemented throughout the application.


- Node.js
- Express.js
- Handlebars (View Engine)
- Multer (File Upload)
- Cloudinary (Image Hosting)
- Client-Sessions (User Session Management)


Clone the project repository.
Install dependencies using npm install.
Configure Cloudinary credentials.
Run the application using npm start.
Access the application at http://localhost:8080.


- public: Contains static files (CSS, images, etc.).
- views: Handlebars templates for rendering views.
- blog-service.js: Module for handling blog-related data and operations.
- auth-service.js: Module for user authentication and registration.
- server.js: Main application file with Express.js setup and routes.

 The project assumes a certain folder structure and dependencies.
Ensure that you have the required credentials for Cloudinary and necessary packages installed before running the application.

InkChronicle - Web Blog Application

https://github.com/DevS0ni/PyGame-SmartMove-Crystal-Quest-Game

CrystalOverflow Game is an engaging and strategic puzzle-based board game developed using Python and the Pygame library. Players dive into a dynamic world of crystals and gemstones, where they must strategically place their pieces on the board, triggering chain reactions and outsmarting their opponents.

 Plan your moves carefully to outmaneuver your opponent and gain control of the game board.

 Adjust the smartness level of your in-game AI opponent to tailor the difficulty to your preference.

 Enjoy visually stunning gemstone sprites and animations as you play.

 Choose between playing against a friend or challenging an AI opponent with adjustable difficulty.

 Experience the thrill of the overflow mechanic, where well-placed moves can lead to spectacular chain reactions.

 Choose between playing as a human or challenging an AI opponent for each player.

 Strategically place your gemstone pieces on the board, aiming for control and domination.

 Witness the overflow mechanic as well-placed moves trigger cascading reactions, influencing the game's outcome.

 Adjust the smartness level of the AI opponent to customize the difficulty and challenge yourself.

Be the first player to achieve a specific pattern or prevent your opponent from making a legal move.

Enjoy the excitement of victory or learn from defeat to refine your strategy for the next round.

 Main script containing the game loop, player interactions, and Pygame setup.

 Module for implementing a Queue data structure.

 Modules containing AI logic for Player 1 and Player 2, respectively.

Embark on a strategic journey through the world of CrystalOverflow Game, where every move counts, and victory awaits the most cunning strategist.

PyGame - SmartMove Crystal Quest

https://github.com/DevS0ni/Valet-Parking-Application-Project

 The Valet Parking System is a C++ application designed to manage the operations of a valet parking service. The system allows for the parking and retrieval of vehicles, maintaining a record of parked vehicles, providing parking tickets, and handling various functionalities related to valet parking.

 ifstream, ofstream (for reading and writing data files)

 Utilizes classes and polymorphism for managing different types of vehicles (Car, Motorcycle) and Modular Approach.

 Allocates and deallocates memory for vehicle objects during runtime.

 Utilizes console-based user interfaces for input and output.

 Saves and loads vehicle records to/from data files.

 Defines a constant for the maximum number of parking spots.

 Tracks the number of spots, number of parked vehicles, and an array of vehicle pointers representing parking spots.

 Initializes the parking module with the number of spots, checks for validity, and initializes parking spots array.

 Implements various functionalities such as checking if the parking is empty, printing parking status, loading and saving data, listing parked vehicles, finding vehicles, parking a vehicle, and returning a vehicle.

 Closes the parking by towing remaining vehicles.

 Utilizes polymorphism to handle different types of vehicles (Car, Motorcycle) through a common base class.

 Stores information such as license plate number, make, and model of the vehicle.

 Allocates and deallocates memory for vehicle objects dynamically.

 Supports reading and writing vehicles in comma-separated value mode.

 Manages date-related operations, supporting the tracking of vehicle entry and exit dates.

 Validates each functionality of the valet parking system, including parking, returning, listing, finding, and closing the parking.

 Tests scenarios with the maximum number of parking spots, invalid inputs, and situations where the parking is full.

 Verifies that data is correctly loaded and saved from/to data files.

 The Valet Parking System is a robust C++ application that efficiently manages the operations of a valet parking service. By incorporating OOP principles, dynamic memory management, and user-friendly interfaces, the system provides a comprehensive solution for handling vehicles, ensuring a smooth and organized valet parking experience.

Valet Parking System

https://github.com/DevS0ni/Movies-Record-Tracking-System

 The Movie Genre Search Application is a C++ program designed to facilitate users in exploring a curated list of the top 50 movies of all time based on their genres. The application allows users to input a specific movie genre of interest, and it returns a list of movies within that genre along with relevant details such as title, release year, rating, duration, genres, and consumer rating.

C++, Data Structures and Algorithms, Modular Approach

Users are prompted to enter a movie genre to initiate the search.

The application then displays a list of movies belonging to the specified genre.

The application provides comprehensive details for each movie, including title, release year, rating, duration, genres, and consumer rating.

The program loads data from an external file ("movies.dat") containing information about the top 50 movies.

It ensures robust handling of data, allowing users to explore a diverse range of movies.

The application features a user-friendly interface with clear instructions and prompts.

Users can easily navigate through the genre search process.

Utilizes a C++ structure named "Movie" to encapsulate information about each movie, promoting code modularity.

Stores movie data in an array of structures, accommodating up to 50 movies.

Implements file handling to read movie data from the "movies.dat" file.

Ensures proper opening and closing of the data file for seamless data retrieval.

Employs a function ("hasGenre") to determine whether a movie contains the specified genre.

Utilizes string manipulation functions to compare genres.

Incorporates functions ("readTitle," "readYear," etc.) for robust input validation while reading movie details from the data file.

Parses the genre information from a comma-separated string in the data file into an array of strings, enhancing flexibility.

Engages users in an iterative process, allowing them to conduct multiple genre searches.

Prompts users with a clear option to continue or exit the application.

 The Movie Genre Search Application combines functionality, data integrity, and user-friendly design to offer an efficient platform for exploring top movies based on user preferences. Its structured approach to file handling, data parsing, and user interaction make it a valuable tool for movie enthusiasts seeking a curated selection based on genres.

Movie Genre Search Application

https://github.com/DevS0ni/Coffee-Shop-Management-Database-Application

The Coffee Shop Management System is a comprehensive software solution designed to streamline and enhance the operations of a coffee shop. This system leverages C++ programming and Oracle Database to manage various aspects of the coffee shop, including order processing, customer information, and inventory management.

The system facilitates the generation of detailed reports on all orders placed, providing insights into order numbers, associated tables, product names, quantities, and order dates.

An additional report highlights outstanding orders, showcasing order numbers, corresponding tables, customer names, outstanding amounts, and order dates.

The system effectively manages inventory by providing a report on product availability. This report includes product IDs, names, associated categories, unit prices, and availability statuses.

Products are categorized into a variety of types, such as regular beverages, soft drinks, pastries, and more.

Utilizing Oracle OCCI, the system establishes a secure and efficient connection with the Oracle Database (myoracle12c.senecacollege.ca:1521/oracle12c).

SQL queries are employed to retrieve and process data, ensuring accurate and timely reporting.

The system is backed by a robust database schema consisting of the following tables:

 Stores information about product categories.

 Manages details about individual products, including category associations.

 Records details about tables within the coffee shop.

 Contains customer information such as customer ID, name, and phone number.

 Captures data related to new orders, including customer and table associations.

 Manages details about items within each order, including product and order associations.

 Stores information about various payment methods accepted.

 Records details of payments made for orders, including order and payment method associations.

The system is populated with sample data, including product categories, products, table details, customer information, new order details, order items, payment methods, and payments.

The Coffee Shop Management System serves as an efficient tool for coffee shop owners and staff to manage orders, track inventory, and ensure smooth operations. It demonstrates proficiency in database management, C++ programming, and Oracle OCCI, providing a solid foundation for further enhancements and customization.

Coffee Shop Management Database Application

COSEWIC SAR Data Analyser - Canada Species at Risk Analysis

https://github.com/DevS0ni/COSEWIC-Sar-Data-Analyser

This project focuses on analyzing data related to species at risk in Canada. The system loads data from a file, provides a user interface for data analysis, and presents insights based on various criteria such as year, province, taxon, and their combinations.

Reads species data from the "data.txt" file.

Handles potential errors, such as missing files.

Implements a menu-driven user interface for data analysis.

Dev Soni - Software Developer

My Portfolio

All of the projects I had worked on