ABDULLA MARUF

Siemens NX CAD Rotating Parking Structure

Overview

The Rotating Parking Structure project aims to address urban parking challenges by providing an efficient, space-saving solution. Utilizing NX CAD for design, the project incorporates a rotating mechanism to maximize parking space usage, making it an ideal solution for densely populated areas. This innovative design minimizes the time spent searching for parking, enhancing the user experience.

Problem Statement

The Siemens NX CAD Rotating Parking Structure addresses urban parking challenges by providing an innovative and space-saving solution. Utilizing NX CAD, it incorporates 3D modeling with a rotation mechanism, an elevator system for vertical movement, and a gear-operated structure for seamless car retrieval.

Libraries & Tools Used

• NX CAD: Used for 3D modeling and design of the rotating parking structure.

Features

• Rotating mechanism to save space and reduce vehicle retrieval time.
• Elevator system for vertical movement, allowing cars to go up and down.
• The top section moves in the opposite direction to the bottom section for efficient parking.
• Operated by a gear system for smooth and reliable functionality.

Heart Disease Prediction Model with Flask

Project Overview

This project is a machine learning-based web application designed to predict the likelihood of heart disease using patient data. It incorporates three machine learning algorithms—K-Nearest Neighbors (KNN), Decision Trees, and Logistic Regression—along with exploratory data analysis (EDA) to provide insights and predictions. The model is deployed using the Flask framework, offering an interactive interface for users to input data and receive predictions.

Key Features

• Machine Learning Models:
• K-Nearest Neighbors (KNN)
• Decision Trees
• Logistic Regression
• Web Application:
• Built with Flask.
• User-friendly interface for data input and prediction results.
• Data Analysis:
• Exploratory Data Analysis (EDA) performed on the heart.csv dataset.
• Visualizations such as histograms, boxplots, and correlation heatmaps.

Technologies Used

• Programming Language: Python
• Libraries:
• Machine Learning: scikit-learn
• Data Analysis and Visualization: pandas, numpy, matplotlib, seaborn
• Web Framework: Flask
• Dataset: heart.csv (contains patient data such as age, cholesterol levels, and resting blood pressure).

User Registration and Search System with SQL

Overview

The User Management System with SQL is a robust web application designed for efficiently managing user data. It offers user registration, login, advanced search functionality, and CRUD operations, ensuring a comprehensive platform for user information management.

Features

• User registration with detailed information fields.
• Secure user sign-in with timestamps for tracking.
• Advanced search options, including:
• Search by username, first/last name, salary, or age.
• Search users by salary or age ranges.
• Search users registered after or on the same day as another user.
• Retrieve users who registered today or have never signed in.
• Dynamic table for real-time user management.
• Full support for adding, editing, and deleting users.

Technologies

• Frontend: HTML5, CSS3, JavaScript
• Backend: Node.js with Express.js
• Database: MySQL for data management
• Other Tools: XAMPP and dotenv

SQL Create Table

Use the following SQL statement to create the users table:

      CREATE TABLE Users(
        username VARCHAR(50) PRIMARY KEY,
        password VARCHAR(50),
        firstname VARCHAR(50),
        lastname VARCHAR(50),
        salary FLOAT,
        age INTEGER,
        registerday DATE,
        signintime DATETIME
      );
          

View Demo

Watch the demonstration of the application here:

YouTube Demo

Setup Instructions

• Clone the repository to your local machine.
• Set up the backend by navigating to the project folder and running npm start.
• Access the frontend via http://localhost/database_javascript/project1/Frontend/auth.html.

SwiftUI Event Management App

Overview

While trying to discover local events, I realized that many people face difficulties in quickly finding, joining, and tracking events in their area. Many existing apps are either too cluttered or lack simple user flows for easy event management.

Problem Statement

Many people struggle to find, join, and track events in their local area due to the complexity or poor user experience of current event management apps. These apps often overwhelm users with too much information or lack an easy-to-navigate interface, making event management cumbersome.

My Solution

This SwiftUI Event Management App solves these issues by providing a simple, intuitive platform for users to browse and join local events. The app offers user authentication, event listings, and a custom calendar to track events. This approach allows users to easily keep their event plans organized.

Technologies Used

• SwiftUI: For building the user interface
• Xcode: The development environment for iOS applications
• Figma: For designing the app's UI/UX and ensuring a user-friendly experience

How to Run the App

• Clone the Repository
• Open the Project in Xcode
• Run the App on a simulator or a physical iOS device

Pantry Tracker

Overview

A responsive pantry inventory manager with sleek visuals and full CRUD functionality backed by Firebase Firestore.

Libraries & Tools Used

• React.js, Material-UI, Firebase

Features

• Real-time syncing of pantry items
• Add/edit/delete features with animations
• Mobile-first neon-inspired UI

Drone Project Management Dashboard

Overview

The Data Dashboard for KPI Analysis is an Excel-based solution designed to provide clear, concise, and visual insights into project performance and key metrics.

Objectives

• Create an easy-to-use Excel dashboard for visualizing KPIs.
• Track project progress, budget, and task completion effectively.
• Provide stakeholders with a quick, visual summary of performance metrics.

Features

• Interactive Excel Dashboard with various KPI charts
• Gantt Chart to track project phases and timelines
• Budget Chart comparing planned and actual expenditures
• Task Completion Pie Chart for visual task status representation
• Summary Table for quick insights on key performance metrics

Tools Used

• Microsoft Excel
• Excel Functions: SUM, IF, VLOOKUP, INDEX-MATCH
• Charts: Gantt chart, bar chart, line chart, pie chart

Visualizations

Usage

• Open the Excel File: Open KPI_Dashboard.xlsx in Excel
• Data Entry: Update raw data tables:
  • Timeline Data: Add tasks, start dates, end dates
  • Budget Data: Enter planned and actual expenses
  • Task Data: Update statuses (Completed, In Progress, On Hold)
• View the Dashboard: Navigate to the Dashboard tab for updated visuals

Future Improvements

• Automated data refresh using Excel macros
• Enhanced filters with slicers for better data interaction
• Additional KPIs such as ROI, efficiency, and forecast accuracy