Flutter News App for Android & iOS with Admin Panel

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is a complete news app with an admin panel that is developed on the Flutter framework developed by Google. It works on both android & iOS. It has all the common and special features that a typical news app has. We have used lots of animations to make this app user-friendly. It could be able to satisfy users with impressive UI design and smooth performance on both iOS and Android devices. If you are looking for a news or blog app for both iOS and Android, News Hour could be the best option for you.

What Will You Get

  1. Source code of app for both iOS & Android
  2. Source code of Admin Panel (Flutter Web)
  3. Step-by-step documentation.
  4. Future updates for free.

Top 10 Reasons to Buy

  1. Pixel perfect & elegant design with lots of animations
  2. Run on both iOS & Android devices
  3. Single code base & fasted backend service
  4. Super fast loading & great performance
  5. Rich functionalities & regular updates.
  6. Offline Database and image cache to use the app offline.
  7. Included Admin panel to access and control the app in one hand.
  8. Clean, Structured & easily readable code and save at least one month of development time.
  9. Developed on Google’s Flutter, which is fast and secure.
  10. Don’t have to buy any domain and hosting for the admin panel.

App Features

  1. Welcome & Beautiful On-Boarding Screens – Introduction screens to define the features of the app. It can be disabled from the admin panel.
  2. User Registration/Login: Login with email/password, social logins like Google, Facebook, and Apple (Only for iOS), Mobile number login, and Guest Login. Initial login can be disabled from the admin panel.
  3. Video Posts: Video posts with native video player. Three types of video formats are supported. Youtube, Video, and Network videos.
  4. Audio Posts: Audio posts support with SoundCloud stream url only.
  5. Users Account Control: Users can change their name and profile picture. Also, they can delete their account and data from the app.
  6. Animations: This app has full of animations. We have used inbuilt animations from Flutter and also used animation files from Lottie. You can change all the custom animations with your Lottie files.
  7. Categories, Sub-categories & Tags: Articles are divided into categories and sub-categories. Also, tags can be added to the articles.
  8. Post Views, Likes & Bookmarks: Posts views and user likes can be disabled from admin.
  9. Monetization: We have used Admob ads for monetization maintaining AdMob policy. Banner, Interstitial, Inline Native Ads are supported
  10. Inline Custom Ads:Like native ads, you can use custom ads within the news list. You can create and control your custom ads directly from the admin panel. Three types of custom ads are supported: Text Only, Image Only, and Image with Title Ads. The app will randomly select each ad for its assigned position. As with native ads, you can choose after how many posts you want to place the ads.
  11. Subscriptions: Subscriptions for premium articles and disabling ads. Subscription plans will be handled from your Google Play Store for Android and the Apple App Store for iOS. You can create your plans and prices by following our step-by-step documentation. Ads will be disabled for premium users. (An Extended license is required for the subscription feature)
  12. Push Notifications: We have used the Firebase push notification service which is completely free. Admin can send push notifications directly from the admin panel to all Android & iOS users in just one click. Push notification’s body also supports HTML text. That means HTML texts, images and videos will be supported too.
  13. Cached Image & Data: Used cache image service to save online images to a local database for a faster experience. Images & databases can be accessible even offline.
  14. Backend Service: We have used Firebase as a backend of this complete project which is fast and secure.
  15. Custom Security Rules: We have included custom security rules for the backend database which will secure the data from hackers. So, you don’t have to worry about database security.
  16. Multi-language Support: The app has multi-language support. You can use any language. We have added 10 prebuilt language files.
  17. RTL Support: RTL support for RTL-type languages like Arabic, Hebrew, etc.
  18. EU Data Protection Policy: EU data protection policy has been applied. Users can delete their accounts and data from the app anytime they want.
  19. Firebase Analytics: To access the real-time activity of the users.
  20. State Management: Riverpod
  21. Local Database: Hive and Shared Preferences.

Admin Panel Features

  1. The admin panel is also built on the Flutter framework. No custom domain and hosting are required for the admin panel. You will get them free from Firebase.
  2. Dashboard: Statistical overview of the users, articles, categories, tags, purchases, featured items & notifications.
  3. Notifications: You can send notifications directly from the admin panel. The notification body supports HTML texts, images, and videos. Post notifications are also supported
  4. Administrative Control: Assign authors, and disable/enable users from the app.
  5. Author Dashboard: Authors have individual dashboards where they can submit their articles and admin can approve.
  6. Customize App: Customize 30+ app specific features from the admin panel.
  7. Ads Control: Enable/Disable specific ads & create custom ads

For Live Demo & Enquiry  :

WhatsApps : +916263056779

Email : official@projectworlds.in

Script Come With :

  • Free Installation support
  • Free technical support
  • Future product updates
  • Quality checked by PROJECTWORLDS
  • Lowest price guarantee
  • 3 months support included

Flight Delay Prediction using Machine Learning Project

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Buy Source Code ₹1501

Delay is one of the most remembered performance indicators of any transportation system. Notably, commercial aviation players understand delay as the period by which a flight is late or postponed. Thus, a delay may be represented by the difference between scheduled and real times of departure or arrival of a plane. Country regulator authorities have a multitude of indicators related to tolerance thresholds for flight delays. Indeed, flight delay is an essential subject in the context of air transportation systems. In 2013, 36% of flights delayed by more than five minutes in Europe, 31.1% of flights delayed by more than 15 minutes in the United States. This indicates how relevant this indicator is and how it affects no matter the scale of airline meshes. To better understand the entire flight ecosystems, vast volumes of data from commercial aviation is collected every moment and stored in databases. Submerged in this massive amount of data produced by sensors and IoT, analysts and data scientists are intensifying their computational and data management skills to extract useful information from each datum. In this context, the procedure of comprehending the domain, managing data and applying a model is known as Data Science, a trend in solving challenging problems related to Big Data. In this project, we’ve performed an extensive data analysis in order to extract the important attributes/factors that are responsible for the delay of flight. Also, there will other factors that may influence the delay of the flight such as climate, natural calamities, pandemic, or technical issues, etc. in the airplane which has not been considered in this project as this factors varying depend on the location and such problems occurring have very less frequency.

Problem Statement

Flight delays are quite frequent (19% of the US domestic flights arrive more than 15 minutes late), and are a major source of frustration and cost for the passengers. As we will see, some flights are more frequently delayed than others, and there is an interest in providing this information to travellers.
Flight prediction is crucial during the decision-making process for all players of commercial aviation. Moreover, the development of accurate prediction models for flight delays became cumbersome due to the complexity of air transportation system, the number of methods for prediction, and the deluge of flight data. Based on data, we would like to analyse what are the major cause for flight delays and assign a probability on whether a particular flight will be delayed.

Objective

The objective of the project is to perform analysis of the historic flight data to gain valuable insights and build a predictive model to predict whether a flight will be delayed or not given a set of flight characteristics. Questions to be answered post analysis: • Does the month of flight have any impact on flight delays? • Flights to which destination have seen the most delays? • Which day of the week sees the least and most flight delays? • Which time of day is most suitable for preventing flight delays? • Which airline has the most number of flights delayed? • What are the primary causes for flight delays? The objective of the predictive model is to build a model to predict whether a flight will be delayed or not based on certain characteristics of the flight. Such a model may help both passengers as well as airline companies to predict future delays and minimize them.

Dataset Details

Dataset obtained from Kaggle:
https://www.kaggle.com/lampubhutia/nyc-flight-delay

Technologies Used

  1. Python
  2. HTML
  3. CSS
  4. Bootstrap
  5. Numpy
  6. Pandas
  7. Matplotlib
  8. Seaborn
  9. Flask

Steps to get started

Setup the virtual environment and turn it on
>> source Flight-Delay-Prediction/bin/activate (For Mac and Linux)
>> .\Flight-Delay-Prediction\Scripts\activate (For Windows)

Run the script
>> python app.py

Complete Online Shopping Website in PHP MySQL

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Buy Source Code ₹501

The rapid advancement of technology has transformed traditional shopping into a digital experience, making online shopping platforms indispensable in today’s world. This document details the development and features of a robust online shopping website that caters to diverse user needs. The platform not only simplifies the shopping process for customers but also provides a comprehensive administrative interface for managing products, orders, categories, and settings. By incorporating modern web technologies and a user-centric design, this platform ensures an engaging and efficient shopping experience. The system’s flexibility and scalability make it suitable for businesses aiming to establish a strong online presence in the competitive e-commerce market.

Detailed Description of Features for Online Shopping Website

  1. Homepage

The homepage serves as the primary entry point for users visiting the website. It includes:

  • Navigation Menu: Clearly visible at the top of the page, the menu includes links to key sections such as Home, Shop, Product, and Contact Us. This ensures easy navigation for users.
  • Search Box: Positioned prominently, it enables users to search for products using keywords or categories, providing a quick way to locate desired items.
  • Cart Button: Located on the right side of the header, this button displays the total number of items currently in the user's cart. Clicking on it redirects to the cart page where users can view or modify their selected items.
  • Login Button: Also positioned on the right, this button takes new and returning users to the login page, enabling them to access their accounts and personalized features.
  1. Shop Page

The Shop page provides an organized display of products sorted into various categories:

  • Categories include:
    • Shoes
    • Clothes
    • Fashion
    • Kids
    • Smartphones
    • Electronics
  • Users can click on a category to view all related products, including details such as price, availability, and specifications. This categorization simplifies product browsing and enhances user experience.
  1. User Registration

New users are required to create an account to access shopping and checkout features. The registration process includes:

  • Form Fields:
    • Name
    • Surname
    • Gender
    • Address
    • Username
    • Password
    • Contact Number
  • Agreement to Terms: Users must agree to the website’s terms and conditions by checking a box before submitting the registration form.
  • Post-Registration Process: Upon successful registration, users are redirected to the login page to access their account.
  1. User Login

Returning users log in to their accounts using:

  • Username and Password: These credentials are validated against the database.
  • Upon successful login, users are redirected to their User Dashboard where they can access all account-specific functionalities.

 

  1. User Dashboard

The User Dashboard is a personalized space for managing all user activities on the platform. Features include:

  • Product Browsing: Users can browse through products, add them to their cart, and view detailed descriptions.
  • Checkout:
    • Cash on Delivery (COD) is offered as a payment method.
    • Users can specify or modify their delivery address during checkout.
  • Wishlist:
    • Allows users to save products they plan to purchase later.
    • Wishlist items can be added to the cart at any time.
  • Order Management:
    • Users can view the status of their orders, categorized as Pending, Confirmed, or Delivered.
    • Option to download and print order invoices in PDF format for record-keeping.
  1. Admin Panel

The Admin Panel provides robust management tools accessible only to administrators. Admins log in using their unique credentials. Features include:

  1. Product Management
  • Add Products: Admins can input product details such as name, category, price, description, and stock quantity.
  • Edit/Update Products: Modify details of existing products to keep the catalog up-to-date.
  • Delete Products: Remove outdated or unavailable products from the database.
  1. Order Management
  • View Orders: Displays all customer orders along with details such as order ID, product name, quantity, status, and customer information.
  • Confirm Orders: Admins can change the status of an order from Pending to Confirmed.
  • Edit/Modify Orders: Allows adjustments to order details if necessary.
  • Delete Orders: Removes canceled or invalid orders.
  1. Category Management
  • Admins can create, edit, or delete product categories. Examples include Shoes, Clothes, Kids, Smartphones, and Electronics.
  • New categories can be added to enhance product organization.
  1. Settings
  • Discounts: Admins can set promotional discounts on products or categories to attract customers.
  • Delivery Fees: Configure fees based on the delivery location, including variations by state or city.
  1. Reports
  • Delivered Products Report:
    • Generate detailed lists of delivered products.
    • Includes information such as product name, price, and delivery date.
    • Useful for tracking sales and inventory management.
  1. Additional Features
  • Security:
    • Passwords are securely encrypted using robust hashing algorithms.
    • Sensitive data is safeguarded against unauthorized access.
  • Responsive Design:
    • The website is optimized for all devices, ensuring a seamless experience on desktops, tablets, and smartphones.
  • User-Friendly Interface:
    • Intuitive design simplifies navigation and usage for both users and admins.
  • PDF Invoice Generation:
    • Users can download professional invoices for completed orders, which include order details and pricing.

Technologies Used

  • Frontend: HTML, CSS, JavaScript, and Bootstrap for a responsive and user-friendly design.
  • Backend: PHP for server-side scripting and business logic.
  • Database: MySQL for secure data storage and management.
  • Server: Apache (XAMPP/WAMP/LAMP).

Online Student Hostel Management System PHP MySQL

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Buy Source Code ₹701

The Online Student Hostel Management System is a web-based platform designed to streamline and automate the management of hostel facilities for educational institutions. Built using PHP and MySQL, this system provides a centralized interface for students, wardens, and administrators to efficiently manage various aspects of hostel operations.

Purpose

The system aims to eliminate manual processes, improve operational efficiency, and provide a user-friendly experience for all stakeholders. By offering secure registration, room booking, complaint management, and feedback collection, the platform ensures a smooth hostel management process.

Key Features

For Students:

  1. Online Registration and Login:
    • Students can easily register using their personal and academic details.
    • Secure login using hashed passwords.
  2. Dashboard with Multiple Options:
    • My Profile: View and update personal details.
    • Room Booking: Select and book hostel rooms with seater preferences and food options.
    • Complaint Management: Lodge and track the status of complaints.
    • Feedback Submission: Share feedback about the hostel experience.
    • Change Password: Update login credentials securely.
  3. Room Details:
    • View information about available rooms, including seater types, monthly fees, and amenities.

For Wardens/Admins:

  1. Admin/Warden Login:
    • Role-based access to the management dashboard.
  2. Comprehensive Dashboard Metrics:
    • Track the total number of students, rooms, and complaints.
    • Monitor complaint statuses (New, In Progress, Closed).
    • View and analyze student feedback.
  3. Room and Stream Management:
    • Add and update room details (e.g., room number, seater type, monthly fees).
    • Register academic streams for student enrollment.
  4. Complaint Resolution:
    • Manage student complaints and update their statuses to ensure timely resolution.
  5. Feedback Analysis:
    • View feedback submissions to identify areas of improvement.

 

Functional Workflow

  1. Student Onboarding:
    • Students register, log in, and book rooms based on preferences.
    • Personal and academic information is securely stored in the database.
  2. Room Booking:
    • Students select seater types, food preferences, and stay duration.
    • The system calculates the total fees dynamically and confirms the booking.
  3. Complaint Management:
    • Students lodge complaints that are visible to wardens/admins.
    • Complaints are categorized as New, In Progress, or Closed.
  4. Admin/Warden Operations:
    • Add and manage rooms, streams, and student details.
    • Respond to complaints and review feedback for service enhancement.

Technologies Used

  • Frontend: HTML, CSS, JavaScript, and Bootstrap for a responsive and user-friendly design.
  • Backend: PHP for server-side scripting and business logic.
  • Database: MySQL for secure data storage and management.
  • Server: Apache (XAMPP/WAMP/LAMP).

Phishing Web Sites Detection Using Machine Learning Project

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The Internet has become an indispensable part of our life, However, It also has provided opportunities to anonymously perform malicious activities like Phishing. Phishers try to deceive their victims by social engineering or creating mockup websites to steal information such as account ID, username, password from individuals and organizations. Although many methods have been proposed to detect phishing websites, Phishers have evolved their methods to escape from these detection methods. One of the most successful methods for detecting these malicious activities is Machine Learning. This is because most Phishing attacks have some common characteristics which can be identified by machine learning methods.

Installation

The Code is written in Python 3.6.8. If you don't have Python installed you can find it here. If you are using a lower version of Python you can upgrade using the pip package, ensuring you have the latest version of pip. To install the required packages and libraries, run this command in the project directory after downloading the project:

pip install -r requirements.txt --user

Result

Accuracy of various model used for URL detection

ML ModelAccuracyf1_scoreRecallPrecision
0Gradient Boosting Classifier0.9740.9770.9940.986
1CatBoost Classifier0.9720.9750.9940.989
2XGBoost Classifier0.9690.9730.9930.984
3Multi-layer Perceptron0.9690.9730.9950.981
4Random Forest0.9670.9710.9930.990
5Support Vector Machine0.9640.9680.9800.965
6Decision Tree0.9600.9640.9910.993
7K-Nearest Neighbors0.9560.9610.9910.989
8Logistic Regression0.9340.9410.9430.927
9Naive Bayes Classifier0.6050.4540.2920.997
Conclusion
  1. The final take away form this project is to explore various machine learning models, perform Exploratory Data Analysis on phishing dataset and understanding their features.
  2. Creating this notebook helped me to learn a lot about the features affecting the models to detect whether URL is safe or not, also I came to know how to tuned model and how they affect the model performance.
  3. The final conclusion on the Phishing dataset is that the some feature like "HTTTPS", "AnchorURL", "WebsiteTraffic" have more importance to classify URL is phishing URL or not.
  4. Gradient Boosting Classifier currectly classify URL upto 97.4% respective classes and hence reduces the chance of malicious attachments.
Download Link
Ai Black and white image colorization with OpenCV Project Free Download

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Image colorization is an intriguing task in the field of computer vision that involves adding color to black and white images. This process transforms historical photographs, enhances low-quality video footage, and brings new life to vintage images. The advent of deep learning, particularly Convolutional Neural Networks (CNNs), has significantly improved the accuracy and realism of automated colorization.
In traditional image processing, colorization required manual effort and expertise, making it a time-consuming and labor-intensive task. However, with the development of AI and deep learning, we now have models that can learn from large datasets of color images and predict the appropriate colors for grayscale images. This not only saves time but also produces remarkably realistic results.
OpenCV (Open Source Computer Vision Library) is a powerful tool for computer vision and image processing. It provides a wide range of functions for manipulating images, making it an excellent choice for implementing AI-based image colorization. By leveraging OpenCV along with deep learning models, we can automate the process of colorizing black and white images with impressive accuracy.
This report delves into the methodology and implementation of AI-based black and white image colorization using OpenCV. We will discuss the conversion of images to different color spaces, the training of neural networks to predict color channels, and the application of these models to achieve vibrant and realistic colorization of grayscale images.
Technology Overview
Image colorization using AI and OpenCV is a fascinating blend of deep learning and computer vision technologies. Here's an overview of the key technologies and concepts involved:
  1. Deep Learning and Convolutional Neural Networks (CNNs):
    • Deep learning is a subset of machine learning that uses neural networks with many layers to model complex patterns in data.
    • CNNs are a type of deep learning model particularly effective for image processing tasks. They consist of layers that automatically and adaptively learn spatial hierarchies of features from input images.
  2. Color Space Conversion:
    • Images are typically processed in RGB color space but for colorization, conversion to Lab color space is common.
    • In Lab color space, the L channel represents lightness, while the a and b channels represent color information (chromaticity). This separation makes it easier for the model to predict color components.
  3. Training the CNN Model:
    • The model is trained on a large dataset of color images, learning to predict the a and b channels given the L channel.
    • Training involves feeding the network pairs of grayscale (L channel) and color (a and b channels) images, and optimizing the network to minimize the difference between predicted and actual color channels.
  4. Implementation with OpenCV:
    • OpenCV is a widely-used library in computer vision for image manipulation and processing. It provides tools for tasks like loading images, converting color spaces, and applying transformations.
    • OpenCV's dnn module can be used to load and run pre-trained CNN models, making it possible to integrate deep learning models into applications for tasks like colorization.
  5. Application Process:
    • Load the grayscale image.
    • Convert the image to Lab color space.
    • Use the trained CNN model to predict the a and b channels.
    • Combine the predicted a and b channels with the original L channel.
    • Convert the image back to RGB color space to get the final colorized image.
Benefits and Challenges
Benefits:
  • Automates the colorization process, saving time and effort.
  • Produces realistic and high-quality colorized images.
  • Can be applied to various fields like film restoration, historical photo enhancement, and more.
Challenges:
  • Requires a large and diverse dataset for training to achieve good results.
  • May struggle with complex images where the grayscale cues alone are insufficient to infer accurate colors.
  • Computationally intensive, requiring powerful hardware for both training and inference.
This combination of deep learning and computer vision techniques has opened up new possibilities in image colorization, making it more accessible and effective. Would you like to explore any of these technologies in more detail?
Download Link
College Complaint Registation System in Python Django

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Buy Source Code ₹701
The College Complaint Registration System streamlines the process of students registering complaints and tracking their resolution statuses. It incorporates role-based access for students and administrators. Django's robust framework is utilized to manage backend processes efficiently, while the frontend ensures a user-friendly experience.
Key Features and Modules
  1.  Student Module
Allows students to log in, register complaints, and monitor their status.
Functionality:
  1. User Authentication:
    • Students log in using their email and password.
    • Authentication is managed using Django's built-in User Authentication System.
  2. Dashboard:
    • Students are redirected to their dashboard upon login.
    • The dashboard includes:
      • Complaint Form where students fill in:
        • Name, Surname
        • Class, Department
        • Complaint Details
        • Upload:
          • Video Proof (e.g., .mp4, .avi)
          • Image Proof (e.g., .jpg, .png)
      • A "Submit" button to save the complaint to the database.
  3. Complaint Status Tracking:
    • Students can view their submitted complaints and track statuses:
      • Pending
      • Under Review
      • Resolved
    • Once marked "Resolved," the student can confirm it by clicking a Resolve button, which removes it from the dashboard.
  1.  Admin Module
Allows the admin to manage students and complaints effectively.
Functionality:
  1. Student Management:
    • Admin can:
      • Add students by providing:
        • Name, Surname, Email, Class, Department
        • Password is either system-generated or input by the admin.
      • Update or delete student details.
  2. Complaint Management:
    • Admin can:
      • View all complaints submitted by students.
      • Access uploaded proofs (video/image).
      • Update the complaint status:
        • Pending, Under Review, Resolved.
      • Add comments or feedback for students.
  3. Status Updates:
    • Students see real-time status updates on their dashboards.
Technologies and Design
Frontend:
  1. Languages:
    • HTML, CSS, JavaScript
  2. Frameworks/Libraries:
    • Bootstrap (for responsive design)
Backend:
  1. Framework: Django
  2. Database: SQLite (default) or any other Django-supported database like PostgreSQL or MySQL.
  3. File Handling:
    • Files are uploaded using Django's FileField or ImageField.
    • Proofs are stored in the media directory.
Online Food Ordering Management System in php mysql

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Buy Source Code ₹701
The Online Food Ordering System is a web-based application that facilitates users to order food online from a catalog of available menu items. It includes features for user and admin management and payment processing. The project is developed using PHP and MySQL as the core technologies, with a responsive front-end and a well-structured back-end.
Project Modules
  1.  User Module
This module focuses on user interaction, including registration, browsing the food menu, placing orders, and managing account details.
Features
  1. Registration and Login:
    • Users can register with their name, email, password, and phone number.
    • Upon successful registration, a wallet balance of ₹2000 is credited to the user's account.
    • Users can log in with their email and password.
    • Passwords are hashed for security (e.g., using bcrypt).
  2. Food Menu:
    • Displays all food items with the following details:
      • Food Name
      • Price
      • Image
    • Users can select the quantity for each item and proceed to place an order.
  3. Placing Orders:
    • Payment options:
      • Wallet: Deducts the amount from the user's wallet.
      • Cash on Delivery (COD): Allows users to enter a delivery address and opt for COD.
    • Upon order confirmation, users receive:
      • Order ID
      • List of items ordered
      • Total cost
      • Payment method
  4. Order Details:
    • Users can view all their orders categorized as:
      • Pending Orders: Orders yet to be delivered.
      • Delivered Orders: Orders successfully delivered.
    • Details include food name, order status, amount paid, and delivery address.
  5. User Dashboard:
    • Profile Management:
      • Update personal details (name, email, phone number, address).
    • Ticket Management:
      • Submit a ticket for issues (e.g., delayed delivery, wrong item).
    • Order History:
      • View details of past and pending orders.
  1.  Admin Module
The admin panel manages the application, including food items, user details, and orders.
Features
  1. Admin Login:
    • Admins log in using their username and password.
    • Authentication ensures only authorized access to the dashboard.
  2. Dashboard Overview:
    • User Management:
      • View a list of registered users with details like name, email, and phone number.
    • Order Management:
      • View and update order statuses (e.g., Pending → Delivered).
    • Ticket Management:
      • Respond to user-submitted tickets.
  3. Food Management:
    • Add Food:
      • Enter food name, price, and upload an image.
    • Edit/Delete Food:
      • Modify or remove existing food items.
  1.  Website Front-End
The front-end includes a user-friendly interface for visitors to explore the platform.
Pages
  1. Home Page:
    • Highlights the service's key features.
    • Includes a call-to-action for registering or logging in.
  2. Our Food Page:
    • Displays the food menu with prices and images.
  3. About Us Page:
    • Shares information about the platform/company.
  4. Order Now Page:
    • Redirects registered users to the food menu.
Technologies Used
  1. Front-End:
    • HTML: Structure of the web pages.
    • CSS: Styling for a visually appealing interface.
    • JavaScript: Dynamic behavior for user interactions.
    • Bootstrap: Responsive design for mobile and desktop users.
  2. Back-End:
    • PHP: Server-side scripting for managing user requests and interactions.
    • MySQL: Database for storing user details, food items, orders, and tickets.
  3. Web Server:
    • Apache: Part of the XAMPP/WAMP stack for hosting the application locally or on a server.
Database Design
  1.  Tables
  1. Users Table:
    • id: Primary Key
    • name: User's full name
    • email: User's email address
    • password: Hashed password
    • phone: Contact number
    • wallet_balance: Wallet amount (default ₹2000)
    • address: User's delivery address
  2. Food Items Table:
    • food_id: Primary Key
    • name: Food name
    • price: Food price
    • image: File path of the food image
  3. Orders Table:
    • order_id: Primary Key
    • user_id: Foreign Key (references Users.id)
    • items: JSON (food items and quantities)
    • total_amount: Total cost
    • payment_method: Wallet or COD
    • status: Pending or Delivered
    • delivery_address: Address for COD orders
  4. Tickets Table:
    • ticket_id: Primary Key
    • user_id: Foreign Key (references Users.id)
    • issue_description: User's complaint or issue
    • status: Open or Resolved
Key Functionalities
  1.  Payment System
  • Wallet integration with balance updates for each transaction.
  • COD option with address validation.
  1.  Order Management
  • Users can track orders by status (Pending/Delivered).
  • Admins can update the order status.
  1.  Responsive Design
  • Ensures usability on desktops, tablets, and smartphones.
  1.  Security
  • Password hashing (e.g., using bcrypt).
  • Prepared statements in SQL to prevent injection attacks.
Project Flow
  1. User Registers → Logs In → Browses Food Menu → Places Order.
  2. Admin Manages Food Items → Monitors Orders → Handles Tickets.
Enhancements and Future Scope
  1. Real-Time Notifications:
    • SMS or email alerts for order updates.
  2. Reviews and Ratings:
    • Allow users to rate food items.
  3. Discounts and Offers:
    • Implement promo codes or discounts.
  4. Multi-Language Support:
    • Cater to a diverse user base.
  5. Delivery Tracking:
    • Include real-time delivery tracking for users.
Conclusion
This system provides a robust and user-friendly platform for online food ordering, catering to both customers and administrators with well-defined modules and functionalities.
 
Online Student Expense Management System PHP MySQL

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BUY NOW Source Code ₹501
The **Student Expense Management System** is a core PHP and MySQL-based web application developed to help students manage their monthly expenses effectively. This system is designed to enable students to track their daily, weekly, and monthly expenses while setting a budget to monitor and control their spending. With user-friendly interfaces, the system provides an easy-to-use platform where students can register, log in, set budgets, and categorize expenses. This way, students gain better insights into their spending habits, which can be crucial for developing good financial management skills.
Features
User Registration and Login
  1.    - Register: Allows students to create an account using personal details (username, email, password).
  2.    - Login: Secure access to the system using credentials.
  3.    - Logout: Ensures secure exit from the system.
Dashboard
  1.    - Displays an overview of the student’s total budget, recent expenses, and remaining balance.
  2.    - Provides graphical representation (optional) of spending across different categories.
Budget Management
  1.    - Set Monthly Budget: Students can set a monthly budget to manage their expenses.
  2.    - Available Budget Display: Shows remaining budget after deducting expenses.
Expense Tracking
  1.    - Add Daily Expenses: Students can input their daily expenses along with a description and category (e.g., food, transport, entertainment).
  2.    - Weekly Expense Summary: Overview of all expenses incurred in a week.
  3.    - Monthly Expense Summary: Detailed summary of all expenses within a month.
  4.    - Filter by Category: View expenses by category to analyze specific spending areas.
Reports and Summaries
  1.    - Today’s Expenses: Overview of all expenses recorded for the current day.
  2.    - Weekly Summary: Shows total spending for each week in a month.
  3.    - Monthly Summary: Comprehensive monthly report that includes total expenses and remaining budget.
  4.    - Export Options (Optional): Ability to export expense reports in formats like PDF or Excel for personal records.
Settings
  1.    - Profile Management: Update personal information such as email or password.
  2.    - Notification Settings (Optional): Students can enable notifications or alerts for budget limits.
Responsive Design
  1.    - Ensures usability across devices, so students can access the system from laptops, tablets, or smartphones.
Brief overview of the technology:
Front end: HTML, CSS, JavaScript
  1. HTML: HTML is used to create and save web document. E.g. Notepad/Notepad++
  2. CSS : (Cascading Style Sheets) Create attractive Layout
  3. Bootstrap : responsive design mobile freindly site
  4. JavaScript: it is a programming language, commonly use with web browsers.
Back end: PHP, MySQL
  1. PHP: Hypertext Preprocessor (PHP) is a technology that allows software developers to create dynamically generated web pages, in HTML, XML, or other document types, as per client request. PHP is open source software.
  2. MySQL: MySql is a database, widely used for accessing querying, updating, and managing data in databases.
Software Requirement(any one)
  1. WAMP Server
  2. XAMPP Server
  3. MAMP Server
  4. LAMP Server
Installation Steps
1. Download zip file and Unzip file on your local server.

2. Put this file inside "c:/wamp/www/" .

3. Database Configuration

Open phpmyadmin

Create Database named studentexpense.

Import database db name.sql from downloaded folder(inside database)

4. Open Your browser put inside "http://localhost/project folder name/"
Online College Result Management System PHP MySQL

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BUY NOW Source Code ₹501
The Online College Result Management System is a web-based application that simplifies result management and provides a streamlined interface for students and college administrators. This system integrates an admin login and a student result view on the same platform. It offers students easy access to their academic performance details and enables administrators to efficiently manage student records, courses, semesters, and results.
Key Features
Student Section
  1. Student Login (View Result) Panel:
    • Students can access their results by entering their unique Student ID.
    • After entering the Student ID, they can view basic details such as Student ID, Name, Branch, Semester, and Percentage of Results.
  2. Detailed Result View:
    • Upon clicking "View Result," students can see their complete results, which includes:
      • Subject Code and Subject Name
      • Marks Obtained for each subject
      • Total Percentage
    • Students also have the option to print their result as a PDF, making it convenient to save or submit for future reference.
College Admin Panel
  1. Admin Login:
    • The admin logs in using a username and password. After a successful login, the admin is redirected to the dashboard.
  2. Dashboard Overview:
    • The dashboard provides an at-a-glance view of key data points:
      • Total Number of Students
      • Total Semesters
      • Total Subjects added by the admin
  3. Sidebar Navigation:
    • The admin can easily navigate through different sections via a sidebar menu.
  4. Semester Management:
    • View Semesters: View all existing semesters.
    • Add, Update, Delete, and Modify Semesters: Admins can manage semester data, allowing for easy updates and adjustments.
  5. Subject Management:
    • View Subjects: View a list of all subjects currently offered.
    • Add, Update, Delete, and Modify Subjects: Admins have control over the subject list, enabling them to keep course offerings up to date.
  6. Student Management:
    • View Students: Access a list of all students enrolled in the system.
    • Add, Update, Delete, and Modify Student Records: Admins can manage student records, ensuring data accuracy.
  7. Result Management:
    • Generate New Student Results: Admins can input student scores and generate a result based on their performance.
    • Save Results: Generated results are saved in the system, allowing for future access by both students and administrators.
This Online College Result Management System is designed to improve administrative efficiency and provide a simple, accessible way for students to review their academic progress. With a user-friendly interface and essential functionalities, the system caters to both students' need for easy result access and administrators' need for efficient data management.
Brief overview of the technology:
Front end: HTML, CSS, JavaScript
  1. HTML: HTML is used to create and save web document. E.g. Notepad/Notepad++
  2. CSS : (Cascading Style Sheets) Create attractive Layout
  3. Bootstrap : responsive design mobile freindly site
  4. JavaScript: it is a programming language, commonly use with web browsers.
Back end: PHP, MySQL
  1. PHP: Hypertext Preprocessor (PHP) is a technology that allows software developers to create dynamically generated web pages, in HTML, XML, or other document types, as per client request. PHP is open source software.
  2. MySQL: MySql is a database, widely used for accessing querying, updating, and managing data in databases.
Software Requirement(any one)
  1. WAMP Server
  2. XAMPP Server
  3. MAMP Server
  4. LAMP Server
Installation Steps
1. Download zip file and Unzip file on your local server.

2. Put this file inside "c:/wamp/www/" .

3. Database Configuration

Open phpmyadmin

Create Database named csrms.

Import database db name.sql from downloaded folder(inside database)

4. Open Your browser put inside "http://localhost/project folder name/"