Online Shopping Web Application BCA Project Using PHP

EXISTING SYSTEM:-

Current system customers have placed orders through phone calls, messages, or face-to-face communication. In the current system, the customer does not think about whether products are available or not.

PROBLEM WITH THE EXISTING SYSTEM:-

  • The current system totally works manually.
  • The existing system is based on a phone call or face-to-face communication.
  • The current system is very hard to operate and maintain.
  • The paper-based work so the records are lost sometimes.

PROPOSED SYSTEM (NEW SYSTEM):-

The Online shopping web application is easy for customers because customer purchase items in stay in the home on their computers. In this new system customer view, a variety of products and what’s products are unavailable(finished), and what products are available. You can also visit & download the Java Console Application project on Online Shopping Management System.

ADVANTAGES OF THE NEW SYSTEM:-

  • Effective communication between admin and customer.
  • Payment systems are available.
  • Home delivery is available.
  • Customers are aware of products and see what’s products available or not.
  • The product is nice or not given feedback.
  • View a product review.

TOOLS AND TECHNOLOGY:-

1) TECHNOLOGY:-

1. Frontend

  • PHP
  • Html, Css, js, Boostrap

2. Backend

  • My SQL

2) TOOLS:-

  • Sublime Text
  • Visual Studio Code
  • Draw.io
  • Microsoft PowerPoint
  • Microsoft Word
  • SQL Server

Project Functionalities:

  • Registration Page
  • Login Page
  • Admin Add Product Page
  • Admin Update Product Page
  • Admin Remove Product Page
  • Search Product Page
  • Buy Product Page
  • Payment Page
  • Cancel Order Page
  • Forgot Password Page
  • Change Password Page

Database tables:

  • Admin Table
  • Customer Table
  • Cart Table
  • Order Table
  • Product Table
  • Category Table
  • Payment Table
  • Feedback Table

Also, Read this Development of an Online Shopping Bot using IBM Watson

Also, Read this Analyzing Online Shopping Data QlikView Project

Acknowledgment

We express our heart gratitude to a number of people who extended their full support and cooperation in developing this project first, We would like to take this opportunity to thank our College for giving us this opportunity and a platform for discovering and developing our potential, This kind of experience that we have received while making this project report is so immense the narrating that in few words is difficult.

After putting in such hard work we have realized that takes to work in the shop and do a project. Our Institute and colleagues have been great sources of help without them we were unable to do this project.
Therefore, our project is a small drop in the water sea. We have learned many things from being a part of the concept of family.

After that our heartiest thank is to our internal guide as well as respected faculty for entrusting us with responsible and acting as a ray of light in the darkness. We find ourselves self-short of the world to describe our feeling for the role he played as a friend, a philosopher, and a guide, whenever we were in need.

Lastly, we are thankful to our parents for their blessing, Love, and Support. We are unable to traverse through this most significant stage of life and also, and we would Like to take this opportunity to express our regards to all our friends and faculties who have helped us directly or indirectly during the execution of the project. We are privileged and thankful to all for bringing our errors and shortcoming. This Online Shopping Store C# and SQL Website is related to the Online Shopping PHP Web Application Project.

Gym Fitness Management System Python Project using Django, HTML5, CSS, JS, MySQL

Introduction

  • The aim of creating this project is to bring every manual activity of the gym to the website or on the online platform.
  • This helps in making work easy for the gym staff which is lengthy and a little bit complex because of doing it on paper.
  • This website also helps the member of a gym, through this website the members can track their attendance manage their schedule, and many more things which we will discuss further.
  • It also allows guest users to apply for Gym membership directly via the website.
  • Trainers of the gym also can track their attendance and workout details of members via this website.
  • Trainers can prepare workout schedules and diet charts for members via this website.

Entities:

  • Admin
  • Trainer
  • Member
  • Guest

Project Profile

Requirement Gathering:

ADMIN:

Admin is the one who manages the whole website and has every access right to the website. Admin can do the following things:-

  • Admin can log in.
  • Admin can add, update or remove Gym Details.
  • Admin can manage the members and trainers of the Gym.
  • Admin can manage the attendance of members and trainers.
  • Admin can manage memberships.
  • Admin can sell Gym products.
  • Admin can provide fitness blogs and videos.
  • Admin can manage payments.
  • Admin can generate reports.

MEMBER:

Members are like clients of the Gym. Member can also access many things on a website like purchase products, view attendance, etc. member can do the following things:-

  • Member can log in.
  • Member can manage his/her profile.
  • Member can track his/her attendance.
  • Members can watch training videos and workout schedules and diet charts provided by Trainer.
  • Members can buy Gym products.
  • Members can manage payments for membership renewal.
  • Members can provide feedback for the website and Gym.

TRAINER:

Trainers are like employees of the gym. Trainers will do things like managing the workout schedule and diet chart of members. A trainer can do the following things:-

  • A trainer can log in.
  • A trainer can manage his/her own profile.
  • A trainer can view or track the attendance of members and his/her own.
  • A trainer can manage users’ workout schedules and diet charts.
  • Trainers can upload workout videos for users.
  • Trainers can give reward points to members on the basis of their weekly performance.

GUEST

Guests can only serve or see the gym website, he/she can do anything only after registering for the gym and website.
• Guest users can view the website.
• Guest users can register/Apply for a Gym membership

ER Diagram:

Existing System

  • Customer data is stored manually either in registers or in MS Excel.
  • Books are maintained to keep track of Customer attendance.
  • Payment transactions are kept in books.
  • Currently, the GYM does not have any advanced system to manage the GYM.

Proposed System

  • In the new system trainers and members can track their attendance from anywhere.
  • In the new system, a member can get his/her diet chart according to their workout plan.
  • In the new system, members can get a workout schedule from the trainer, while they also get rewards for points for achieving workout targets.
  • In this system, members can watch workout videos provided by their trainers which helps them to do exercise at home.
  • Here members can also purchase gym products.

Tools And Technology Used

FrontEnd: HTML5, CSS 2.1, JS
Backend: Mysql 5.5
Framework: Django 3.1 (Python 3.8)
Other Tools: Microsoft Powerpoint 2019, EDraw max 9.0, Microsoft Visio 2016, and Microsoft Word 2019

Data Dictionary

1) Table Name: User_Type

Table Description: Contains details of user type. It will give information about the type of user whether it is a member, trainer, or admin in the User_Master table.

2) Table Name: User_Master

Table Description: Contains details about users. It will contain all the basic information about users like name, email, gender, address, mobile no. etc along with the type of user.

3) Table Name: Plan_Master

Table Description: Contains details about membership plans. It will contain all the basic details about plans that a member can choose for a gym membership.

4) Table Name: Membership_Master

Table Description: Contains details about members’ memberships. It will contain all information regarding memberships of members according to their chosen plan.

5) Table Name: Trainer Details

Table Description: Contains details about the trainer. It will contain additional details about trainers along with details in the User_Master Table.

6) Table Name: Payment_Master

Table Description: Contains details about payments. It will contain the payment details of Memberships of a member

7) Table Name: Product_Master.

Table Description: Contains details about Gym products. It will contain basic information about products that the admin wants to sell and that a member can buy.

8) Table Name: Feedback_Master

Table Description: Contains details about feedback. It will contain feedback details given by members about the Gym.

9) Table Name: Workout_Master

Table Description: Contains workout details of members. It will contain members’ workout details like diet charts, workout schedules, workout videos, and reward points provided by trainers.

10) Table Name: Order_Master

Table Description: Contains Order Details. It will contain basic order details like which member has made the order, date of placing an order, delivery date, etc. of orders made by members for their purchase of products

11) Table Name: Order_Details

Table Description: It contains order Details. It will contain additional information about orders like the product purchased, the quantity of the product, the Price of the Product, etc. in relation to the Order_Master table.

12) Table Name: Attendance_Master

Table Description: Contains details about the attendance of users. It will contain day-to-day attendance details of members and trainers which will be added by admin.

Modules Functionalities:

ADMIN SIDE:

  • Login page for admin with validations. The email id Field Should not be empty. Email id should match the requested format which contains @ and (.)
  • Admin not allowed to login due to invalid username.
  • Change the Password page of Admin, the retyped password doesn’t match the validation Correct admin username and password:
  • Home page of Admin:
  • Admin dashboard. It Shows Side Panel which directs it to the selected page to be visited. The Page shows the direct link and information of User_type, Users, Trainer details, Attendance, and plans.
  • Add User Type: Admin is adding user type member
  • When the view tab of User type is clicked type of users is shown on this page
  • Add Users window can be opened from the side panel and the Admin can add a new user.
  • View Users window- All the users are shown here to the admin where the admin can take actions like edit and delete.
  • When the view part of Plans in the side menu is clicked plan details are shown.
  • Add Plans window-Admin can add new plan details in this window.
  • Admin can add membership details of the user, here validation is showing where the amount field is required.
  • When viewing a part of Membership Details in the side menu clicked Membership details table is shown
  • Attendance adds window- In add attendance window admin can add attendance details of users.
  • When view part of attendance in the side menu is clicked attendance details of users are shown
  • Then add part of Trainer Details is clicked, Admin can add details of the trainer.
  • View part of Trainer Details where Details of the trainer have been shown.
  • Add payment window is open when adding part of Payment Details is clicked, Admin can approve Payment Status.
  • When the view part of Payment details is clicked Payment Details is shown.
  • Add product window is shown when clicking on the add part of the Products.
  • When the view part of the Products tab is clicked all product details with price and quantity have been shown.
  • Add Workout Details Window – The admin can add Workout Details of a particular user by adding a diet chart, workout schedule, and workout videos for the user.
  • View the Workout Details window where all the details of a user’s workout(including diet chart and schedule) are shown.
  • View Order window – All the details with delivery status are shown in this window.
  • View Feedback window: Admin can view feedback and ratings given by users in this window.

TRAINER SIDE:

  • Trainer Login Page:
  • Trainer dashboard which contains information about trainers with Edit Profile and Change Password Link. It Shows Side Panel which directs it to the selected page to be visited. The Page shows the direct link and information on Attendance and Workout Details.
  • When Change Password Link is clicked, the trainer will be redirected to the Change Password Page where he/she can change their login password:-
  • Change Password Validations:-
  • When the My Attendance part of Attendance in the side menu is clicked attendance details of his/her own are shown:-
  • When the Members Attendance part of Attendance in the side menu is clicked attendance details of the member are shown:-
  • Dashboard Showing Add and View Option in Workout Menu of Side Bar :
  • Add Workout Details Window – The trainer can add Workout Details of a particular user by adding a diet chart, workout schedule, and workout videos for the member.
  • View Workout Details Window: Details of member workouts including diet chart, workout schedule, and total reward points are shown in this window.

GUEST SIDE:

  • HomePage:- The starting point of the website/first page of the website
  • About Options:-
  • About Us page giving information about GYM:-
  • FAQ Page:- It Contains all the frequently asked questions with their answers
  • Testimonial Page:- It contains all the reviews given by the members.
  • Contact Us Page:- It contains all the contact details of the gym.
  • When a user clicks on the Apply For Membership tab Registration page is opened which Collects user data for registration so that the user can make a login.
  • Registration Page Showing How to Apply for the GYM Membership.
  • Registration page displaying validation:-
  • After Successfully filling Registration Form, the User will be redirected to the Payment Confirmation Form which will show the user information along with the plan he has chosen while registering then the user has to choose how payment was done, enter transaction no. and has to upload Payment Receipt.
  • When User will successfully submit the payment confirmation form, they will be redirected to the Login page or can open it from Login Tab.
  • Login Page with Validation:-
  • Forgot password? – asking for a registered email ID
  • Password received by the customer through email.

USER SIDE:

  • After Successful Login User will be redirected to the Homepage. The Apply For Membership and Login heading is changed to My Account with Profile, Membership, Attendance, and Logout Options.
  • When the User Clicks on Membership, He/she will be redirected to the membership page which contains the membership details the user.
  • When the User Clicks on the Attendance option in the My Account Section he/she will be redirected to the Attendance Page which contains the attendance details of the user:-
  • Shop Page:- It contains all the products with details that the gym wants to sell.
  • Add to cart option on the product:-
  • Shop Page showing Add to Cart Option for a product:-
  • After clicking add to cart from Shop Page, Cart is opened which shows items in your cart.
  • If the Customer wants to shop for more than one product, he/she can click on Buy More and add other products also.
  • When the User clicks on Proceed to Checkout, the Checkout page is opened which shows order details and Billing details and gives the summary of your orders.
  • After clicking Place order, the user is provided with the appropriate order placed message and view order option. On clicking view order user will be shown all the details of his/her orders.
  • When the User Clicks on View Order, he/she will be redirected to My Orders Page which contains all the order details of orders made by the member.
  • When the user Clicks on More details, he/she will be redirected to the order details page which contains additional details about the order.
  • My Workout Page:- It will give the user his/her option to download his/her diet chart, workout schedule, and workout videos provided by the trainer
  • Blog Page:- It contains all the fitness blogs that users can read.
  • Homepage showing My Account Section having Options Profile, Membership, Attendance, Logout:-
  • On clicking the Profile Option in the My Account Section, the User will be redirected to the My Account Page which contains all details of the currently Logged In User like name, address, gender, email, mobile, etc. with the Edit Profile/Change Password Option.
  • When the User Clicks on Change Password, he/she will be redirected to the Change Password Page where the user can change his/her old password new password.
    Change password Validations:-
  • Showing Logout Option In My Account Menu:-
  • When the User Clicks on Logout, he/she will be redirected to Login Page.
  • Report of all the users registered with Dynamo Fitness.
  • Various Filters for user reports like reports based on user type, i.e. members or trainers, and reports based on gender.
  • Report after using the user type and gender filter it will show only gym members who are female as we used the user type filter as members and gender filter as female.
  • Report on Current plan and membership of the members it displays the name and plan type of members.
  • Membership report using start date filter for plans starting date.
  • The report shows the list of members whose memberships start in a selected month.
  • Filter based on plan title i.e. basic, standard, and ultimate plan.
  • list of members who are registered with the standard plan.
  • Report after using the print option, the report shows the member with their specific plan with a start date and end date of the plan.
  • Report for the feedback given by users with filters that are gender and ratings.
  • Report using a rating filter, it will display users with specific ratings.
  • Report showing list of users given rating 9.
  • Feedback report after selecting the print option.
  • PDF view of feedback report using the view pdf option.
  • Product order report showing user id with the product they ordered
  • A report showing a filter of product names with different products available.
  • Reports after applying the product name filter i.e. dumbells will show the product id and user id of the users who ordered them.
  • Report after using a filter with the Delivery status it displays the product which is delivered.
  • The attendance report shows the attendance of users that are members and trainers on day to day basis.
  • The filter of the Attendance report is based on the user type i.e. Member and Trainer.
  • The attendance report on the base of the trainer filter displays only trainer attendance.
  • Report after selecting the print option.
  • Date filter option for a report which shows the attendance of users of a specific date.
  • Report After Filter By Attendance Date and Gender

CONCLUSION

The entire duration of this project has been a great learning experience for us. It has introduced us to the working of real-life projects and taught us to face obstacles while developing them. By developing this web application, we hereby conclude that at Gym Management we have achieved our aim at the following:

1) Building a platform where people can apply for a GYM Membership at any place and start their workout activities even at Home.
2) We believe that this website has made it easier for the GYM Owner to manage the information regarding different aspects of the Gym.
3) This website has also made it easier for trainers to manage the workout activities of members. We also hope to expand the scale of the project and make it ubiquitous by developing it for all digital platforms.

Download the complete project on Gym Fitness Management System Project using Python, MySQL, and Django Framework.

Fake Disaster Tweet Detection Web-App Python Machine Learning Project

This project “Fake Disaster Tweet Detection” aims to help predict, whether a tweet weather it is fake or real. It uses the Multinomial Naïve Bayes approach for detecting fake or real tweets from existing datasets available on Kaggle. The classifier will be trained only on text data. Traditionally text analysis is performed using Natural Language Processing also known as NLP. Natural language processing is a field that comes under Artificial Intelligence. Its main focus is on letting computers understand human language and process it. NLP helps recognize and predict diseases using speech, it helps in sentiment analysis, cognitive assistant, spam detection, the healthcare industry, etc. In this project Training Data is pre-processed, then sent to the classifier, then and the classifier predicts weather the tweet is real or fake.

This project is made on Jupyter Notebook which is a part of Anaconda Navigator. This project ran successfully on Jupyter Notebook. The dataset was successfully loaded into the notebook. All the extra python packages which were required for project completion were also loaded into the notebook. The model is also deployed successfully using HTML, CSS, python, and flask.

The accuracy score on test data is 77.977%. average recall value is 0.775 and the average precision score is 0.775. Precision is used to calculate a number of correct positive predictions made by the model. The recall is used to calculate the number of correct positive predictions made out of all the positive predictions that could have been made.

System Design

System Flowchart

System Flowchart

Problem: To detect disaster tweets whether it’s fake or real using a machine learning algorithm. In this, the concept of Natural language Processing is used.

Identification of data: In this project, I have used a dataset available on Kaggle competition based on Natural language processing. This project works only on text data. It has five columns:

  1. Id: It tells the unique identification of each tweet
  2. Text: It tells the tweet in text form
  3. Location: It tells the place from where the tweet was sent and it can be blank
  4. Keyword: It tells a particular word in the tweet and it can be blank
  5. Target: It tells the actual value of the tweet weather it’s a real tweet or Fake

Data-preprocessing: First the preprocessing is done in the dataset which includes the removal of punctuations, then the removal of URLs, digits, non-alphabets, and contractions, then tokenization and removing Stopwords, and removing Unicode. Then lemmatization is done on the dataset. After preprocessing Countvectorizer is used to convert text data into numerical data as the classifier only works for numerical data. The dataset is then split into 70% training data and 30% test data.

Definition of Training Data: The training dataset which contains 70% of the whole dataset is used for training the model.

Algorithm Section: In this project Multinomial Naïve Bayes classifier algorithm is used for detecting disaster tweets whether they are fake or real.

Evaluation with test set: Several text samples are passed through the model to check whether the classification algorithm gives the correct result or not.

Prediction Model

Implementation Work Details

The data-set which is used in this project “Fake disaster tweet detection” is taken from the Kaggle competition “Natural Language Processing with Disaster Tweets”. The data set contains 7613 samples. This project works only on text data. It has five columns:

  • Id: It tells the unique identification of each tweet
  • Text: It tells the tweet in text form
  • Location: It tells the place from where the tweet was sent and it can be blank
  • Keyword: It tells a particular word in the tweet and it can be blank
  • Target: It tells the actual value of the tweet weather it’s a real tweet

Step 2: Data-Preprocessing

  1. Removing Punctuations: Punctuations are removed with the help of the following python code
  1. Removing URLs, digits, non-alphabets, _: True means it has HTTP, and False means it does not have HTTP
  1. Removing Contraction: It expands the words which are written in short form like can’t is expanded into cannot, I’ll is expanded into I will, etc.
  1. Lowercase the text, tokenize them, and remove Stopwords: Tokenizing means splitting the text into a list of tokens. Stopwords are the words in the text which does not provide additional meaning to the text.
  1. Lemmatizing: It converts any word into its root form like running, ran into a run.
  1. Countvectorizer:

Text cannot be used to train our model, it has to be converted into numbers that our computer can understand, so far in this project, Countvectorizer is used. Countvectorizer counts the number of times each word appears in a document. Countvectorizer works as:

Step1: It first identifies unique words in the complete dataset.

Step 2: then it will create an array of zeros for each sample of the same length as above Step 3: It then takes each word at a time and find its occurrence in each sample in the dataset. The number of times the word appears in the sample will replace the zero positioned at the word in the list. This will repeat for every word. 

Step 3: Model Used:

In this project, the Multinomial Naïve Bayes approach is used for detecting fake or real tweets from existing datasets available on Kaggle. Naïve Bayes classifier is based on the probability theorem “Bayes Theorem” and also has an assumption of conditional independence among every pair.

System Testing

This project is made on Jupyter Notebook which is a part of Anaconda Navigator. This project ran successfully on Jupyter Notebook. The dataset was successfully loaded into the notebook. All the extra python packages which were required for project completion were also loaded into the notebook. The model is also deployed successfully using HTML, CSS, python, and flask.

The machine learning model is evaluated we normally use classification accuracy which is the number of correct predictions divided by the total number of predictions.

This accuracy measuring technique works well when there is an equal number of samples in the dataset belonging to each class. The accuracy score on test data is 77.977%. average recall value is 0.775 and the average precision score is 0.775. Precision is used to calculate a number of correct positive predictions made by the model. The recall is used to calculate the number of correct positive predictions made out of all the positive predictions that could have been made.

  • Precision = True Positives / (True Positives + False Positives)
  • Recall = True Positives / (True Positives + False Negatives)

Conclusion

In this project only one classification algorithm is used which is Multinomial Naïve Bayes. First, the preprocessing is done in the dataset which includes the removal of punctuations, then removal of URLs, digits, non-alphabets, and contractions, then tokenization and removing Stopwords, and removing Unicode. Then lemmatization is done on the dataset. After preprocessing Countvectorizer is used to convert text data into numerical data as the classifier only works for numerical data. The dataset is then split into 70% training data and 30% test data. The accuracy score on test data is 77.977%. average recall value is 0.775 and the average f1 score is 0.775.

Future Scope

In the future, some other classification algorithms can also be tried on this dataset like KNN, Support vector machine (SVM), Logistic Regression, and even Deep learning algorithms can also be used which give very high accuracy. Vectorizing can be done using other methods like word2vec, Tf-Idf vectorizer, etc.

Download the Complete Project on ake Disaster Tweet Detection Web Application Python-based Machine Learning Project.

Online Student Project Report Submission and Evaluation System PHP Project

Project Overview

The online project report submission and evaluation system enables the student to submit their project report online without submitting any physical file. Before the submission, the student needs to update their progress to the system and the lecturer can view their progress and give comments online.

The online project report submission and evaluation system is providing an online discussion and document sharing for students and lecturers. The pre-existing systems didn’t have the functionalities such as notifying the student when he/she is being added to the project group, online automatic generation of the certificate after the completion of the entire project, and many more which are being implemented in this version of the system.

The proposed system will take away the biggest risk out of the picture i.e. the manual transmission of all the tasks related to the project report and also the design is formulated in such a way that the impersonation will be reduced to a greater level. With the increase in technology, the need for systems is constantly increasing.

What is new today will be old tomorrow. Our system at present will help to overcome the drawbacks of the previous versions of the system as per mentioned in the literature survey. Smooth access and a more user-friendly UI will help the users to get a home-like environment.

A special feature has been inculcated into the system as a result of which the notifications will be received by the faculty as well as the students on their respective registered mobile numbers. The faculty who will be added to the portal as well as the students who will be allotted to them will all get an individual notification that they have been allotted under which group and to which project they have been entitled. No submission is permitted by the system after the deadline has been crossed. The upload report button will be automatically disabled by the system itself so that no reports can be uploaded once the deadline has been crossed.

Objectives

  • The system provides online processing of the reports.
  • Accurate results can be obtained.
  • The proposed system is used to reduce chaos and manual errors.
  • By viewing the reports the management can improve the institutional facilities.

Motivation

  • As society is developing and new trends are emerging in the education sector every coming day.
  • The ‘Online project report submission and evaluation system’ approach is all about managing project reports online for institutional and educational practices
  • Intelligence is used for the automatic generation of the certificates once the project report has been finalized or the deadline is crossed.
  • The motivation is to propose an intelligent system that can be implemented in any organization.

Use Case Diagram for the Proposed System:

Conclusion:

With the increase in technology, the need for systems is constantly increasing. What is new today will be old tomorrow. The proposed system at present will help to overcome the drawbacks of the previous versions of the system as per mentioned in the literature survey. Smooth access and a more user-friendly UI will help the users to get a home-like environment. The electronic marking of student project reports will save a lot of time, effort, and energy as well as expenses. It will also be more accurate and reliable for both the students and their instructions. In all, it will be a great help at the institutional level.

This application can be implemented in various situations. New features can be added as and when required. Reusability is possible as and when required in the proposed system. All modules are flexible. A very useful functionality from which the students could benefit would be if the system had a forum where any discussion could be opened that is related to the project. In the future, a useful feature that can be added is a platform to upload the student’s projects (like applications) to their instructors by the students.

Software Requirements

  • Front-end Design: JS, CSS, HTML
  • Back-end Coding: PHP, MySQL
  • Web Browser: Mozilla Firefox, Google Chrome, or later.
  • Operating System: Linux, Ubuntu, Windows 10.
  • Application Server: XAMPP Server

Download the complete Online Project Report Submission and Evaluation System for College students with HTML, CSS, JavaScript, PHP & MySQL Source code, and Full report documentation.