Online Food Ordering System Project Synopsis using PHP

About the Project:

The reason behind Online Food Ordering System is that there is a lot of information to be maintained and has to be kept in mind while running the business. For the reason we have provided the features present system is partially automated actually the existing system is laborious as one has to enter the same information at three different places.


The records were never used to be lots of difficulties in associating any particular transaction with the particular context.
If any information was found to be it was required to go through the different registers, document there would never exist anything like report generation. With the help of this system, people can easily order food. It can also ensure that. People don’t waste their precious time and use their time productively in other works.
This system proves to be more effective and reliable than other traditional systems. however one needs to take care of small parameters like server breakdown while this system is implemented.

Basic Structure:

Technology Used:

a) Hardware:

  • 1 TB storage
  • 8 GB RAM desktop

b) Software:

  • Notepad++ (for code)
  • Web browser
  • Operating System (Windows, Linux)

c) Language Used:

  • HTML
  • CSS
  • PHP

Choice of programming language:-

So many programming languages were put into consideration in the cause of designing this software. A lot of factors were also considered which include online database access, data transmission via networks, online database retrieval, online data capture, multi-user network access database security, etc.


Take Away Ordering. Takeaway ordering is a win-win solution for restaurant owners and customers.

  • Pre-Orders
  • Catering Orders
  • Scan & Order
  • Unique Webpage
  • Social Media Sharing
  • Search Engine Optimization
  • Combo Deals

Available Applications

  • Foodpanda
  • Zomato
  • Faasos
  • Deliveroo
  • Dunzo
  • Grubhub
  • Swiggy
  • User Interface


  • Makes the ordering process easier
  • Efficient customer ordering management
  • No-cost marketing.
  • Better customer data
  • The convenience of mobile ordering
  • Greater reach


  • Deliverymen put themselves in danger
  • Disguised increased expense
  • Juggling with your health
  • Unsuccessful payment resulting in delayed food delivery


Basically, the users targeted:

  • There will be a lesser requirement for staff at the back counter.
  • The system will help in the reduction of labor costs involved and also reduce the space required to set up a place like a cafeteria in restricted areas.
  • As it is an automated system is less probable to make any mistakes.
  • The customers can avoid the long queue a the counter, with a reasonable speed of execution and maximum throughput.


The simulation first starts with the customer entering his/her credentials(name, ID, and password). Once that has been verified the customer can place an order specifying the quantity of ordering food requirement. Now we get a window that displays the order number, customer ID, price, food name, and quantity. Once the customer finalizes his/her order they are redirected to the payment window where the total price is displayed and the customer can choose the payment option. The customer will get the confirmation message.

The above-mentioned simulation will flow with respect to the customer’s overview. Now if you are an admin you can select the normal login option and can enter the admin portal. Once you enter the admin portal you can add or reduce the food or update food or their price. Once the selected option is carried out to the end result that added item list will be displayed and if you have deleted the food the particular food will disappear.


The online food ordering system is developed so that customers can order food and avoid the hassles of waiting for the order taken by the waiter. Using the application, the end user registers online and reads the E-menu card to order food online. Once the customers select the required food item the chef will be able to see the results on the screen and start processing the food. This application nullifies the need for a waiter or reduces the workload of the waiter.
The advantage is that the in a crowded restaurant there will be chances that the waiters are overloaded with orders and are unable to meet the requirement of customers at a time. Therefore by using this application users can directly order their food online.

A Study on Excessive use of Social Media contribute to addictive behaviors or Mental health issues

Scope of the Study:

The study relates to the effect of negative aspects of social media’s contribution to human behavior especially the contribution towards addiction and mental health issues in the youth population. The study scope is confined to smartphone users as well as social networking sites and the users of this social media network.

Statement Problem:

This study was carried out based on the statistics of the agencies and the councils etc., There are even positive attributes of social media that can be used for promotion, knowledge sharing, etc., but the impact is majorly on the negative side of social media. When we compare the advantages and disadvantages of social media it is an equal proportionate of both but the challenge here is how to have control over social media access and how to utilize these social media for our benefit without spoiling our health etc.,

Data Analysis & Interpretation:

SWOT Analysis:


  • Social media can really help in many ways if we use them in a correct way like knowledge sharing for students, blood donation for the needy in health care, recruitment or job opportunities for unemployed youth, promotion the creative works or the content or the product, etc.,
  • Social networking sites of almost all types have come in mobile applications as all smartphone users can access them easily as the tariff of the telecom is also getting cheaper.


  • People often feel anxiety
  • Skipping the food timings and actively getting involved


  • The relationship building as they can search and meet many people
  • Classification of the subject of interests
  • They can keep in touch with relatives, friends, etc.,


  • Losing family and personal relationships
  • Causing Mental ill health
  • They are getting addicted to SNS where the first thing they do after waking up in the morning is check for the messages in SNS which is not at all a good sign and late sleep disorders etc.


Some facts out of our Primary research:

  • Almost 94% use Social networking sites, and the remaining 6% of youth don’t use them due to a lack of knowledge about them and include youth including rural areas.
  • Most of these 94% of people spend at least an hour to four hours on SNS which include Whatsapp.
  • 50% of youth do Online Gambling
  • 90% think that overuse may lead to addiction.
  • 60% feel that addiction affects mental behavior starting with anxiety.
  • The frequency of usage of SNS on average is 3 – 4 Hours/day by an addicted person.

Latest CSE Python Projects on ML & AI – 2022

These are the Latest CSE Python Projects on Machine Learning, Deep Learning, Artificial Intelligence, Big Data, Blockchain Technology, Cloud Computing, Data Mining, Networking, Network Security, and Cyber Security domains.

Download the Projects List Here – Python Projects on ML & AI – 2022

Python Projects List – 2022

These are the latest Python Machine Learning & Deep Learning projects for the year 2022.

  1. Characterizing And Predicting Early Reviewers For Effective Product Marketing On Ecommerce Websites
  2. Semi-Supervised Machine Learning Approach For DDoS Detection
  3. 5g-Smart Diabetes Toward Personalized Diabetes Diagnosis With Healthcare Big Data Clouds
  4. Credit Card Fraud Detection Using Random Forest & Cart Algorithm
  5. Driver Drowsiness Monitoring System Using Visual Behaviour And Machine Learning
  6. E-Assessment Using Image Processing In ∞Exams
  7. Automating E-Government Using Ai
  8. Eye Ball Cursor Movement Using OpenCV
  9. Filtering Instagram Hashtags Through Crowdtagging And The Hits Algorithm
  10. Converging Blockchain and Machine Learning for Healthcare
  11. Suspicious Activity Detection
  12. Use Of Artificial Neural Networks To Identify Fake profiles
  13. Video-Based Abnormal Driving Behaviourdetection Via Deep Learning Fusions
  14. Crop Yield Prediction And Efficient Use Of Fertilizers
  15. Fake Images Detection
  16. Opinion Mining For Social Networking Sites
  17. Image Classification Using Cnn (Convolution Neural Networks) Algorithm
  18. Cyber Threat Detection Based On Artificial Neural Networks Using Event Profiles
  19. Analysis Of Women’s Safety In Indian Cities Using Machine Learning On Tweets
  20. Construction Site Accident Analysis Using Text Mining And Natural Language Processing Techniques
  21. Performance Comparison Of SVM ,Random Forest, And Extreme Learning Machine For Intrusion Detection
  22. Accident Detection System
  23. A Data Mining-Based Model For Detection Of Fraudulent Behaviour In Water Consumption(Standalone)
  24. Detection Of Lung Cancer From Ct Image Using Svm Classification And Compare The Survival Rate Of Patients Using 3d Convolutional Neural Network(3d Cnn)On Lung Nodules Data Set
  25. Automatic Facial Expression Recognition Using Features Extraction Based On Spatial & Temporal Sequences Using Cnn & Rnn Algorithm
  26. Facial Expression Recognition And Their Temporal Segments From Face Profile Image Sequences Using Yolo Object Detection Algorithm
  27. Cartoon Of An Image
  28. Bird Species Identification Using Deep Learning
  29. A Deep Learning Facial Expression Recognition Based Scoring System For Restaurants
  30. Seer Cancer Incidence Using Machine Learning With Data Analysis
  31. Loan Prediction Dataset Using Machine Learning With Data Analysis
  32. User-Centric Machine Learning Framework For Cyber Security Operations Center
  33. Recolored Image Detection
  34. Robust Malware Detection For IoT Devices Using Deep Eigenspace Learning
  35. Modeling And Predicting Cyber Hacking Breaches
  36. Image-Based Appraisal Of Real Estate Properties
  37. Heart Disease Prediction
  38. Crop prediction using machine learning
  39. Face mask detection using artificial intelligence
  40. Facial attendance system using artificial intelligence
  41. Skin disease prediction using deep learning
  42. Fruit disease prediction using deep learning
  43. Malaria disease prediction using deep learning
  44. Phishing email detection using convolutional neural network
  45. Type 2 diabetes prediction using machine learning
  46. Suicidal tweets detection using machine learning
  47. web community questions and answering
  48. currency recognize system using artificial intelligence
  49. Fake news Detection using machine learning
  50. Detection of fake online reviews using semi-supervised and supervised learning
  51. mobile price prediction using machine learning
  52. Vigorous malware detection for the internet of things devices using machine learning
  53. Estimating the price of houses using machine learning
  54. Predicting the strength of the concrete pillars used in industrial infrastructure
  55. Passive Aggressive Classifier for Detection of Encrypted VPN
  56. speech emotion recognition using mlp algorithm
  57. face emotion recognition system using artificial intelligence
  58. Data Analysis by Web Scraping using Python
  59. A Decision Tree-based Recommendation System for Tourists
  60. A Machine Learning Model for Average fuel consumption in Heavy Vehicles
  61. Density-Based Smart Traffic Control System UsingCanny Edge Detection Algorithm for CongregatingTraffic Information
  62. Image Classification Using CNN (Convolution Neural Networks) Algorithm
  63. Prudent Fraud Detection in Internet Banking
  64. Twitter sentimental analysis
  65. Android malware detection using Machine learning techniques
  66. Missing Child Identification System using DeepLearning and Multiclass SVM
  67. Emotion-Based Music recommendation system
  68. Stress Detection in IT Professionals
  69. Cryptocurrency Price Analysis with Artificial Intelligence
  70. Object detection using artificial intelligence
  71. Using Deep Learning to Predict Plant Growth and Yield in Greenhouse Environments
  72. Human Activity Recognition
  73. Deep Learning Model for Detecting COVID-19 on Chest X-Ray Using Convolutional Neural Networks
  74. Encryption And Decryption Algorithm Based On Neural Network
  75. FAMD: A Fast Multi-feature Android Malware Detection Framework, Design, and Implementation
  76. Image Super-Resolution using Convolution Neural Networks and Auto-encoders
    Lip Reading using Neural Networks and Deep learning
  77. Image Segmentation with Mask R-CNN
  78. Open Pose: Real-time Multi-Person 2D Pose Estimation using Part Affinity Fields
  79. Tuning Malconv: Malware Detection With Not Just Raw Bytes
  80. A Hybrid Fuzzy Logic-based Deep Learning Approach for Fake Review Detection and Sentiment Classification of Amazon Food Reviews
  81. News Text Summarization Based on Multi-Feature and Fuzzy Logic
  82. An Android Malware Detection Approach Based on SIMGRU
  83. Access Control and Authorization in Smart Homes: A Survey
  84. Spam Detection for Youtube Comments
  85. Animal Classification using Facial Images with Score-Level Fusion
  86. An Enhanced Anomaly Detection in Web Traffic Using a Stack of Classifier Ensemble
  87. Automatic Corpus Creation and Annotation for Natural Language Processing of Telugu
  88. Blockchain for Secure EHRs Sharing of Mobile Cloud-Based E-Health Systems
  89. CaptionBot for Assistive Vision
  90. A joint multi-task CNN for cross-age face recognition
  91. Cyber security Tools for IS Auditing
  92. Cyber Threat Detection Based on Artificial Neural Networks Using Event Profiles
  93. A Deep Learning Approach for Effective Intrusion Detection in Wireless Networks using CNN
  94. Digital Image Encryption Algorithm Based on Elliptic Curve Public Cryptosystem
  95. Toward Universal, Word Sense Disambiguation Using Deep Neural Networks
  96. An Expert System for Insulin Dosage Prediction
  97. An Efficient Gait Recognition Method for Known and Unknown Covariate Conditions
  98. Self-Diagnosing Health Care Chatbot using Machine Learning
  99. Machine learning Models for diagnosis of the diabetic patient and prediction insulin dosage
  100. An Improved Approach to Movie Recommendation System
  101. Efficient Privacy-Preserving Machine Learning for Blockchain Network
  102. Sentiment Analysis to Classify Amazon Product Reviews Using Supervised Classification Algorithms
  103. A Deep Learning Approach for Effective Intrusion Detection in Wireless Networks using CNN
  104. SE-Enc: A Secure and Efficient Encoding Scheme Using Elliptic Curve Cryptography
  105. Secure Image Transmission Using Chaotic-Enhanced Elliptic Curve Cryptography(JAVA)
  106. Predicting Stock Market Trends Using Machine Learning and Deep Learning Algorithms Via Continuous and Binary Data a Comparative Analysis
  107. Multimedia summarization
  108. Quality Risk Analysis for Sustainable Smart Water Supply Using Data Perception
  109. Android Permission Control App(ANDROID)
  110. Increasing the Performance of Machine Learning-Based IDSs on an Imbalanced and Up-to-Date Dataset
  111. Fake Image Identification
  112. Non-Binary Image Classification using Convolution Neural Networks
  113. Robust Intelligent Malware Detection Using Deep Learning
  114. Construction site accident analysis using text mining and natural language processing techniques
  115. Cyber Threat Detection Based on Artificial Neural Networks Using Event Profiles
  116. Data Recovery
  117. Context-Based Image Processing Using Machine Learning Approaches
  118. A Knowledge-Based Recommendation System That Includes Sentiment Analysis and Deep Learning
  119. Robust Intelligent Malware Detection Using Deep Learning
  120. Rossman Stores Sales Prediction
  121. A Driving Decision Strategy (DDS) Based on Machine learning for an autonomous Vehicle
  122. A Machine Learning-Based Lightweight Intrusion Detection System for the Internet of Things
  123. A Model for prediction of consumer conduct using a machine learning algorithm
  124. An automatic garbage classification system based on deep learning
  125. Detection of fake online reviews using semi-supervised and supervised learning
  126. Forensic Scanner Identification Using Machine Learning
  127. Use of Artificial Neural Networks to Identify Fake Profiles
  128. Analysis and Prediction of Industrial Accidents Using Machine Learning
  129. Credit Card Fraud Detection Using Random Forest & Cart Algorithm
  130. Identification of covid-19 spreaders using multiplex networks approach
  131. Object Tracking Using Python from Video
  132. Software Defect Estimation Using Machine Learning Algorithms
  133. MamaBot: A System Based on ML and NLP for Supporting Women and Families during Pregnancy
  134. Deep Texture Features for Robust Face Spoofing Detection
  135. Prediction of loan eligibility of the customer
  136. Using Deep Learning to Predict Plant Growth and Yield in Greenhouse Environments
  137. A Malware Detection Method for Health Sensor Data Based on Machine Learning
  138. Blood Cell Types Classification Using CNN
  139. Feature extraction for classifying students based on their academic performance
  140. Hazard Identification and Detection using Machine Learning Approach
  141. Effective Heart Disease Prediction using Hybrid ML Algorithms
  142. Noise Reduction in Web Data A Learning Approach Based on Dynamic User Interests
  143. Online Book Recommendation System by using Collaborative filtering and Association Mining
  144. Sentiment Analysis Using Telugu SentiWordNet
  145. Soil Moisture Retrieval using Groundwater Dataset using Machine Learning
  146. A Time-Series prediction model using long-short-term memory networks for the prediction of Covid – 19 data
  147. Detection of Cyber Attacks in Network using Machine Learning Techniques
  148. Duplicate Question Detection with Deep Learning in Stack Overflow
  149. Machine Learning Techniques Applied To Detect Cyber Attacks On Web Applications
  150. Performance Analysis and Evaluation of Machine Learning Algorithms in Rainfall Prediction
  151. A Machine Learning Model for Average Fuel Consumption in Heavy Vehicles
  152. Accident Detection
  153. BAT Deep Learning Methods on Network Intrusion Detection Using NSL-KDD Dataset
  154. Online Book store
  155. Data Poison Detection Schemes for Distributed Machine Learning
  156. Detecting At-Risk Students With Early Interventions Using Machine Learning Techniques
  157. Detection of Possible Illicit Messages Using Natural Language Processing and
    Machine Learning-Based Approaches for Detecting COVID-19 using Clinical Text Data
  158. Personalized effective feedback to address students’ frustration in an intelligent tutoring system
  159. Research on Recognition Model of Crop Diseases and Insect Pests Based on Deep Learning in Harsh Environments
  160. Smart contract-based access control for health care data vehicle Pattern Recognition using Machine & Deep Learning to Predict Car Model
  161. Analysis of Women’s Safety in Indian Cities Using Machine Learning on Tweets
  162. Analyzing and estimating the IPL winner using machine learning
  163. Characterizing and predicting early reviewers for effective product marketing on eCommerce websites
  164. Crime Data Analysis Using Machine Learning Models
  165. Detection of fake online reviews using semi-supervised and supervised learning
  166. Detection of Malicious Code Variants Based on Deep Learning
  167. Detection and classification of fruit diseases using image processing & cloud computing
  168. Grape Leaf Disease Identification using Machine Learning Techniques
  169. Effective Heart Disease Prediction Using Hybrid Machine Learning Techniques
  170. Missing Child Identification System using Deep Learning and Multiclass SVM
  171. Music & Movie Recommendation
  172. Network Intrusion Detection using Supervised Machine Learning Technique with Feature Selection
  173. Prediction of Hepatitis Disease Using Machine Learning Technique
  174. Skin Disease Detection and Classification Using Deep Learning Algorithms
  175. Spammer Detection and Fake User Identification on Social Networks
  176. Using Deep Learning to Predict Plant Growth and Yield in Greenhouse Environments
  177. Using Data Mining Techniques to Predict Student Performance to Support Decision
  178. Making in University Admission Systems

Latest CSE Python Projects on ML & AI – 2022

  1. An automated system to limit COVID-19 using facial mask detection in a smart city network
  2. Analysis and Prediction of COVID-19 using Time Series Forecasting
  3. Analysis and prediction of occupational accidents
  4. Analysis of Women’s Safety in Indian Cities Using Twitter Data
  5. Artist Recommendation System using Collaborative Filtering
  6. A-Secure-Searchable-Encryption-Framework-for-Privacy-Critical-Cloud-Storage-Services
  7. Authorship Identification Using Text Mining
  8. Automated word prediction in Telugu language using a Statistical approach
  9. Biometric Steganography Using Mid Position Value Technique
  10. Classification of COVID-19 Using Chest X-ray
  11. Covid-19 future forecasting
  12. Covid19 Social Distance Monitoring System Using YOLO
  13. Credit Card Fraud Detection
  14. Detection and Classification of Fruit Diseases
  15. Diabetic Retinopathy Detection
  16. Early prediction of Diabetes Mellitus using intensive care data to improve clinical decisions
  17. E-Certificates Issue Services Using Blockchain
  18. Face to Emoji using OpenCV and haar cascade classifier
  19. Facial Emotion Recognition using ML Algorithms
  20. Fake Job Recruitment Detection
  21. Fusion Approach to Infrared and Visible Images
  22. High-value customers identification for an E-Commerce company
  23. Image Caption And Speech Generation Using LSTM and GTTS API
  24. Image Deblurring
  25. IoT based Attendance System using Blockchain
  26. Malicious Application Detection Using Machine Learning
  27. Money Laundering Detection Using Machine Learning Methods
  28. Music Genre Classification using ML algorithms
  29. Object Detection and Alert System for Visually Impaired People
  30. Object detection and localization
  31. Offline Signature Forgery Detection
  32. People count on Surveillance Video
  33. Politeness Transfer A Tag and Generate Approach
  34. Prediction Analysis Using Support Vector Machine In Cardiovascular Ailments
  35. Product Recommendation System Using ML Technique
  36. Rice Crop Disease Detection
  37. Sign Language Translator for Speech Impaired
  38. Skin Lesion Classification
  39. StellarStudent Social Web Application for Colleges
  40. Survival of Heart Failure Prediction Using Feature Scaling
  41. Text Summarization Method
  42. Text to Image Generator using GAN
  43. Vessel detection from spaceborne images
  44. HR Analysis of Employee Attrition & Performance
  45. Analysis of Forest Fire Area Prediction
  46. Prediction of Chronic Kidney Disease Using Machine Learning
  47. Predicting the Resale Price of a Car
  48. Prediction Of Diabetes Mellitus
  49. Prediction of Exact Niche using Bank Data
  50. Prediction of Insurance Claims using Health Analysis
  51. Sales Prophesy in Business using ML
  52. Prediction Of Taxi Fare Using Exploratory Analysis
  53. Prediction of customer churn in the telecom industry
  54. Estimation Of Wine Quality Using Chemical Analysis Data
  55. The Simpsons Character Recognition
  56. IMDB Movie Review Analysis Using Bidirectional LSTM
  57. Pattern Recognition of IRIS Flower based on Artificial Intelligence
  58. Recommendation System
  59. Zomato Review System
  60. Drug Review Prediction
  61. Web Traffic Prediction
  62. Building a Model for MNIST Dataset using Convolutional
  63. Toxic Comment Detection
  64. Sonar Prediction
  65. Accuracy analysis using Fashion MNIST dataset
  66. Survival Analysis Of Diabetes
  67. Wine Quality Prediction
  68. Bank Churn Model
  69. Survival Analysis (Human Breast Cancer Prediction)
  70. Black Friday Sales Data Analysis Prediction
  71. Bank Marketing
  72. Breast Cancer Classification
  73. Company Turnover Predictor
  74. Pneumonia Prediction
  75. Employee Attrition Prediction
  76. Intelligent Album Creator
  77. Predicting The Readmission To Hospitals For Diabetic Patients
  78. Communication Through Gesture
  79. Twitter Sentiment Analysis
  80. Smart Security System Using Image Recognition
  81. Text Generation
  82. Crop Health Assistant using Artificial intelligence
  83. Air Quality Prediction
  84. Suspicious activity Detector
  85. Watch Bot
  86. Pneumonia Detection Using CNN
  87. Sentiment analysis of Twitter comments
  88. Motor Health Prediction
  89. Real or fake face Detection
  90. predicting simpson Characteristics
  91. The Sorting Hat
  92. Analysis of Airline reviews using NLP
  93. Heart Disease Prediction
  94. Cereal Analysis
  95. Fertilizer Prediction
  96. Turbine power prediction
  97. Kidney Disease Analysis
  98. Analysis of Accidents in 2017
  99. A Machine Learning Approach to Predict Crime Rate Analysis
  100. Advertising Based on Usage
  101. Life Expectancy
  102. Abalone Age Prediction
  103. Exploring the Bitcoin Cryptocurrency
  104. Predicting High Potential Employees and Employees at Risk
  105. Insurance Purchase Prediction
  106. MNIST Classification using CNN
  107. Vehicle resale value Prediction
  108. University Admission Prediction
  109. Automatic Challan Generation
  110. Smart investment Prediction
  111. Smart Security using Artificial Intelligence
  112. Bike Buyer Prediction
  113. Best Crop Prediction
  114. Taxi Fare Prediction
  115. Resale Values of Predicting Cars
  116. Power Consumption Prediction
  117. Health Insurance Prediction
  118. Health Monitoring System
  119. Crime Rate Prediction
  120. Assert Failure Prediction
  121. Adult Census Income Prediction Using Random Forest
  122. Smart Predictors
  123. Nutrition Analysis Using Image Classification
  124. Liver Patient Analysis
  125. Flood Prediction
  126. Customer Recommendation System
  127. Crop Protection Using Deep Learning Techniques
  128. Communication Using Gestures
  129. Car Performance Prediction
  130. Avalanche Prediction
  131. 3D Printer Material Prediction
  132. Income Prediction Using Random Forest
  133. Term Deposit Subscription Prediction
  134. Advertisement popularity Prediction
  135. Google Review of Places Certificates
  136. Blood Cell Image Prediction

Stay Safe Women Security Android App Project Report

This system is for women’s safety and overcomes existing systems. This GPS system is the “Women’s Safety App”. It consists of a GPS device, an Android phone. The unit will provide status information such as latitude, the longitude of the user.

The proposed App is based on advanced sensors. Each time a user makes a phone call, an emergency signal will be generated automatically and then an information alert will be sent to the contacts that have been added to the emergency call.

low-battery alarm: when the user’s battery will be less than 10%, a low battery alert message will be sent to the emergency contacts.

In the new application, we provide a user-friendly connection where the user can send notification information in a simpler and more intelligent way. The user did not need to forget all the important contact numbers for their siblings or friends. The new system is also interactive for users and gives them the opportunity to get to know the police, the hospital, and their location.


• User-friend interface.
• Time construction.
• Easy integration and access.
• Internal communication. SMS communication and information will be sent in case of an emergency.


1. Scream Alarm: It works for both women and other users who need some kind of security alarm if they see if someone is following them or following them. At the same time, it consists of two other types of allergic reactions to radiation. It is the first move that will take some time and allows the user to get rid of the problem.

• Male voice scream
• Police siren.

The user can choose one of their options from the “Settings” program, as two other shooting devices have been added to this application because security and safety are everyone’s concerns today.

2. Fake Call Timer: Allow the fake call timer to allow the user to make false calls when needed. It helps the user to avoid any unwanted situation with an important call reference from anyone who needs it/he/she should hurry up and stop, depending on the user’s creativity. This feature also helps to save the user from social events
In order to make a false call, the user needs to select the icon “Fake Call” and after that, the user can specify from which name he/she wants a false call. Users can also set the timer as needed. Users can also select the default time from the “Settings” application in the application.
In a critical situation, the user is only forced to buy a very long false call button and automatically receive a false call in the settings according to the desired settings.

3. Where Are You: Your friend is at the party for the night. How can you control where that person is? That feature allows the user to find the latest location for friends and family if needed without the attention of the person being tracked.
When the first request is sent by the sender. The candidate is forced to select the “Where You Are” icon and then open a new dialog box with “Choose Friend”. The sender can select any friend and send the request to the recipient. One finally accepts this request and a message is sent to the recipient from the place where the user is currently receiving it.

4. Track Me: Our Track feature allows the user to see the dynamic location of the victim. The first user must send a Track Me application at the end of the receiver. The person agrees to the request and then his or her name is displayed on the friends you are running under the application. The user can select that friend from there and then it will be automatically redirected by Google Maps to the location where the user can see the exact location of the victim and also where he is going.

5. Friends List: This entry shows all contact numbers for family and friends that have been added by the user to the media. This can be done by selecting the contact icon in the lower right corner of the friend’s name.

6. Settings: The “Settings” function consists of the following features -:

• Emergency Services: This allows the Security Security application to send emergency and SMS messages to the right places from emergency contacts.
• Low Battery Alert: The low battery alarm feature allows the Stay Safe application to send emergency equipment and low battery batteries for emergency communication.
• Set Scream Sound: The user can select any beep sound as needed.
• Fake Call Timer(On Long press): The user can set the default time as required for false calls.

7. Emergency Distress Signal (SOS): An emergency signal is generated by the user in an emergency. In order to generate an emergency signal, the user has to shake his phone, then an emergency signal is displayed at the end of the user with a standard clock of 5 seconds. Finally, an emergency signal will be sent to the emergency contacts registered by the user. The application sends SMS and user information as well as the actual location of the user via a push message at the end of the receiver before the user sends the first emergency signal to activate the rescue functions from the application settings.

Data Flow Diagrams:

ata Flow Diagram Level 1
Data Flow Diagram Level 1
Data Flow Diagram Level 2
Data Flow Diagram Level 2

Output Results of the App:

When the user starts the application on their Android phone the first screen that saves the login desktop. First, it is necessary for the user to record the entry of information such as the name of the line and the contact number of the user.

After you enter the correct information to register, the authentication code (OTP) will be sent to the user in their contact address.

After logging in by the user, a pop-up window will open for the main program, which consists of the following functions:-

• Scream Function: The cookie function allows the user to avoid an unknown situation.
Users can also select the screaming style from the “Settings” icon as needed.

• Fake Call: Timer allows fake calls to be made by the user when they need to make false calls. It allows a quick call to be important to anyone who needs it/him/her quickly, to help the user get out of an uncertain situation. After a long time, the printout on the icon will also trigger a false call for the user.

Where are you? : Where you have the function to look at the static location of the user and the SMS will be sent at the end of the receiver with the actual static locations of the user.
After selecting the Where You icon, users need to select a friend from the friend’s address, and wherever they want you will be sent to the end of the receiver. The person accepts the request and the site will be sent to the end-user.

Track Me: Our Track feature allows the user to see the exact dynamic location of the victims. The first user must send a Track Me application at the end of the receiver. The person agrees to the request and then his or her name is displayed on the friends you are running under the application. The user can select that friend from there and then it will be automatically redirected by Google Maps to the location where the user can see the exact location of the victim and also where he is going.

Friends: The Friends list identifies the friends with whom the user is connected. The user can purchase a friend by selecting the “Add a friend” icon in the lower right corner. The user can add any contact number. directly or indirectly from “Contacts”.

Distress Signal (SOS): The emergency signal is generated by the user in an emergency. To create an emergency signal, the user needs to shake their phone, then there will be an emergency signal at the end of the user. The proper time to send this signal is 5 sec. A custom timeout is set so that the user can remove the signal from his / her end. Eventually, an emergency signal will be sent to the victim’s actual location for emergency contact. At the same time, a push message will be sent to the end of the user with all the details.

Download the attached Stay Safe Women Security Android App Project Report

Stock Market Analysis Python Project Report

Stock Market Analysis and prediction is a project for technical analysis, visualization, and estimation using Google Financial data. Seeing data from the market, especially some general and other software columns. Pandas used to take stock of the information, looked at different aspects of it, and finally looked at it in some way to assess the risk of a stock based on its recent performance history. Competing with the Monte Carlo method in anticipation of future prices.


Stock exchange analysis is only intended for the analysis of stock company data for various organizations. Using this method of data analysis, any organization can easily extract relevant information.


The main goal of my project is to analyze the data of all the institutions in which form we need.


Share financial data with quandl for the following companies:

  • Apple
  • Amazon
  • Microsoft
  • Google

Perform basic data analysis

  • Get last year’s data
  • Check Apple values
  • Indicate the final price
  • The stock market has seen a rate hike
  • Gather all the company data together for the final price

Make daily return analyzes and show the relationship between the different stocks

  • Percentage change plan for Apple product
  • Find a shared website for Apple and Google
  • Use PairPlot to show the relationship between everything

Perform risk analysis


We evaluated two basic measurements of the analysis and found no conclusive evidence about their estimated value.
These predictions are also very long-lasting and will see a year in the future. Suggestions on this scale are not the main project time. Instead, we will focus on predicting daily market trends. Because of these problems, we avoided basic analysis.

Performing risk analysis Results:

Download the attached  Stock Market Analysis python Project Report


Course Finder and Allocation Management Tool .Net Project

The Course Finder system is supported by students who enter high school. The purpose of the Course Finder software is first and foremost Internet users. This section discusses different courses and materials. The main purpose of this system is to search for secrets. An e-mail was opened at the university to participate in the new course.

They have many advantages such as school teaching, college photography, state-of-the-art exhibitions at the bar according to your classroom rain, course.

Generally, students will rely on candidates already studying at university to understand university details, but by using this software, they can easily understand the current status of university researchers. It is a tool for student purposes on the web. The student can search for university information, fees, academic records.

Purpose of the Project: –

The purpose of the “Course Finder and Allocation Management Tool” project is to facilitate the search for online universities by means of a package called the Course Study System.

The system has a registration module for students to forget their passwords, and at the same time, a new user enters the place where new students want to register and also an alternative to a forgotten password. A successful student can participate in a college search.

As modern organizations grow increasingly complex and computing works according to leaders, it becomes important for the coordination of individuals, groups, and computers in the modern organization.

Through this college search, students can find universities that can be adapted to their subject type and at the same time reduce search time.

Big cities where life is within a few minutes have to announce things. In this way, this online archived information helps students complete their search in a limited time.

Furthermore, students can go directly to the university directly from this site. At the same time, they can make the university of their choice.

Existing system

The current system is an intervention where students have to search for papers on campus and go to college to obtain university information.

The following is the usability of the current system.

  • It is difficult to find out about a college degree on a relevant course that is being sought by a student who is new to college.
  • More manual hours are required and reports are required.
  • It is easy to know important information about the environment and the found objects.
  • The signs of a college renovation are hard to maintain. 

The default system

Course attendees and course management systems are an application that delivers more than the accreditation hours to enable universities to successfully understand the relevant course. These applications collect data in a centralized way that is accessible to all users at the same time. It is very easy to manage historical data in a database. There is no specific training for users to use the application. They can easily use a device that reduces interference to normal elements and thus improves performance.

The purpose of the system

Course attendance systems are assisted by middle school students and higher education students who are new to the school. The purpose of the search engine software is first and foremost Internet users. The purpose of the course and attendance management is to give users of the information system the best information when it comes to looking for universities for the best results.

Download the attached Course Finder and Allocation Management Tool .Net Project full source code, project report, PPT

Course Finder And Allocation Management Tool .Net Project

Veterinary Website Management System Java Project


Online applications are playing an important role in our day to day life from online shopping to doctor booking which is saving time and helping ineffective management of resources. As of now, there are no applications for online doctor appointments for veterinary systems. In this project java based web application is designed, which as features for booking an appointment by checking the availability of a doctor and then select specific doctor specialization and a form is shown to the user who will fill the form based on animal condition and symptoms and do online payment. Books are conformed by admin and updates are sent to the doctor regarding bookings along with details the user has filled. The project is designed with three modules admin, user, and doctor. Entire data is managed in a centralized database using the MySQL database.

Existing system:

At present, there are many websites that provide online veterinary services but they have only details of doctors and type of treatment. There are no online services like booking appointments, sending patient details ..etc.


  • Websites which provide veterinary services are limited to specific service only
  • Users need to wait for a long time for finding a doctor and getting treatment

Proposed system:

In proposed system website is developed with advanced features for Veterinary purpose which has features of online appointment booking, checking the availability of doctors with timings, Advance patient information updating and online payment.


  • Users can save time by processing through this website
  • Easy to find if a doctor is available based on our required treatment.



Admin will look after the application who will check users and doctors and confirm appointments and send emails to the user. Admin updated user booking status to the doctor online.


The user should register with the application he is basically a person who wants to get his pet to be treated. The user will select the type of doctor and treatment and fill form related to a problem and check the availability of doctors and book appointments and confirm the booking.


The doctor will register with the application based on his specialization and what type of service he provides. A doctor can check booking uses details and check the form which use has filled to know about patient status.


Hardware Requirements

Processor : Intel 2.0 Ghz Or Above
Hard Disk : 200 Gb
Ram : 2 gb Ram.

Software Requirements

Operating System: Windows XP With Sp2.
Language (Front End) Java (Jdk1.5/1.6)
Server: Apache Tomcat 5.5/6.0
Web Technology: Html, Javascript, CSS.
Database (Back End): MySQL
Architecture: 3-Tier Architecture

Smart Colony Automation ECE Project


The development of a country depends on the City and village’s development. As part of the smart colony  concept, we need a system that helps in development of city  in the areas like which have authorized entry using RFID system at entry gate to colony gate, and the system will have auto street lights system to switch on the lights in night and OFF them at day time and automatic  garden watering system based on soil moisture monitoring,  garbage bin which has automatic door system to prevent the fly’s around it, and  home automation system which can control the lights and fans from our android application in mobile.

The entire Smart Colony Automation system is controlled with Atmega 328 microcontroller which has connected RFID , moisture sensor , LDR sensor, Wi-Fi module which will control the home appliance over android application, the entire system works on 12V DC power supply.


Smart Colony Automation ECE Project


Hardware Components used

  • Arduino Uno board
  • RFID Reader
  • Soil moisture sensor
  • LDR sensor
  • Lights
  • Servo motor
  • Water pump
  • Relay


  • Gated community colony
  • Hospitals
  • Colony’s

Travel and Events Portal Website Development

Project Statement:

Need to develop a travel and events portal website to provide users different tours and travel packages depending upon their interests.

It will allow users to register and search through various tours which will be displayed on the website. Tours related info will be managed by admin panel in the back end and will be dynamic.

Search will also be location-based and package based. Admin panel will be provided to manage locations, regions, packages, and tours as per search are done by the user.

Once a user searches through the related info he or she will request a quote and email will be sent. Either user or travel admin will follow up.

The request form will capture all important info like Email, name, number, etc. If hotels are also being planned then we will also include a related field in the request form. 

Basically, we will manage it basing:

Places to enjoy
Weekend Plans
Recommended Tours 

It will basically have two logins:

Admin and User.

Admin will manage all back end data. Will update tours, packages, destinations, locations, weekends plans, etc.

These all will be seen by the user in the front end. So the project will be basically divided into Front end website and back end admin panel for managing data.

Website Structure:

1. Application & General Site:

Welcome screen with the option to register/sign in
Terms & Conditions
Privacy Policy

Company Profile
About Us

2. Admin pages:
Admin panel login and forgot password option

Manage Enquiry Requests 

Manage Blogs
Manage tours
Manage packages
Manage Destinations
Manage weekend plans
Manage Recommended tours
Manage Customers 
Manage Bookings 

3. Quality Control:

At the end of the development cycle, you will have a properly functioning and quality assured site.

By ensuring implementation of the following points we maintain quality in the products we deliver.

  • W3C validated semantic HTML code
  • Well commented and indented PHP code
  • Proper escaping of user entered data to prevent XSS, CSRF and other security issues
  • Optimized database tables
  • Minified CSS, JS and optimized images for faster loading
  • Implementation of meta tags, descriptions, open graph tags for help in SEO

4. Search Engine Optimization:

All the below points will be implemented for making the site on page SEO ready:

Search Engine Friendly Code i.e. H1-H6 and Meta Tags, ALT Tag for images, etc.

Page Title and Page description

sitemap page


DIV Based Code (Table Less)

Friendly URLs, such as, etc.

Keywords, Meta Description Placement

Custom Design 404 Error Page

Organized and Commented Code

Faster website loading and good speed score


Task / Modules Page


Initial Planning and Design


Primary Database Design


Responsive HTML Design of All Pages


Front End Section


Landing activity for the welcome screen along with login/register option
Terms & Conditions
Privacy Policy

Company Profile
About Us

Search Criteria
Packages selections
Destination selections
Places to enjoy selections
Weekend Plans selections
Recommended Tours selections 


Admin Panel 


User management
Tours, Destinations, Places to Enjoy, Weekend tours management

Manage categories and subcategories

Manage bookings 

Manage blogs and Enquiry requests  


Testing & Bug Fixing 


Web service, DB Design, Architecture, and deployment 

Related Projects on Travel & Tourism below:

Football Prediction Android App Project

Project Statement:

To design and develop a Football Prediction Android mobile app for Android / IOS platforms which will provide betting tips for football matches.

The option will be there to buy credits and look out for suggested Gold Boom tips and VIP tips. Free daily tips will also be provided to any player who has installed the app. Bet tips will be loaded from back end Admin panel.

The option will be provided for checking the match analysis and understand the tips, and then form a strategy.  It will load games that are about to start or already running and we can also sort it as per preferences. And provide tips for related games.

User Types:

  • Admin
  • Customer

The app will have the following features:

Home Grid
App Icon design
Boom Gold Tips
Free Daily Tips
Top Match Analysis
Super Bonus Tips
Rate Us
Betting Strategy
About Us
Privacy Policy
Contact us
Customer Login / Account
Credits payment gateway integration
Admin Panel

Module Details:


Task / Modules Page


Initial Planning and Design


Primary Database Design


Admin Panel
Back end designs for below modules
Tips → Boom Gold tips, Free daily tips, Super Bonus Tips all these three will be managed dynamically from admin panel
Customer mgmt →  will handle customer registrations who will pay for getting the Gold and Bonus tips.
Payment gateway and credits
Transactions → will be for managing the transactions done by the customer for paying and getting credits
Credits to manage credits in a customer account

Match Analysis mgmt
Membership plans


Rate Us
Betting Strategy
About Us
Privacy Policy
Contact us
Login / Logout

Match Analysis


Web Services & DB architecture management with deployment 

Choice of Technology:

Dot net MVC with ASP and SQL Server as server-side programming language and database or Php side programming and MySQL 


Android: Java  (Android v 6.1 and higher)
iOS: Swift 6.0.1 (Native and supporting iOS 11 and above)

We need to purchase API related to all football leagues that are happening, which we will integrate.