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Career Analysis System Project Idea

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Career Analysis system

Objective

A career analysis system is a software developed which enable students to know about particular college and all its details. It enables students to search for college according to their rank.It helps them to search for college and its location. It is developed in Java and Mysl is used as a database. The main objective is to reduce the time and effort that occur in manual systems. The students can also get the details of the courses in the particular colleges and can enroll for them online. So every information is available to students at just one click. In an earlier Career Analysis system, the students cannot access the information online as there was no such software so they have to go the college and then get the details. So the earlier system lea to errors and this system allows everything to get simplified.

Career Analysis system

Existing system

In the earlier Career Analysis system the students the students have to go to the colleges physically and then get information. They cannot sit at their homes and get the information. So it was a tedious and time-consuming process. They can’t get the proper details and cannot search suitable college according to their rank. He completes information regarding colleges and courses could not be accessed using this earlier system so there was the need for an automated system to be developed which could rectify all the problems.

Proposed system

In the new Career Analysis system, the students can get all the information regarding colleges and the courses at just one click. They can access this information without having to go anywhere and this reduced physical effort and time. Now they can easily know which college is according to their rank through this one system developed. This system provides a good and accurate way to search for colleges. So this new system is automated and manages all the details about the student’s colleges and ranks. It generates the accurate result for students and helps them in selecting proper college according to their rank.

Career Analysis system Modules

  • Admin

In this module, the administrator is given the privilege and can add or edit the information regarding different colleges and the courses available. He or she can dd courses details and can also add information about the students. It can check the rank of students and accordingly generate the result.

  • User

In this module, the students or users have to fill the registration form and then get the login credentials. After this, they can log in and then enter their rank after which they can get suitable college details according to their rank. They a view correct courses according to their rank.

Software Requirements

  • JVM

Hardware Requirements

  • Hard Disk – 2 GB.
  • RAM required – 1 GB (minimum)
  • Processor – Dual Core or Above.

Technology Used

  • Java

Other Projects to Try:

  1. Student Performance Analysis Prediction Data Analytics
  2. Online Voting System project Idea
  3. College Management System project in Java
  4. College Selector Android Project
  5. Online Career Guidance System Project

Student Performance Analysis Prediction Data Analytics

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Student Performance Analysis Prediction Using Data Analytics

 

Objective

To analyse the students performance based on their academic data using data mining techniques.

Project Overview

In this technological world, data storage and analysis are a big challenge. The ultimate goal of this project is aimed at better analysis with improved accuracy of data. Its requirement is so simple, that needs only the data sources, which is then processed to compute the results in the form of the report through which we can easily analyze the performance of the student in an efficient way.

It also focuses on analyzing data which helps in categorizing and thereby motivating the students in their academics as well as flavoring the staffs to improvise the students to the next level.Finally, the students are grouped as a good performer, average performer, a bad performer based on their result analyzed from their academic data.

Proposed System

Career building is the most cherished part of every college student. For a graduate, it is necessary to have immense knowledge in their domain to get placed in a reputed company. This system applies data mining techniques to the academic dataset. The Academic data includes the Internal marks and the Assignment marks. The final semester marks are predicted from the internal marks each student.

The proposed system architecture is shown in the figure.

Student Performance Analysis

Figure: Proposed System Architecture

Module 1:Data Selection

The required data is collected from the academic institutions. The data should consist of student details with internal marks and assignment marks.

Module 2: Data Preparation

Data preparation is an important step in the data mining process. Data pre-processing, includes cleaning, normalization, transformation, feature extraction, and selection, etc.

Module 3: Implementation of Data Mining Techniques

The required data mining algorithm is implemented using Java in Netbeans. These algorithms are applied to the data set to analyze the student academic performance and the accuracy are calculated.

Module 4: Predicting End Semester Grades

Prediction is a data mining function that discovers the future characteristics of the data. The relationships between co-occurring items are expressed as association rules. Predictive techniques rules are used to predict the final grades of the students using cumulative test mark and assignment marks.

Module 5: Grouping Students Using Simple Cluster

The students are grouped based on their end semester grades. The good performing students are grouped in one group, the average performing students are grouped as a group and finally, poor performing students are grouped in a group.

Module 6: Data Visualization

The association between theextracted results is found, to give the accurate analysis of results. These analyzed results are then displayed in the pictorial format of bar charts for the easy analysis and better understanding of the user.

Software Requirements

  • Weka 3.8
  • Netbeans
  • Visual Studio
  • SQL Server 2008

Hardware Requirements

  • Hard Disk – 1 TB or Above
  • RAM required – 4 GB or Above
  • Processor – Core i3 or Above

Other Projects to Try:

  1. Diabetes Prediction Using Data Mining Project
  2. Higher Education Access Prediction using Data Mining
  3. Academic Performance Of Students With Fuzzy Logic
  4. Sentiment Analysis on E-Commerce Sites | Data Analytics
  5. Cricket Matches Prediction using Data Science

Tableau in Institutions for Better Insight | Tableau Projects

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Tableau in Institutions for Better Insight

 

Objective

To implement the business intelligence in institutions using Tableau for the better insight using Tableau Projects. This will help the institutions to enhance their process.

Project Overview

The mark and attendance of the student are used for the analysis, extracting the relationship among attributes in several constraints and possibilities. Attendance and mark analysis system are built with facilitating easy analysis by highlighting the hidden association in the data set. The more stable working environment needs to be developed.

Existing System

Most of the institutions use some type of software to maintain their data in digital format. The main focus of the software is to store, update and retrieve the required data easily. The existing system mainly concentrates on the data storage in the single repository rather the analysis of the data, is much difficult to process. This existing mark and attendance reporting system satisfy only the basic needs of the end users. Weekly, monthly and daily reports can be extracted from the existing system but extracting complex community reports is impossible in the existing system. This project adds over that and focuses more on the data analytics.

Problem Definition

This system satisfies only the basic requirements such as the monthly, weekly and daily report of attendance record of the students along with the course description.

Proposed System

Proposed System of this project can be stated in terms of different categories as visualizing, comparing and analyzing. In this system, requirements such as analysis and relationship of the complex reports are achieved using the following,

  • Basic Statistics and Business Intelligence
  • Data Analytics

This also includes the extraction of association between various attributes and the hidden relationship between them. Finally, data analytics is used to filter those required data from the entire dataset.

Module 1 : Requirement Analysis and Data Pre-Processing:

In this module, the requirements are collected from faculties and students. Some of the requirements include:

  • Finding the students who secured top and bottom 5 marks.
  • Comparative analysis among students.
  • Finding the Impact on marks due to attendance.
  • For analysis, student internal marks along with their attendance and assignment marks will be collected from the institutions.

Module 2: Statistics

In this module, the marks and attendance of students are analyzed. From this above statistics, we get the average details of the given dataset, like maximum minimum internal grade and highest lowest percentage. With the above statistics, we are going to analyze the marks of the students in different constraints using various tools.

Module 3: Business Intelligence

The concept of business intelligence is included in the project by using Tableau tool. The tool helps in finding the relational flow graph for the student course wise, exam wise top5 and bottom 5. It is also helpful in finding attendance and mark based on different categories.

Module 4-Data Mining

The concept of data mining is included in the project by using the Rapid Miner and R tool. The algorithm of data mining is imported from the rapid miner and working part of the algorithm is implemented as built-in and the required graph is displayed.

Tableau project in Institutions for Better Insight

Apriori Algorithm

The Apriorialgorithm is implemented in Rapid Miner as it includes the property of the association.

  • Rules (Top 5 – Support)
    • Top 5 support is used to segregate the top 5 records from the entire dataset, which helps in easy retrieval and analysis of the statistical data.
  • Rules (Bottom 5 – Support)
    • Bottom 5 support is used to segregate the bottom 5 records from the entire dataset, which helps in easy retrieval and analysis of the statistical data.

Software Requirements

  • MySQL Server
  • Tableau
  • R
  • RapidMiner

Hardware Requirements

  • Hard Disk – 1 TB or Above
  • RAM required – 8 GB or Above
  • Processor – Core i3 or Above

Other Projects to Try:

  1. Sentiment Analysis on E-Commerce Sites | Data Analytics
  2. Student Performance Analysis Prediction Data Analytics
  3. Store Management System Project
  4. Trending YouTube Video Statistics Deep Learning
  5. Big Data Hadoop Projects Ideas

Trending YouTube Video Statistics Deep Learning

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Trending YouTube Video Statistics

 

Objective

To extract the useful information from the trending YouTube video using the statistics modelling techniques.

Trending YouTube Video Statistics

Project Overview

YouTube is the well-known video sharing platform in the world. The website maintains the mostly viewed topmost videos and trending videos. Most of the trending videos are music videos, comedy, celebrity performances, sports incidents and latest viral videos. To identify the trending videos, it uses the factors like,

  • Number of Views
  • Shares
  • Comments
  • Likes

System Design

Proposed YouTube Video Statistics System of this project concentrates on the categories such as visualizing, comparing and analyzing. In this system, the required outcome is obtained using the following,

  • Basic Statistics
  • Business Intelligence
  • Data Analytics
  • Machine Learning
  • Predictive Analytics

List of modules are

  • Data set collection
  • Data preparation
  • Data analytics
  • Data visualization

Module 1 : Data Set Collection

The required data set was collected from YouTube using the YouTube API.The collected data set consists of daily trending videos of last few years. The gathered data includes the regions such as USA, Canada, France and Great Britain. The data includes the factor like channel title, video title, time published, number of tags, number of views, number of likes, number of dislikes, description of the video and comment count.

List of Attributes

The YouTube Video Statistics data set consist of two parts. One is a comment and another one is video statistics. Here video_id is used as a unique field.

The attributes of the video file,

  • video_id
  • video_title
  • date
  • channel_title
  • category_id
  • views
  • likes
  • dislikes
  • thumbnail_link
  • tags

The attributes of the comments file

  • video_id
  • comment_text
  • likes
  • replies

Module 2: Data Preparation

Data preparation is one of the important step and time-consuming process in the data mining process. Data pre-processing, includes cleaning, transformation, and attribute selection, etc.

Module 3: Data Analytics

From the collected data set following things can be done for the better understanding and better decision making in the future.

  • Categorising the videos
    • Comments play a huge factor here.
  • Different forms of sentiment analysis
    • Supervised learning algorithms used here.
  • Auto-generation of comments
    • Machine learning algorithms play a huge role here.
  • Predicting the popularity of the video in advance
    • Predictive analytics used here.

Module 4 : Data Visualization

The hidden information between the extracted results is found. These patterns are then displayed in the pictorial format of bar charts for the easy analysis and better understanding. The resultant chart contains relative comparisons between two features combination of the data set. The analyzed result is obtained a relationship between all items as visualized form.

More attributes can be added to the data set while collecting data. This will help to gain much better understanding. Deeper analyzes of the project give furthermore efficient and effective analyzes in the project.

Software Requirements

  • Tableau
  • R

Hardware Requirements

  • Hard Disk – 1 TB or Above
  • RAM required – 8 GB or Above
  • Processor – Core i3 or Above

Download Abstract

Other Projects to Try:

  1. Video Rental Management System Project
  2. Tableau in Institutions for Better Insight | Tableau Projects
  3. Flight History Analysis Using Hadoop Project
  4. Big Data Hadoop Projects Ideas
  5. Learning Made Easy mini project

Smart Voting System Project IOT Project

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Smart Voting System Project

 

Objective

  • To develop a smart voting system based on Internet of Things (IoT) using Rasperrybito efficiently manage the voting process.

Project Overview

A enormous amount of money is involved in conducting an election. But, nowadays it will be very difficult to conduct good and fair election in all the places. Some forces try to disrupt the elections using some technologies. So it is necessary to secure the voting system with latest technologies.The two level of authentication need to be implemented to improve the security mechanism in system. If anyone try to caste fake vote, he/she need to be identified priorly and steps need to be taken to have fair election.

Electronic voting system refer’s to voting using electronic mediums and smart voting system refers voting system using IoT. In recent times, we are facing many problems like travelling long distance, spending huge money to travel. From the government perspectives, they need to deploy huge man power, infrastructure and machines. Both point of view, its complex process. This decade utilized the advantages of new technology in many fields. This project concentrates on improving the voting system with new IoT and other latest features.

Proposed System

The proposed Smart Voting System IoT based smart voting system concentrates on automating the voting process with good accuracy and efficiency.Internet of things is made up of many devices like simple sensors, smart phones and wearable sensors and etc., For the purpose of developing good an IOT infrastructure, we need to configure the hardware with software and control the devices over the internet. In order to help this process, raspberry pi can be used. This raspberry pi platform is used for creating new environment internet of things infrastructure. The proposed system architecture is shown in following figure.

  • Before starting the process, it needs some settings. Server with client PC’s needs to be set carefully over the large area. This connection might be wireless. Then actual voting can taken place. Voting machine is connected to laptops.

Smart Voting System

Working Principle

  • The process is started with voter submit the unique identification number with fingerprint on the authorization unit. This detail is sent to the server.
  • Data will be verified. If the data found to be correct, then authorized user information will be displayed, else he/she will not be permitted to vote.
  • Once verification is done, then voter can go to the voting machine and he/she can register the vote. Voter will get the receipt for the voting.

Smart Voting System Advantages

  • It can be used for long distance voting.
  • It saves time, money, otherextra efforts to reach the voting place.
  • Less human effort is required.
  • Counting of votes could be done immediately after voting completed.
  • Easy installation and less effort is required.

Future Scope

  • Aadhar card can be used in future to get more details.in
  • Audio signal can be used in future to get the best results.

Components / Software /Hardware’s Required

  • Web Server
  • MySQL Database
  • Wifi Modem
  • Rasperry Pi

Download Abstract

Download Project

Other Projects to Try:

  1. Online Voting System project Idea
  2. Online e-Voting Machine System Project
  3. Voting System Project using Android
  4. Smart Toll Booth Management System IOT Project
  5. Smart Gas Pipe Leakage Detector System IOT Project

Vehicle Parking System IOT Project

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Vehicle Parking System IOT Project

 

Objective

To develop a vehicle parking system based on Internet of Things (IoT) using Raspberry efficiently parking the vehicles.

Project Overview

Nowadays, Internet of things is the latest and evolving hot technology. It can be used to connect surrounding things to a network system and communicating and sharing the things with each other. It reduces the human intervention and automating the process. Nearly more than 50% of world’s population lives in cities. In recent years, the usage of vehicle increases and growing in rapid rate. During the parking of the vehicle, people find difficulties. It takes time and increases fuel usage. It creates congestion and traffic. This happens due to the lack of good vehicle parking system.

Population of the world increasing rapidly. People from rural areas switching to cities for employment and other reasons. Number of vehicle usage is growing at enormous speed. So, it causes issues in parking in many ways. It leads to traffic, accident and so on. If you visit the public places such as hotels, multiplex, shopping malls, you will be frustrated with parking issues. One of the research study says that a driver takes nearly minimum of 5 minutes on an average to park the vehicle. So it is necessary to create a good parking facility in the cities to avoid frustrations, traffics and accidents.

Existing System

Existing Vehicle Parking System provides Bluetooth device and finds a slot in the parking place. The information about the parking area, only available within the Bluetooth range. So new system which covers large distance need to be developed to improve the parking facility.

Proposed System

The proposed Vehicle Parking System architecture is shown in following figure.

The proposed Vehicle Parking System IoT based vehicle parking system focuses on automating the process with good efficiency. This parking system provided solution to the parking issues and also reduces human work and manual work. This system can be implemented in cities, airports, large shops, multiplexes and institutions.

Vehicle Parking System

Working Principle

  • User needs to register the vehicle details through mobile app. This information will be stored in the server. It can be used to track the user, in case of any policy breaks. Once the entire registration is completed, user can check the free parking area and he/she can use those facilities provided by the smart vehicle parking system.
  • Here IR sensors are used detect slot to park the vehicle. RFID tag is used for vehicle identification. .

Vehicle Parking System Advantages

  • It reduces the waiting time to park the vehicles.
  • It maximize the venue availability to the vehicle users.
  • Less human effort is required.

Future Work

  • This system work can be further extended to advance booking ofparkingsplaces over a period of time.
  • The android mobile application can be further extended to other operating systems such as iOS, Windows ,etc.

Components / Software /Hardware’s Required

  • Web Server
  • MySQL Database
  • Wifi Modem
  • Raspberry Pi
  • IR Sensor
  • Android

Download Abstract

Download Project

Other Projects to Try:

  1. Streetlight Monitoring System IOT Project
  2. Smart Toll Booth Management System IOT Project
  3. Traffic Signal Monitoring & Controlling System IOT Project
  4. Smart Gas Pipe Leakage Detector System IOT Project
  5. Smart Voting System Project IOT Project