When it comes to careers in software development, it is a must for aspiring developers to build their own projects. Working on real-world projects is the best way to sharpen your skills and transfigure your theoretical knowledge into practical experience. In this article, we will be exploring some of the computer science latest project ideas to start with.
Facial Mask Detection
The Covid-19 pandemic has made a lot of changes to our lifestyle and wearing a facial mask is one of them. The use of facial masks is really important in preventing the spread of the virus and several governments and organizations across the world are trying to ensure the usage of facial masks.
Using our proposed system, we aim to detect people devoid of masks and give them a proper warning. This system can be deployed along with CCTV placed in malls, theatres, institutions, offices, etc. An automated system like this will be pretty useful for many organizations. If you’re interested in doing this project, check out this IEEE Document for more details.
Cifar-10 Image Classification
Images can be classified pretty accurately using deep learning algorithms. In this project, we will be using the popular dataset called Cifar-10 and the keras library of Python. I have a soft corner for this project and wanted to include it in this list because this is the project that I did when I was in the final year of my computer science course.
The cifar-10 dataset contains 10 categories of images, viz., birds, cats, deers, dogs, frogs, horses, airplanes, automobiles, ships, and trucks. We can create a CNN model using keras and provide the dataset for training. You don’t need to manually download all the images in this dataset. Instead, you can import the entire dataset from the keras.datasets module.
After I did this project, I documented all the steps that I’ve done including the code and images, and created a blog post so that others can use it to create their own projects. Check out this article if you’re interested in this project.
Traffic Prediction Tool For Intelligent Transport
The goal of this project is to create an automated system that predicts and provides accurate and timely information regarding accidents, traffic signals, road repairing, traffic blocks, rallies, or any other important traffic information that can be helpful for people.
To analyze the big data for transportation systems, here we make use of machine learning, genetic, soft computing, and deep learning algorithms. These algorithms can be really useful in predicting accurate traffic flow information with less complexity. Image processing algorithms can help in traffic signal recognition.
For the accomplishment of this project, we need Android Studio, Java, Garmin, PHP, XML, Python, and the sklearn library. A link to the IEEE research paper describing this project is given here. Check it out for more details.
Predicting Crime Rates
Day by day, the number of crimes and criminals is increasing everywhere in our society. We can see that certain crimes repetitively occur in periodic time intervals. Our project is based on these types of crimes. Using the data of the crimes that occurred in an area in the past, we can predict future crimes and try to prevent them from happening.
Since crime prediction and identification of criminals are some of the challenging jobs for the authorities, we can apply machine learning to predict the type of crime which will occur in a particular area. Using the Linear regression algorithm and Python, we can predict the percentage of crimes that can occur in the future with the help of previous data and information.
The date is given as input to the algorithm and the output is the percentage of the crime rate in that particular year. The officials can take charge and try to reduce the crime rate based on this information. If you’re interested in doing this project, check out this research document for more information.
Smart Mirror Based on Raspberry Pi
Since 3D mirrors and hair salon mirrors are expensive, why not try developing an intelligent mirror made of Raspberry Pi! Here, Raspberry Pi is used as the host controller, and STM32F030C8T6 microcontroller is used as the core control chip.
With the designed intelligent mirror, the user can ask questions to the mirror and receive information regarding weather, news, time, etc. Imagine how cool it will be to read daily news while brushing your teeth in front of the mirror. For detailed information regarding the design of this project, check out this IEEE paper.
YouTube Channel Success Prediction
Being a YouTuber has been one of the latest career options and many people are considering it as a full-time profession. The profit from YouTube is often directly proportional to the popularity of the person and his/her videos. Most of the newbie YouTubers do have a concern about how many people will watch their videos and how often will their videos get watched. If a YouTuber can predict the popularity of his videos, he can make changes and modifications accordingly.
In this project, the properties of the YouTube videos such as their title, time gap, category, tags, description, duration, etc., are selected as the inputs to the machine learning model to predict the performances of the videos.
Several multi-classification algorithms such as stochastic gradient descent, multilayer perceptron neutron network, decision trees, random forest, gradient boosting methods, etc., are used to output the predicted category of the video such as non-popular, overwhelming praises, overwhelming bad views, neutral videos, etc. Go through this IEEE paper to get more implementation details of this project.
Spy Project Using Keylogger
This is a pretty interesting project idea if you want to spy on someone else’s computer. Well, you can use this project for good reasons and bad reasons, and I hope you’ll only use it for good reasons. The basic idea behind this project is to develop a program with the help of a keylogger on the computer system of the victim. This program will be able to track all the activities done by that person on his/her computer.
The user of the system cannot identify the presence of this keylogger. Parents can use this to keep an eye on the computer activities of their kids and in companies, employees and their activities can also be tracked using this program. We can also remote control their system using this program.
Plant Disease Detection using Deep Learning
Due to the ever-increasing population rate, the need for food production also increases considerably. This makes it necessary to fastly identify and cure the rising number of plant diseases too. Laboratory researches and the service of expert people are both difficult in rural areas. So that makes us think about the possibility of using smartphones for this purpose.
In this project, we use a deep learning approach to identify diseases. We can train the deep learning model using the PlantVillage dataset. The classical machine learning algorithms including SVM, k-NN, FCNN, and the deep learning algorithm CNN, can be used here. For more details about this project, check out this IEEE paper.
Counting People in Dense Crowd Images
People counting is a challenging problem in highly dense crowds due to severe disturbances and unbalanced camera positions. So here, we are trying to implement an algorithm that enables us to count the number of people in a thick crowd using sparse head detections.
In a dense crowd, the head will be the prominently visible part. So here we try to make use of a head detector that can evaluate the varying head size with which we can count the number of different heads. Download this IEEE paper to know more about this interesting project topic.
Computer Vision Based Mouse
This project will be suitable for students interested in the robotics field. The Human-Computer Interaction field has seen a lot of advancements in recent years. Here in this project, we try to improvise this further by trying to control the cursor of our computer without using any physical devices such as a keyboard or mouse.
We aim to move the cursor based on the movement of a colored object in our hand. Sounds interesting? Well, the OpenCV library is used for image processing, and the GUI module of Python called PyAutoGUI is used to control the mouse cursor and its clicking events. For more details about this project, here is a link to the IEEE research document.
IoT-Based Intelligent Robot
Rather than creating normal web and mobile applications, let’s try something new, like creating a simple robot. In this project, we try to develop a remote-controlled wireless surveillance monitoring framework utilizing Raspberry Pi mounted on a robotic vehicle that is capable of obstacle detection and avoidance.
Here, we can control the robot through a workstation that makes use of Web of Things(WoT) technology. It will be an exciting venture to develop a low-cost surveillance robot that gathers several audio and video information through various sensors. This gathered information will be sent to the Raspberry Pi microcontroller which then controls the robot.
In this IOT-based project, we mostly make use of a Raspberry Pi, a USB web camera, and two DC engines with a Robot case, to construct this Mechanical vehicle. This could be a very helpful and reasonably secure spy instrument. Sounds great? Check out the given IEEE document for more details about this project.
Predicting influencers in a Social Network
In recent years, the widespread usage of social media and other online networks has sky-rocketed. This has also led to a very rapid increase in the power of social media influencers in young minds. In this scenario, it will be pretty useful to create software that can identify the true influencers based on their social media features.
The dataset from Kaggle provided by PeerIndex is used here for training. Naive Bayes and Coordinate ascent-based algorithms can be employed for this project. Check out this IEEE paper to get a comparison of both these algorithms and more details about the project.
IoT-Based Automatic Attendance System
Attendance plays a major role in all classrooms, even though most of the students are big fans of it. In this project, we are aiming to provide a better alternative to the tedious and tiresome process of manual marking of attendance. Imagine an automatic attendance system that can capture images, recognize images, and mark attendance automatically. This is exactly what we are trying to implement.
Our automatic attendance system will be initially trained with the student database, which includes student names, photos, and personal details. During every class hour, attendance will be taken automatically using the image recognition technology and will be updated to the student’s database.
If any student is absent, the message will be automatically sent to their parents or guardian of the absentees using the GSM module. The system will also update the everyday attendance database to the Head of the department. If you wish to try this latest IoT-based project and implement this in your institution, check out this document for a more detailed explanation.
These are some of the latest and popular choices in computer science projects. Go through each one of them and the associated documents, find out the projects of your interest, and try implementing the projects that you’re most interested in.
If you’re interested in more project ideas, I’ve created a detailed article on 55 Python project ideas that can be helpful for you. Check it out if you’re interested.
Remember, the more you experiment with various project ideas, the more knowledge you gain. Go ahead, happy coding.