The study and production of software for computers go by various titles, including information technology (IT), computer science engineering (CSE), and computer science. Students of computer science and information technology students won’t find a better source of inspiration elsewhere. All CSE and IT student Work, both past, and present, is archived here.

Therefore, it creates a database of the most innovative and futuristic AI project ideas in computer science, information technology, and other software engineering disciplines. Before digging deeper into artificial intelligence research, familiarity with robot differences and similarities is helpful.

If you are a senior in an engineering or IT program and want to learn about the five most promising AI project ideas, you have come to the right spot.

  1. Counting and identifying vehicles using computer vision

People leave rural regions for urban centers to be closer to amenities like education, employment, and healthcare. Congestion is a serious issue in many of the world’s largest cities. Congestion on the roadways can be attributed to various factors.

The expansion of the population has necessitated the construction of more roads, reducing the efficiency of the existing network. Major cities often have traffic jams due to inadequate routes relative to the number of vehicles. As more people move to cities, more cars will be on the road.

When it comes to intelligent transportation and traffic management, for example, taking public transit is equivalent to installing a system to identify and tally individual cars. Inefficient traffic management can also be attributed to a lack of real-time traffic data.

  1. System for Identifying Drunk Drivers

In 2018, the World Health Organization reported that around 1.3 million people were killed in traffic-related incidents. (WHO).

The National Highway Traffic Safety Administration’s (NHTSA) annual research on road mortality indicated that 91,000 people died in vehicle accidents caused by sleepy drivers in 2017, while 795 people died from fatigue.

Crashes sometimes include drivers who are too tired to operate their vehicles safely. After two or three hours of driving, researchers have observed a comparable reduction in a driver’s energy and steering ability.

The hazards are the same throughout lunch, the early afternoon, and the late hours of the night. Drowsiness might be thought of as tired when one is actively doing something.

It is possible to use the Driver Drowsiness Detection System to analyze three levels of drowsiness in this way: being awake, having REM sleep, and having a non-REM sleep (NREM).

  1. Tag Expectations: Synopsis of the Film with Predicted Tags

Using social tagging, you may learn about new films, stories, soundtracks, pieces of information, and visual and emotional experiences. This info might be used to build better automated algorithms for movie tagging.

Automatic rating systems tell viewers what they may anticipate from a movie, while recommendation algorithms help them locate another film they would enjoy. This project aims to gather data on movies and summaries of such films.

Using this strategy, we developed 70 tags that emphasize individual aspects of film plots and the multi-label interactions between these tags and over 14,000 plot summaries.

The designations are compared to the film’s genre and the character’s development to see if they make sense. To conclude, this dataset will be used to see if tag values can be deduced from plot summaries.

According to our findings, the corpus will be helpful for narrative analysis in the future.

Inadequate labeling can severely detract from the quality of the user experience. a. Predict many tags with a high recall and accuracy without being overly restricted by latency.

  1. The Generation of Forensic Images by Software

We used some form of software dedicated to that purpose to enhance or rectify the image. Machine learning methods have resulted in significant simplifications in the image processing workflow. Forensic drawings made using GAN may now be accessed through image generator data.

Computer vision, image processing, and machine learning researchers have long been interested in developing methods for automating the production and recognition of faces in visual media.

We use machine learning techniques and technologies to create an image that looks very much like a drawing. Since this method streamlines the process of making forensic images, it has the potential to result in more convincing graphics. High levels of automation mean the need for human intervention is significantly reduced.

The network’s generator and discriminator need training before they can be used.

Both the discriminator and generator may be trained separately.

  1. Recognizing Credit Card Scams

Using a stolen credit card may get you in serious trouble with the law. The key objectives of this research are to (1) classify the many forms of counterfeit credit cards and (2) compare and contrast various methods for detecting fraud. The most current studies on credit card fraud detection will also be reviewed and debated.

This website is helpful since it provides definitions of essential phrases and relevant statistics on credit card fraud. Several procedures may be introduced and required depending on the sort of fraud suffered by the credit card industry or financial institutions.

It is anticipated that the suggestions offered in this study would be more economically viable. The need to take this action to protect against credit card theft is emphasized.

Still, moral questions arise when otherwise honest people are wrongfully convicted of credit card theft. There are many different names for logistic regression.


As a result, opportunities involving artificial intelligence abound for your projects.

Try these tests if you wish to sharpen your AI abilities. These tasks will help you learn AI concepts rapidly and prepare you for professional practice.

Even if you don’t have much experience in AI, you’re invited to pitch in on some cool projects involving AI.