The Five Most Promising Concepts for Future AI-Based Projects (AI)

Information technology (IT), computer science engineering (CSE), and computer science are all names for studying and creating computer software. CSE and IT students can’t find a more extraordinary resource for ideas than this. All past and present CSE and IT student work are available here.

As a result, it compiles a catalog of the most forward-thinking and cutting-edge AI project ideas in CSE, IT, and other software engineering fields. It would help if you were well-versed in the Difference Or Variances of robots before delving deeper into AI studies.

You have found the ideal place if you are a senior studying engineering or information technology and are interested in reading about the top five significant AI project ideas.

Computer Vision-Based Vehicle Counting And Identification

People migrate to cities from rural areas to be closer to services, including housing, jobs, and healthcare. Throughout the world, many major cities face the severe problem of traffic congestion. There are several reasons for traffic congestion on the roads.

Population growth has resulted in inadequate road capacity, which has slowed progress. Congestion frequently occurs in major cities because the number of roadways is insufficient compared to the number of cars on the road. There are more people on the road because more people are settling in urban areas.

Using public transit, for instance, achieves the same result as using a system to recognize and count automobiles for intelligent transportation, particularly traffic management. Lack of real-time traffic data is also a contributor to ineffective traffic management.

Drunk Driving Detection System

According to WHO statistics, around 1.3 million individuals lost their lives in traffic accidents in 2018. (WHO).

The annual study on road deaths by the National Highway Traffic Safety Administration (NHTSA) found that 91,000 persons lost their lives in vehicle accidents caused by drowsy drivers in 2017, while 795 lost their lives due to exhaustion.

Drowsy driving is a significant contributor to traffic accidents. Researchers have seen a similar decline in a driver’s energy and steering abilities after two to three hours on the road.

Lunchtime, early afternoon, and nighttime all pose the same risks. Therefore, drowsiness may be defined as the feeling of being sleepy yet awake and engaged in some activity.

In this way, the Driver Drowsiness Detection System may study three distinct states of sleepiness: being awake, experiencing rapid eye movement (REM), and experiencing non-REM sleep (NREM).

Tag Predictions: Plot Synopsis With Tags

It’s possible to use social tagging to discover different types of movies, storylines, soundtracks, information, and visual and emotional experiences. This data might be helpful in the research and development of automated methods for the creation of movie labeling systems.

Automatic labeling systems let audiences know what to expect from a film, while recommendation engines may more easily find a similar cinema. This work aims to compile a database of movie-related metadata and summaries.

Using this method, we generated 70 tags highlighting distinct elements of film plots and the multi-label relationships between these tags and more than 14,000 plot summaries.

These labels are analyzed to determine if they are consistent with the film’s genre and the character’s emotional growth. Finally, this dataset will test the idea that tag values may be inferred from plot summaries.

Our research suggests the corpus will be helpful in future narrative analysis situations.

Unsuitable labeling has the potential to harm the user experience significantly. a. Predict many tags while keeping recall and accuracy high and without being too constrained by latency.

Forensic Image Generation Software

The image was improved or corrected using image processing software. Image processing has been substantially streamlined using machine learning techniques. Image generator data may now access forensic drawings created using GAN.

Automating the creation of and recognizing faces in visual media has been a primary focus of research in computer vision, image processing, and machine learning for quite some time.

In our efforts, we employ machine learning methods and tools to produce a picture that closely resembles a sketch. Because of the high degree of automation, the user’s input is minimal. This approach might lead to more lifelike forensic visuals since it facilitates their creation rapidly and accurately.

Before the network can be used, the generator and discriminator must be trained. It is possible to train the discriminator and the generator independently.

Credit Card Fraud Detection

Credit card fraud carries severe legal consequences. The study’s primary goals are to (1) categorize the many types of counterfeit credit cards and (2) analyze different approaches to detecting fraud. Additionally, the most recent research on detecting credit card fraud will be discussed and evaluated.

This site is helpful since it defines key terms and gives pertinent statistics on credit card theft. Several measures may be implemented and made mandatory depending on the specific type of fraud experienced by the credit card industry or financial institutions.

The recommendations made in this research are expected to be more cost-effective. The need for these measures to prevent credit card fraud is highlighted.

Ethical concerns remain when legitimate credit card holders are wrongly accused of fraud.

Logistic regression is known as Classifier, Random Forest, Autoencoder, and SMOTE.

This study’s primary focus is examining various deep learning and machine learning algorithms and incorrect behaviors using counterfeit credit cards.


Therefore, you are flush with possibilities for AI-based endeavors.

If you want to improve your AI skills, you might want to try your hand at these challenges. These assignments will get you up to speed quickly on AI and ready for work in the field. If you’re interested in helping out with some exciting AI projects, you’re welcome to do so, regardless of your level of AI experience.