Top 5 Big Project Ideas of Artificial Intelligence (AI)

In The Field Of Computer Science Engineering, sometimes known as CSE, and information technology, or IT, the creation and research of computer software occur. There is no better place for CSE and IT undergraduates to find inspiration for their next project. Here is the complete collection of IT and CSE student projects.

As a result, compiles a list of the most excellent and recent Artificial Intelligence project ideas for CSE, IT, and other software engineering disciplines. All of the final year projects were evaluated and put together into a list so students could select their favorite topic for debate in the last year.

If you’re in your last year of engineering or IT and looking for articles about top 5 big project ideas of Artificial Intelligence (AI), you are at the right site.

1.    A Vehicle Identification and Counting System Based On Computer Vision

Traffic congestion is a significant issue in many major cities throughout the world. Several factors contribute to traffic gridlock. People move from rural to urban regions in search of greater access to health care, education, employment, and better-built homes.

Insufficient road capacity has resulted from an increase in population, which has led to delayed expansion. It’s also becoming more common for people to live in cities, increasing traffic. Because of the imbalance in the number of roads and automobiles, traffic jams are common in big cities.

Taking public transit, for example, has the same effect. Inadequate traffic management is also a result of the absence of real-time traffic information. Vehicle detection and counting systems play a critical role in intelligent transportation, particularly traffic management.

2.    System for Detecting Drunk Driving In the Driver

World Health Organization (WHO) vehicle accident studies estimate that in 2018, over 1.3 million people died on roadways.

According to the National Highway Traffic Safety Administration’s (NHTSA) annual report on traffic fatalities, 795 persons died from sleepy driving in 2017, and 91,000 died from car accidents involving drowsy driving.

One of the causes of car accidents is a tired driver. Similarly, the researchers have shown that the driver’s energy levels drop after 2 to 3 hours of driving, as does their steering ability.

Similar risks exist in the early afternoon, following lunch, and at midnight. Drowsiness, then, can be characterized as a condition in which a person experiences sleepiness while awake and engaged in activities.

Thus, the Driver Drowsiness Detection System enables us to study three groups of persons who suffer from drowsiness: those who are awake, those who are in rapid eye movement (REM), and those who are in non-REM sleep (NREM).

3.    Plot Synopses with Tags: Predictions for the Tags

Cinematic genres, story structures, soundtracks, metadata, and visual and emotional experiences may all be discovered through abstract social tagging. Such data can be helpful in the development of automated systems for creating movie tagging systems.

Recommendation engines can benefit from automatic tagging systems by better retrieving comparable films, while audiences can anticipate what to expect from a movie going into it. This paper’s goal is a corpus of movie plot synopses and tags.

Using this technique, we have built up a 70-tag set that reveals the many properties of movie plots and the multi-label connections of these tags with over 14,000 synopses of movie plots.

These tags are examined to see whether they are linked to the movie genre and the flow of emotions throughout the film. Finally, this corpus will be used to test whether plot synopses may be used to infer tag values.

We expect the corpus to benefit from additional tasks that call for narrative analysis.

Incorrect tags might negatively damage the customer experience. a. Predict as many tags as feasible with high precision and recall. b. No severe latency limits.

4.    Image Generator for Forensic Sketches

Image processing has been an effective technique for enhancing or refining the image. Using machine learning methods, the process of picture processing has been dramatically simplified. Forensic sketches to image generator information utilizing GAN are now available.

Computer vision, image processing, and machine learning have all long been interested in automating the development and detection of facial sketches in photos.

Our research uses machine learning algorithms/systems to turn a person’s sketch into an image with the same trait or attribute as the drawing. Because the entire procedure is computerized, little effort is required from the user. This method may produce forensic sketches quickly and accurately, producing a more realistic image.

Teaching a model

The discriminator and generator must first be trained before the network can be used.

The Discriminator and Generator can be trained separately.

5.    Detection of Fraudulent Use of Credit Cards

Fraud is a significant legal issue in the credit card industry. The primary objectives of this study are to identify the various types of counterfeit credit cards and to investigate alternative fraud detection technologies. Another goal is to discuss and analyze the latest findings in the field of credit card fraud detection.

Credit card fraud terminology and numbers are defined, as well as relevant data, on this page. Various actions can be implemented and enforced based on the sort of fraud that the credit card industry or financial institutions are dealing with.

The suggestions provided in this study are likely to save money and be more effective. The relevance of implementing these measures to reduce credit card fraud is highlighted here.

However, there are still ethical concerns when legal credit card users are mistakenly labeled fraudulent.

Classifier, Random Forest, Autoencoder, and SMOTE are all synonyms for Logistic Regression.

Researching different machine learning and deep learning algorithms, as well as the erroneous processes based on fraudulent credit cards, is the primary goal of this paper.

Conclusion

As a result, you now have an abundance of AI Project Ideas.

These tasks will assist you in honing your artificial intelligence (AI) abilities. In addition, these projects will put you on the fast track to becoming an AI specialist while simultaneously preparing you for a career in the field.

You may participate in these fascinating AI projects as a complete novice or a seasoned AI professional.

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