What is IEEE projects?
IEEE projects are those that follow the standards and guidelines set by the Institute of Electrical and Electronics Engineers in fields such as electrical and electronics engineering, computer science, and related areas. These projects have a broad range of topics and technologies and aim to solve real-world issues and advance new technologies. Anyone, including undergraduate and graduate students, researchers, and industry professionals, can develop IEEE projects individually or as a team. These projects offer an excellent opportunity to apply theoretical concepts to practical problems, develop innovative technologies, and gain hands-on experience in the field of study. Ideas for IEEE projects can be found in various sources such as academic journals, conference proceedings, online communities, and research papers.
Advantages of IEEE projects on AI
IEEE projects on AI offer exposure to cutting-edge technology, provide opportunities to work on real-world problems with interdisciplinary collaboration, can lead to career opportunities, and contribute to the advancement of the field through the development of new algorithms and techniques.
1. Cutting-edge technology: AI is an emerging field that is growing rapidly and has the potential to revolutionize several industries. By working on IEEE projects on AI, students, researchers, and professionals can gain exposure to the latest developments and technologies in the field.
2. Real-world applications: AI has several real-world applications such as image and speech recognition, natural language processing, autonomous vehicles, and medical diagnosis. IEEE projects on AI provide an opportunity to work on projects that solve real-world problems and have a significant impact on society.
3. Contribution to the field: IEEE projects on AI can lead to the development of new algorithms, techniques, and technologies that can contribute to the advancement of the field. By working on IEEE projects on AI, researchers and professionals can make a significant contribution to the field and have a lasting impact.
Top 10 IEEE Projects On Artificial Intelligence In 2023
1. Assistive Object Recognition and Tracking System for the Visually Impaired using CNN”
This project proposes an object recognition and tracking system using Convolutional Neural Networks (CNN) to assist visually impaired individuals. The system utilizes a camera to capture real-time images of the surroundings, which are then processed using the CNN algorithm to recognize and track objects of interest.
The system provides audio feedback to the user, which describes the object’s location and properties, such as size, shape, and color. The proposed system aims to enhance the independence and mobility of visually impaired individuals by providing them with a tool to navigate their surroundings safely and efficiently. Experimental results show that the system achieves high accuracy in object recognition and tracking, making it a promising solution for assisting visually impaired people in their daily activities.
2. Comparative Evaluation of R-CNN and YOLO Algorithms for Object Recognition in Urban Environments
Abstract: This research project focuses on evaluating the performance of two pre-trained deep learning algorithms, R-CNN and YOLO, for recognizing street objects in urban environments. The study utilizes the publicly available GRAZ-02 dataset consisting of 1476 raw images of cars, bicycles, and pedestrians.
The deep learning algorithms are fine-tuned and trained on large databases, ImageNet and COCO, and then tested on the dataset. Both algorithms achieved high accuracy, greater than 90%, in recognizing all three objects of interest. The results suggest that deep learning algorithms, particularly R-CNN and YOLO, have promising potential in the automated driving domain for object recognition in urban environments.
3. TensorFlow-based Automatic Personality Recognition Used in Asynchronous Video Interviews
With the development of artificial intelligence (AI), the automatic analysis of video interviews to recognize individual personality traits has become an active area of research and has applications in personality computing, human-computer interaction, and psychological assessment.
Advances in computer vision and pattern recognition based on deep learning (DL) techniques have led to the establishment of convolutional neural network (CNN) models that can successfully recognize human nonverbal cues and attribute their personality traits with the use of a camera.
In this study, an end-to-end AI interviewing system was developed using asynchronous video interview (AVI) processing and a TensorFlow AI engine to perform automatic personality recognition (APR) based on the features extracted from the AVIs and the true personality scores from the facial expressions and self-reported questionnaires of 120 real job applicants
4. Deep learning-based respiratory sound analysis to aid in the detection of chronic obstructive pulmonary disease.
In today’s world, the field of medicine is constantly being aided by technologies such as machine learning and deep learning, which have proven to be effective in tackling medical challenges. These technologies have improved the accuracy of early disease detection by analyzing medical imaging and audio.
Medical practitioners, faced with a shortage of trained personnel, have welcomed such technological advancements as a helping hand in managing an increasing number of patients. The prevalence of respiratory diseases is also on the rise and is becoming a serious threat to society, making it necessary to develop and implement technologies
5. Research on Intrusion Detection Based on Particle Swarm Optimization in IoT.
With the advent of the “Internet plus” era, the Internet of Things (IoT) is gradually penetrating into various _fields, and the scale of its equipment is also showing an explosive growth trend. The age of the “Internet of Everything” is coming.
The integration and diversification of IoT terminals and applications make IoT more vulnerable to various intrusion attacks. Therefore, it is particularly important to design an intrusion detection model that guarantees the security, integrity and reliability of the IoT.
Traditional intrusion detection technology has the disadvantages of low detection rate and poor scalability, which cannot adapt to the complex and changeable IoT environment. In this paper, we propose a particle swarm optimization-based gradient
6. Indian Cuisine Recipe Recommendation based on Ingredients using Machine Learning Techniques
There are plenty of different types of Indian delicacies available with the same ingredients. In India, traditional recipes are varied due to the locally available spices, vegetables, fruits & herbs. In this paper, we purposed a way that recommends Indian recipes based on readily available ingredients and popular dishes.
In this task, we perform a web search to create a collection of recipe types and apply a content-based approach to machine learning to recommend recipes. This system provides Indian food recommendations based on ingredients.
7. Medicine assistance application for visually impaired people
Visual written information nowadays is the basis for most of the tasks but for visually impaired people reading printed text is a challenging task. Nowadays smartphones are very common and accessible to each and everyone. The objective of this project is to assist visually challenged elderly people in taking correct and timely doses of medicines without being dependent on others using their smartphones.
Users need to take pictures of the backside of medicine strips with the help of their mobile camera in the app. The application will scan the text written on it with the help of optical character recognition (OCR) and with the help of text localization techniques it will extract medicine details from the wrapper of medicine.
App also allows users to set reminders to take dosage of their medicine on time. This project is proposed to help visually challenged people with the help of Artificial intelligence, machine learning, image-to-text recognition and voice assistance.
8. Online Smart Voting System Using Biometrics Based Facial and Fingerprint Detection on Image Processing and CNN.
India being a democratic country, still conducts its elections by using voting machines, which involves high costs and manual labor. The web-based system enables voters to cast their votes from anywhere in the world. The online website has a prevented IP address generated by the government of India for election purposes. People should register their name and address in the website
9. Recognition of Objects in the Urban Environment using R-CNN and YOLO Deep Learning Algorithms.
Over the course of the last decade, the subfield of artificial intelligence, called deep learning, becomes the main technology that provides breakthroughs in the computer vision area. Likewise, deep learning algorithms made a major impact in the automated driving domain.
This research aims to apply and evaluate the performance of two pre-trained deep learning algorithms in order to recognize different street objects. Both RCNN, as well as YOLO algorithms, are used to recognize bikes, cars and pedestrians using the public GRAZ-02 dataset composed of 1476 raw images of street objects. Accuracy greater than 90% is achieved in recognizing all considered objects. The
fine-tuning and training of both algorithms is established using databases named ImageNet and COCO, and afterwards, trained models are tried on the test data.
10. Soil Properties Prediction for Agriculture using Machine Learning Techniques.
Information about soil properties help the farmers to do effective and efficient farming, and yield more crops with less usage of resources. An attempt has been made in this paper to predict the soil properties using machine learning approaches. The main properties of soil prediction are Calcium, Phosphorus, pH, Soil Organic Carbon, and Sand.
These properties greatly affect the production of crops. Four well-known machine learning models, namely, multiple linear regression, random forest regression, support vector machine, and gradient boosting, are used for prediction of these soil properties. The performance of these models is evaluated on Africa Soil Property Prediction dataset.
Experimental results reveal that the gradient boosting outperforms the other models in terms of coefficient of determination. Gradient boosting is able to predict all the soil properties accurately except phosphorus. It will be helpful for the farmers to know the properties of the soil in their particular
The field of artificial intelligence is constantly evolving, and the IEEE community is at the forefront of these advancements. The top 10 IEEE projects on artificial intelligence showcase the innovative and ground-breaking research being conducted in this field.
By exploring IEEE papers on artificial intelligence projects, students and researchers can gain valuable insights and inspiration for their own projects. As we move into 2023, the demand for artificial intelligence IEEE projects is only expected to increase, and the IEEE community will undoubtedly continue to push the boundaries of what is possible in this exciting and rapidly growing field..
So, let us explore and create our own artificial intelligence IEEE projects to contribute to this exciting and promising field of technology.
1) How to get source code of AI Based IEEE Projects?
Visit our website citl projects and register your name and request for the source code depend on the project we can assist in solving that project and guide you through. we have vast collection solved papers
2) How does the IEEE Project on AI helps students?
AI has several real-world applications such as image and speech recognition, natural language processing, autonomous vehicles, and medical diagnosis. IEEE projects on AI provide an opportunity to work on projects that solve real-world problems and have a significant impact on society.This will helps the students to showcase their skills to gain employment opportunities in this field.