The Smart Learning Tool for Kids with Real-time Image Classification is an AI-powered educational tool designed to assist young learners in recognizing and identifying objects through real-time image classification. The system captures images using a webcam, processes them through a Convolutional Neural Network (CNN) model and outputs the corresponding class label. It provides immediate audio feedback by pronouncing the class name in four languages: English, Myanmar, Thai and Chinese. The system aims to enhance kids’ learning experience by engaging multiple senses—visual and auditory—that makes learning interactive and multilingual. The CNN model is trained with custom training data, enabling accurate classification of 12 object classes. This system serves as a smart and user-friendly tool for early childhood education.

The World Wide Web serves as a huge widely distributed global information service center. The tremendous amount of information on the web is improving day by day. So, the process of finding the relevant information on the web is a major challenge in Information Retrieval. This leads the need for the development of new techniques for helping users to effectively navigate, summarize and organize the overwhelmed information. One of the techniques that can play an important role towards the achievement of this objective is web document clustering. This paper aims to develop a clustering algorithm and apply in web document clustering area. The Cuckoo Search Optimization algorithm is a recently developed optimization algorithm based on the obligate behavior of some cuckoo species in combining with the levy flight. In this paper, Cuckoo Search Clustering Algorithm based on levy flight is proposed. This algorithm is the application of Cuckoo Search Optimization algorithm in web document clustering area to locate the optimal centroids of the cluster and to find global solution of the clustering algorithm. For testing the performance of the proposed method, this paper will show the experience result by using the benchmark dataset. The result obtained shows that the Cuckoo Search Clustering algorithm based on Levy Flight performs well in web document clustering.