Using Augmented Reality and Drones in Tandem to Serve Smart Cities

Augmented Reality Technologies as such have been known since the first decade of the 21st century. However, due to the relatively high costs of terminal equipment, the lack of mass demand in industries, their unpreparedness to implement augmented reality in production processes, the limited use of augmented reality in the educational process, etc., this technology did not become networked. In the broadest sense of this word, the traffic generated by augmented reality significantly affects both the principles of network construction and its planning. The article is devoted to studying the interaction of augmented reality applications and control methods for Unmanned Aerial Vehicles. The study was carried out experimentally using the developed experimental stand. During the experiment, an augmented reality application was used to control the UAV. The assessments of the quality of service of the network and subjective evaluations of the quality of perception were obtained. The Hurst parameter was used to determine the relationship between the quality of communication network service and the quality of perception. The parameters of the communication network maintenance are determined to ensure the specified rate of perception when controlling the UAV using the augmented reality application.

Blended Learning Through an Interactive Mobile Application for Teaching Autistic Kindergarten Students

The mobile applications industry has had significant growth in the last few years. Mobile phones are everywhere since we use them in every part of our daily lives for entertainment, communication and other various uses. Unfortunately, there was also a substantial increase the number of autism cases in kids around the world, which has prompted for a dire need of a therapy method that is cheap, reliable and accessible for everyone who needs it. Researchers have tried several methods, like robotics and virtual reality, to help in the therapy of autistic children. While their results were promising, these technologies are still out of reach of most users due to their high cost. Mobile phones, however, are much more accessible since everyone has one, and they have a wide array of useful gadgets that can be used in making the therapy sessions more engaging and fun such as cameras, accelerometers, speakers, microphones and others. This project aims to design and implement an interactive learning environment based on a mobile application for teaching kids with special needs.

Face Recognition Based on Artificial Neural Network: A Review

The face recognition/detection is considered as one of the most popular applications in the field of image processing and biometric pattern recognition systems. Although the face recognition approach improves authentication procedure, nevertheless still many challenges appear due to diversities in human facial expression, image huge size, background complexity, variation in illumination, poses, blurry, etc. Therefore, the face detection procedure is classified as one of the most difficult tasks in computer vision. This research paper tends to address the concept of image processing along with the use of the Artificial Neural Network approach and represent it is a potential capability in enhancing the method of extracting face pattern through an adaption of various ANN topologies. Furthermore, it represents fundamental phases associated with the construction of any facial recognition system. Finally, it provides a general overview of different literature survives that related to face recognition based on the use of different ANN approaches and algorithms

Image Processing Technique for the Detection of Alberseem Leaves Diseases Based on Soft Computing

Detecting plant diseases using the traditional method such as the naked eye can sometimes lead to incorrect identification and classification of the diseases. Consequently, this traditional method can strongly contribute to the losses of the crop. Image processing techniques have been used as an approach to detect and classify plant diseases. This study aims to focus on the diseases affecting the leaves of al-berseem and how to use image processing techniques to detect al-berseem diseases. Early detection of diseases important for finding appropriate treatment quickly and avoid economic losses. Detect the plant disease is based on the symptoms and signs that appear on the leaves. The detection steps include image preprocessing, segmentation, and identification. The image noise is removed in the preprocessing stage by using the MATLAB features energy, mean, homogeneity, and others. The k-mean-clustering is used to detect the affected area in leaves. Finally, KNN will be used to recognize unhealthy leaves and determines disease types (fungal diseases, pest diseases (shall), leaf minor (red spider), and deficiency of nutrient (yellow leaf)); these four types of diseases will detect in this thesis. Identification is the last step in which the disease will identify and classified.

Smart Online Grocery Shopping App Development

Shopping is one of the activities that some people consider part of their life, while others do not even think of it. This comparison makes us discover people's problems with shopping. People have shopping problems such as limited time, expats in foreign countries without cars, a transportation issue, people consider physical shopping as a waste of time, health issues, long-distance to market. And the difficulty in obtaining some items. As the problems mentioned above, we have explored our idea, which is related to personal shopping. Therefore, we have built an application that combines different market shops, i.e. (Malls, supermarkets, and pharmacies). This personal grocery shopping is an innovative app that allows the customers to get all their needs and suggest items based on previous history. Then deliver items to their doorstep and can facilitate online shopping procedure where customers can browse unlimited products all at one time. This work supports people in exploiting their time to be safer and more accessible than wasting it physically. Moreover, people can order the product from home instead of going around for long distances for shopping. In addition, this app could help people who are facing health problems and unable to buy something physically to avoid future problems. Finally, some people do not have transportation methods for shopping, and they should keep pace with the evolution.

Humanoid Robot Enhancing Social and Communication Skills of Autistic Children: Review

Autism is a neurological disease that affects people’s social, communicational and mental abilities. This makes it difficult for them to express themselves and integrate seamlessly with other people and society as a whole. With the number of autism cases steadily increasing, researchers and caretakers alike around the world are working on finding a teaching technique to help with the therapy and education of autistic children. Due to the number of resources and expertise that are required for this operation, it has proven to be quite difficult to find such a teaching technique. The results of our literature survey also show that the USA has the most research in this field, followed by England and Spain. The aim of this paper is to study the interaction of autistic children with the humanoid robot NAO. Therefore, we developed different interactive activities and materials for testing the children’s attitude and engagement. After careful observation and experimenting, it was found that the children were much more engaged and excited during the lessons that involved the robot. This can be attributed to its simple and toy-like nature, which makes the lessons more fun and exciting. The children were also more responsive, absorbed more information overall and were even willing to learn new subjects that they previously avoided.

Training and teaching applications for Autistic Children based on C# standalone application

Autism is a disease, which affects the child's ability to communicate with those around them and develop mutual relations with them and hence it needs to have a quick and efficient treatment technique. The earliest age of ASD diagnosis is between 4.5 and 5.5 years. Approximately 6 per 1000 children under eight years suffer from ASD. Statistics show an annual increase of the disease about 3,500 cases of children with autism in the Sultanate of Oman. The aim of this work is to design an Interactive Learning System based Windows Application for teaching the children with Autism. The Windows Application is developed using C# which will be useful to teach the children different things such as Alphabets, Numbers, Fruits, Vegetables and many more. The application is a bi-lingual application (English and Arabic). The application can be used also to test the progress of the children. Also, develop interactive materials that help children with special needs for enhancing their communicating and thinking. In addition develop interactive materials that help children with special needs for enhancing their communication and rational skills which could help them to integrate into the society.

Social and Telepresence Robots a future of teaching

The robotics industry is advancing at rates faster than ever before. It produces plentiful different types of robots incorporated in other fields like medical, defense, manufacturing, and mining industries. Of course, it is no surprise that the robotics industry managed to make its way to the educational field, and with it came the social and telepresence robots. This paper aims to compare social and telepresence robots in the teaching industry in the near future. Both a literature survey and a comparison segment were produced. It was concluded that the future of educational environments would incorporate both of these technologies since they serve different functions. This is to provide the best experience for as wide of a range of people as possible, wherever they are living and whatever disabilities/ challenges they are experiencing.

Expert system for identifying and analyzing the IoT devices using Augmented Reality Approach

Biometrics In conjunction with the new development of the Internet of Things (IoT), augmented reality (AR) systems are evolving to visualize 3D virtual models of the real world into an intelligent and interactive virtual reality environment that facilitates physical identification of objects and defines their specifications efficiently. The integration between AR and IoT in a complementary way helps identify network-related items' specifications and interact with the Internet of Things more efficiently. An identity is a dedicated, publicly known attribute or set of names for an individual device. Typically, identifiers operate within a specific area or network, making it difficult to identify things globally. This paper explores the use of Augmented Reality (AR) Technology for identifying devices and displaying relevant information about the device to the user. Based on the developed model network, the developed system of identification of IoT devices was tested. Also, the traffic generated by the AR device when generating requests to the organization server was investigated. According to the test results, the system is undemanding to the main network indicators. The system-generated traffic is self-similar. The test results show that the server software can solve the problems of identifying IoT devices through interaction with augmented reality devices.

Viability of Robots in Improving Autistic Student’s Engagement and Happiness When Learning

The adoption of robotics in other industries is increasing exponentially at a rapid pace due to increased interest in the field. Advancements in robotic technology allow them to be more capable in teaching a variety of topics while costing much less than even just a decade ago. This means that robots are more ready than ever before to be deployed globally in the educational space. The aim of paper is to check the viability of robots in improving autistic students’ engagement and happiness, rather than just their performance. 6 autistic students aged 7 – 12 took part in this experiment (4 male and 2 female). Several different structured scenarios and tasks were used to evaluate the student’s happiness and engagement on a scale of five. It was found that the children showed an improvement of 144% across the board, when comparing the happiness score and an increase of 61.4% for the students’ engagement score. It was also found that the children were showing much more emotion and were much more responsive during the tasks.