Property viewing and real estate decision-making are heavily dependent on spatial understanding and trust, which are difficult to establish through conventional digital media such as videos, photographs and floor plans. The rise of immersive technologies like Virtual Reality presents a new opportunity to transform how people explore and evaluate properties. This research presents a VR-based property tour system guided by an AI-driven MetaHuman agent capable of natural conversation, contextual awareness and socially aware movement. Developed in Unity and deployed on the Meta Quest 2 with the Convai conversational AI framework, users can explore a high-fidelity virtual apartment while receiving personalised, adaptive guidance from the agent in real time. Initial observations from a preliminary user evaluation with ten participants suggest positive improvements across presence, trust, authenticity, engagement and decision confidence, highlighting the clear potential of AI-driven MetaHuman agent for immersive property exploration and brand engagement in real estate contexts.

Invasion of locust swarms has affected the crops in many countries in Africa and Asia, which is a significant threat to food security. Therefore, different approaches are adopted to monitor and control the locust swarms to save the crops. Furthermore, it has been proved in various studies that technology can help in agriculture through drones, real-time data monitoring, or teaching the farmers with the latest tools. Following the UN sustainability goals for food security, this research has presented a Virtual Reality(VR) based educational application to teach sustainable locust management strategies. Using hand tracking technology in the Oculus Quest lets users learn how farmers can deal with locusts without pesticides. Based on a storytelling approach, the methods presented are profitable for the farmers and free of any harm to crops regarding food security. This application can help motivate the adoption of these sustainable locust control strategies in broader interventions for environmental recovery.

During the last decade, there has been a surge in research studies exploring the adoption of Augmented Reality (AR) in educational settings. Within these multiple research studies, AR's capability to extend the teaching and learning environment with augmented 3D learning objects with enhanced interactive capabilities have been demonstrated. This new technology has not been widely adopted in the mainstream but with the recent unprecedented circumstances of COVID-19, there has been an increasing societal willingness to adopt these technologies. AR has been a desirable technology due to its inherent touchless nature which facilitates social distancing at this time but AR applications crucially offer so much more. They can provide interactive functionality through augmentation of the teaching and learning environment within an immersive user experience including 3D interactions with learning objects, gestures, hand interaction, tangible and multi-modal interaction. This paper presents the results of a review of touchless interaction studies in educational applications and proposes the implementation of real-time touchless hand interaction within kinesthetic learning and utilization of machine learning agents. The architecture of two AR applications with real-time hand interaction and machine learning agents are demonstrated within this paper enabling engaged kinesthetic learning as an alternative learning interface.

Augmented Reality (AR) learning has successfully been proven to support new learning pedagogies. The pedagogical approach of Kinesthetic Learning or "Learning by Doing" using AR combined with virtual touchless hand interaction and machine learning agents has not been explored in great detail. Fundamentally this exploration of touchless technologies and learning intelligence has taken on new importance in the new post-COVID world which created a need for more interactive and personalized learning solutions. This research presented the implementation of touchless hand interaction and machine learning agents in an AR learning application for teaching the PC assembly in the resource constraint environment.

Creating the best learning environment for students and handling a large class size is always a big challenge for the teachers in the developing countries. It creates lack of individual attention for students which resulting a higher number of dropouts in earlier school classes. Previous studies show best practices of smart technologies in the classroom. This research conducted to develop an efficient and low-cost solution to create children interaction and increasing engagement and teaching efficiency in the classroom. We developed My Class Manager; a Smartphone application for quiz and test marking, audio quiz for native language learning and performance management throughout the year. This application is for Android OS Smart phones. We conducted three evaluation tests of three classes of size 35, 40 and 45 students in a local school. It created a time-efficient learning environment and provided awesome feedback to develop more functionality in the application. This paper is presenting the quantitative and qualitative results of the pilot study.

Braille literacy is one of the core pillars of education for visually impaired children. Previous studies have highlighted the importance of Braille for Visually impaired children by suggesting that students who read Braille outside of the classroom have higher reading speed and fluency. In resource constrained countries, such as Pakistan, the visually impaired students may acquire the knowledge of Urdu Braille at special education schools. However, there is a dearth of resources for the parents of such children, when it comes to learning Urdu Braille. Therefore, we designed a web-based Urdu Braille Translator and interactive Braille learning tool to enhance the Urdu Braille learning experience for parents of visually impaired. The usability study of this tool was conducted with 15 parents of the visually impaired students.