Because of the metaphysical shift in the technological era, the world is witnessing machine to machine (M2M) communication. Sensors are omnipresent, owing to which wireless sensor networks (WSNs) are developing as a key enabling technology for the Internet of Things (IoT). M2M interaction poses a severe threat to the lifetime of the network. Clustering plays an essential role in elevating the energy efficiency of the WSN. Particularly, uniform distribution of cluster heads (CHs) is crucial for achieving better network lifetime and uninterrupted sensing from the area under observation. For this, we propose an efficient two-fold clustering algorithm, namely second-fold clustering (SFC). In the first phase, the selection of CH is made based on zonal residual energy and zonal degree of connectivity. In the second phase, the leftover nodes known as isolated nodes are clumped. CH is selected based on the zonal degree of connectivity to ensure that energy is disbursed (almost) uniformly by all the nodes. This uniformity makes it suitable for integration with the IoT. To find out the efficacy of SFC, carried rigorous experimental study out where it is compared to two existing clustering algorithms. The simulation results show that SFC outperforms its counterparts. The results showed that SFC improved network lifetime by approximately 9.6% and 10.2% compared to regional energy-aware clustering scheme and Residual-Low Energy Adaptive Clustering Hierarchy (R-LEACH), respectively.

In higher education institutions (HEI), particularly in biology and medical education, the use of 3D animation, virtual reality, and simulation offers great potential in terms of enhancing learning and engaging students. Higher education researchers are still investigating virtual reality’s possibilities and outcomes in various fields. This study focuses on the effects of 3D gamification using an Artificial Intelligence integrated Internet of Medical Things (AIoMT) implemented with virtual reality application for biology and medical students to learn about the human brain. Nowadays, both theoretical and practical education frequently incorporate virtual reality and augmented reality. Virtual tours of the human body’s systems are offered to biology students so that they may comprehend such systems’ functions. This study focuses on the use of 3D animation, virtual reality, and simulation in medical education, with a specific focus on the effects of a 3D gamification app using the Internet of Medical Things (AIoMT) on medical professionals’ passion for learning. This study uses the ARCS model and SEM analysis to examine the impact of virtual reality on students’ motivation and learning. The results show that virtual reality positively impacts motivation and the understanding of the concept-to-execution process through practice and simulation-based training. To assess how well students are learning, what they are analyzing, and how well they can understand the objects of analysis, a 3D-simulation-based and user-feedback-based design has been developed using the proposed research methodology. According to this article’s findings, a smartphone app that uses virtual reality can help medical professionals better understand the concept-to-execution process through practice. VR simulation-based training, as well as Biology teachers or medical colleges, can offer high-definition 3D VR models rather than organs in jars to understand the human anatomy and its functions more experientially and effectively.

Multimedia tools and immersive technology have enormous potential for actively engaging students and improving learning quality. This research aims into the use of virtual reality (VR) in physical training and sports rigorous training to give students a new perspective on college training and educational training, as well as to improve the professional level and training excellence of college athletes. We present a revolutionary Virtual Reality-based Physical Training (VR-PT) technology for effective virtual reality instruction on a digital application. The semi-supervised learning framework was used to implement movement inputs and interactive reality methods. Virtual simulation and differentiated selection techniques based on Q statistical data are used first to identify sports students with excellent independent learning capacity, followed by the classifier’s neighbour reliability. Experiment results indicate that this strategy can successfully support physical training practices while also improving students’ learning performance. The effectiveness of students in athletics has increased by 30%. Simultaneously, two-thirds of people believe their involvement in athletic training has increased by 80%, and 90% of college coaches believe that using VR technology throughout physical training is extremely important for improving the technical aspect as well as the reliability of college sports training.

To communicate efficiently with a prospective user, auditory interfaces are employed in mobile communication devices. Diverse sounds in different volumes are used to alert the user in various devices such as mobile phones, modern laptops and domestic appliances. These alert noises behave erroneously in dynamic noise environments, leading to major annoyances to the user. In noisy environments, as sounds can be played quietly, this leads to the improper masked rendering of the necessary information. To overcome these issues, a multi-model sensing technique is developed as a smartphone application to achieve automatic volume control in a smart phone. Based on the ambient environment, the volume is automatically controlled such that it is maintained at an appropriate level for the user. By identifying the average noise level of the ambient environment from dynamic microphone and together with the activity recognition data obtained from the inertial sensors, the automatic volume control is achieved. Experiments are conducted with five different mobile devices at various noise-level environments and different user activity states. Results demonstrate the effectiveness of the proposed application for active volume control in dynamic environments.