Infectious viruses are spread during human-to-human contact and can cause worldwide pandemics. We have witnessed worldwide disasters during the COVID-19 pandemic because of infectious viruses, and these incidents often unfold in various phases and waves. During this pandemic, so many deaths have occurred worldwide that they cannot even be counted accurately. The biggest issue that comes to the forefront is that health workers going to treat patients suffering from COVID-19 also may get infected. Many health workers have lost their lives to COVID-19 and are still losing their lives. The situation can worsen further by coinciding with other natural disasters like cyclones, earthquakes, and tsunamis. In these situations, an intelligent automated model is needed to provide contactless medical services such as ambulance facilities and primary health tests. In this paper, we explore these types of services safely with the help of an intelligent automated transportation model using a vehicular delay-tolerant network. To solve the scenario, we propose an intelligent transportation system for automated medical services to prevent healthcare workers from becoming infected during testing and collecting health data by collaborating with a delay-tolerant network of vehicles in intelligent transport systems. The proposed model automatically categorizes and filters infected patients, providing medical facilities based on their illnesses. Our mathematical evaluation and simulation results affirm the effectiveness and feasibility of the proposed model, highlighting its strength compared to existing state-of-the-art protocols. © 2024 Elsevier B.V.

We study the smoothness of the moduli space of finite quiver vector bundles over the smooth complex projective curves

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Cyber-physical systems (CPS) can significantly transform our daily lives as it is an emerging area for future innovative services. CPS have the inherent features and benefits of using available networks such as wireless sensor networks, following generation networks, and the Internet. However, network disconnection is a concern in traditional networks. Delay tolerant networks can solve the problem of network disconnection. Mobile wireless networks are often characterized by frequent segmentation and potentially long message delivery delays. Modern applications in these networks have shown that energy is an essential concern as energy sources are limited. Nodes in a delay tolerant network are characterized by sparse connectivity, which provides an opportunity to save energy by periodically disabling the node radio (i.e., putting the node into sleep mode). Another problem is the limited energy of nodes, so an effective energy-saving model is necessary to allow these networks to operate for long periods. We have proposed an adaptive energy-aware DTN-based communication layer for CPS. We have designed an energy-saving system for CPS based on a delay tolerant network in the proposed model. We have proposed an energy-saving model that allows energy savings by managing the wake-up period at regular intervals while keeping the node inactive for the rest of the time. We evaluate our model implementing the Opportunistic Network Environment Simulator (ONE). The achieved results show that our energy that our energy-saving model has increased battery life five times as compared to constant access.