Access to the internet inside moving vehicles with the proper speed and reliability creates several challenges to avail the service to user's satisfaction, unmanned car operation, traffic control, etc. A Vehicular ad-hoc Network (VANET) is familiar as the appropriate model for broadcasting data among running objects in a certain topographical range and behaves as an intelligent system for road safety and traffic management. A Greedy routing scheme is widely preferred to set a dedicated dynamical path from the source to the destination with the moving bodies that result in several unwanted intermediate nodes as the obstacle to the signal frequencies. The greater number of forwarding nodes in a certain range creates several issues such as process delay, packet loss, etc. leading to a slower and resource-consuming process that is not suitable as the next-generation data dissemination model for ad-hoc network. Hence, a novel Neuro-fuzzy forwarder scheme is proposed for the elimination of undesirable nodes for the achievement of better signal strength with improved performance. Furthermore, the comparative study demonstrates expected performance in path reliability with less latency in end-to-end connection after the node optimization with the proposed system.

An estimated 1.3 million individuals every year pass away in crashes involving cars. A comprehensive vehicular communication system is necessary given the worrisome increase in daily accidents brought on by the spike in the number of vehicles using our roadways. The creation of a fresh communication paradigm with an accident prevention focus was motivated by this need. The research presented here offers an extensive system that uses cutting-edge technology to coordinate dynamic interactions between nearby vehicles. A sophisticated inter-vehicle communication network aided by radio frequency (RF) technology forms the basis of this breakthrough. By enabling vehicles to exchange vital warnings and data, this network fosters a cooperative environment for accident prevention. Each vehicle also has a Visible-Light Communications (VLC) module, which was carefully engineered to identify accidents and transmit realtime accident information to all connected vehicles.

Medical images such as brain MRI, ultrasound, and X-ray images are currently used by doctors to treat many serious diseases in most hospitals and clinics. These images play a major role in medical diagnosis. Diagnostic images with sensitive patient data are recorded and exchanged owing to the advancement of public networks. As a result, maintaining the privacy of sensitive patient data is becoming increasingly important. In medical imaging, the pixels are highly correlated. To reduce pixel correlation, a variety of complex encryption methods have been used in recent years, increasing the algorithm's computational complexity. This paper proposes an image encryption method based on chaos-based shifting operations. Security, convenience, and speed are all advantages of shifting activities. This method initially executes bit-plane flipping and permutation operations, then block-based flipping and diffusion operations to obtain the cipher images. The simulation and security analysis findings show that the proposed approach performs better.