The concept of the Internet of Things (IoT) is an innovation paradigm that suggests linking physical devices together to share data and work toward a common goal. Nodes in an IoT network are anticipated to communicate with one another and with third-party Internet services. However, not all network nodes have direct Internet access due to high deployment costs. As a result, additional network nodes should be using Internet-connected nodes as gateways to transmit data to online services. Due to its central role in establishing connections between nodes in a network and distributing data packets, routing protocols have emerged as a significant challenge in IoT use cases. The work of routing is complicated in mobile IoT scenarios due to the topology changes brought on by the mobility of nodes. To better handle the mobile nature of the devices, existing Iot routing solutions typically exhibit severe constraints and poor performance in such cases. This study proposes an improvement to the existing protocols; the Cluster Formation Protocol with Neuro Fuzzy Rules, in light of the fact that main routing techniques for low-power network are unable to achieve adequate performance in the shown IoT context. The energy efficiency of the routing process in WSN can be improved with the help of cluster based routing thanks to the proposed efficient routing algorithms. In addition, the efficiency of clustering & cluster based routing protocols can be enhanced by employing intelligent approaches like fuzzy rules, temporal constraints, and categorization via deep learning. Therefore, the safe transfer of data packets from of the source point to the sink node necessitates careful consideration in the development of cluster dependent routing algorithms. The cluster dependent routing method presented is developed, evaluated with respect to a number of criteria, and shown to be effective.

In this paper a novel image based data security and authentication based, image watermarking scheme that combines the discrete wavelet transform (DWT) and Singular value decomposition (SVD) is proposed. This paper explains a dual watermarking scheme with different algorithm. At first original image is divided into its appropriate levels by using DWT, and convert LL sub-band to its red, green and blue component, and the obtained colour component of image is divided into non-overlapping blocks, final apply SVD on each block to obtained the singular value for watermarking. The second scheme chose HH sub-band of original image and converts its own red, green, blue component, and then apply SVD to each colour component to obtain the singular value for watermarking. We take two watermark images one is Logo image and other is Quick Response Code (QR Code) for experiment. Results obtained from the experiment reflect the efficiency of the proposed scheme.

The Internet of Things (IoT) has witnessed exponential growth, connected billions of devices, and enabled various applications of distributed and heterogeneous nature. The extensive embrace of IoT devices has sparked noteworthy apprehensions regarding security. The majority of these devices prioritize user-friendliness during manufacturing rather than robust security. Consequently, conventional security measures frequently prove inadequate in safeguarding the integrity, confidentiality, and accessibility of IoT networks. Together, these issues give rise to substantial threats to the entire system. Each IoT device generates a cryptographic hash of its data and records it on the blockchain. Smart contracts and consensus mechanisms can be utilized to facilitate node status management and consensus on the state of the IoT network. Integration of blockchain technology for detecting malicious activity in IoT networks brings several benefits, including increased transparency, data integrity assurance, and decentralized trust. Blockchain technology offers a trustless environment in which multiple parties can collaboratively verify and confirm the legitimacy of data and transactions. This characteristic is achieved through consensus algorithms like proof-of-work and proof-of-stake, effectively thwarting attempts by malicious entities to manipulate or jeopardize the integrity of the system. Blockchain's resilience to attacks and tampering provides an additional layer of security for IoT systems. Nodes can refer to the blockchain for verifying the integrity and authenticity of the data generated by other nodes, enabling the identification and isolation of malicious actors in the network. <!----> <!----> <!----> <!---->

Healthcare delivery is poised to undergo a paradigm shift as a result of the convergence of cloud computing and Healthcare 5.0, which promises to revolutionize patient care. In order to enable Healthcare 5.0, a patient-centric strategy that combines cutting-edge technologies and data-driven insights to customize healthcare experiences, this chapter serves as an introduction to the transformative potential of cloud computing. Beginning with a thorough explanation of cloud computing's fundamental principles, architecture, and distinguishing features, the chapter moves on to its main points. Introduced is the idea of healthcare 5.0, emphasizing its emphasis on patient empowerment, personalized medicine, and the harmonious fusion of medical knowledge and technology. By utilizing telemedicine, cloud-based data analytics, and artificial intelligence (AI), Healthcare 5.0 seeks to go beyond the conventional one-size-fits-all method of providing healthcare services. Request access from your librarian to read this chapter's full text.

Parallel prefix is an important technique that has been widely accepted in many area of scientific and engineering research. In this paper we propose an improved parallel prefix computation algorithm on n × n mesh network that requires 2n + 5 times. Our proposed algorithm can be compare with the traditional parallel prefix algorithm that requires 3n + 2 time on same architecture