The land registry system is one of the very important department in any governance system that stores the records of land ownership. There are various issues and loopholes in the existing system that give rise to corruption and disputes. This requires a significant chunk of valuable government resources from judiciary and law enforcement agencies in settling these issues. Blockchain technology has the potential to counter these loopholes and sort out the issues related with land registry system like tempering of records, trading of the same piece of land to more than one buyer. In this paper, a secure and reliable framework for land registry system using Blockchain has been proposed. The proposed framework uses the concept of smart contract at various stages of the land registry and gives an algorithm for pre-agreement. First, we describe the conventional land registry system and reviews the issues in it. Then, we outline the potential benefits of employing Blockchain technology in the land registry system and presented a framework. Finally, a number of case studies are presented.

Providing an identity solution is essential for a reliable blockchain-based land registry system. A secure, privacy-preserving, and efficient identity solution is essential but challenging. This paper examines the current literature and provides a systematic literature review in three stages based on the three research questions (RQ) that show the assessment and interpretation process step by step. Based on the parameters and RQ specified in the research methodology section, a total of 43 primary articles have been selected from the 251 articles extracted from various scientific databases. The majority of these articles are concerned with evaluating the existing self-sovereign identity (SSI) solutions and their role in the blockchain-based land registry system to address the compliance issues in the existing SSI solutions with SSI principles and find the best possible SSI solution to address the identity problems in the land registry. The existing digital identity solutions cannot handle the requirements of the identity principle and are prone to various limitations like centralization and dependency on third parties that further augment the chance of security threats. SSI has been designed to overcome these limitations and provide a secure, reliable, and efficient identity solution that gives complete control to the users over their personal identity information (PII). This paper reviews the existing SSI solutions, evaluates them based on the SSI principles, and comes up with the best possible SSI solution for a blockchain-based land registry system. It further provides a detailed investigation of each SSI solution to present its functionalities and limitations for further improvement.

FANET (flying ad-hoc networks) is currently a trending research topic. Unmanned aerial vehicles (UAVs) have two significant challenges: short flight times and inefficient routing due to low battery power and high mobility. Due to these topological restrictions, FANETS routing is considered more complicated than MANETs or VANETs. Clustering approaches based on artificial intelligence (AI) approaches can be used to solve complex routing issues when static and dynamic routings fail. Evolutionary algorithm-based clustering techniques, such as moth flame optimization, and ant colony optimization, can be used to solve these kinds of problems with routes. Moth flame optimization gives excellent coverage while consuming little energy and requiring a minimum number of cluster heads (CHs) for routing. This paper employs a moth flame optimization algorithm for network building and node deployment. Then, we employ a variation of the K-Means Density clustering approach to choosing the cluster head. Choosing the right cluster heads increases the cluster’s lifespan and reduces routing traffic. Moreover, it lowers the number of routing overheads. This step is followed by MRCQ image-based compression techniques to reduce the amount of data that must be transmitted. Finally, the reference point group mobility model is used to send data by the most optimal path. Particle swarm optimization (PSO), ant colony optimization (ACO), and grey wolf optimization (GWO) were put to the test against our proposed EECP-MFO. Several metrics are used to gauge the efficiency of our proposed method, including the number of clusters, cluster construction time, cluster lifespan, consistency of cluster heads, and energy consumption. This paper demonstrates that our proposed algorithm performance is superior to the current state-of-the-art approaches using experimental results.

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