Both object-oriented and relational database management systems are referred to as DBMS. The web-scale is expanding at an incredible rate, and with it comes an increase in mobile applications, technologies, and social media platforms. The rapid growth of these technologies produces a variety of structured and unstructured data in various forms, each of which has various consequences for data security. Using RDBMS and OODBMS, this study's methodology outlines the development, installation, and management process of multiple and complicated data sets. This study gives a documented study comparing different kinds of data stored in databases by employing two types of database techniques: relational database method and object-oriented database technique. We use a different fingerprint database for the web and mobile devices. This database is also managed using different technologies, such as MySQL, and it accommodates data generated using distinct methods. In addition, this study explores the benefits and advantages of the various databases and determines the ideal database management system for organizations. According to the survey's findings, RDBMS stores data and the relationships between them in tables, but OODBMS stores data in objects, in a manner analogous to Object-Oriented Programming (OOP). According to the study's findings, the primary distinction between relational database management systems (RDBMS) and object-oriented database management systems (OODBMS) is that RDBMS is a Database Management System based on the relational model. In contrast, OODBMS is a Database Management System that facilitates creating and modeling data as objects.

The Internet of Things is assisting in developing a new and more intelligent world in which everything will fall under its purview. The issue of security is by far the most critical concern and component regarding the Internet of Things. With billions or trillions of connected devices, it will be difficult for future generations to find solutions to the security concerns we face today. The Internet of Things (IoT) paves the way for various entities and applications that benefit humanity. Although it is the most significant accomplishment of the decade, it has also given rise to catastrophic scenarios due to security concerns such as threats, vulnerabilities, and attacks on connected and interconnected devices and objects. Despite this, it is still the most significant achievement of the decade. Businesses and organizations are backing the current paradigm shift by providing financial assistance to researchers and academics. The industry expected to have the most growth over this decade is the Internet of Things, which will connect trillions of different devices. It is anticipated that IoT will alter the method by which we communicate. The Internet of Things poses many significant dangers, including physical attacks, network attacks, encryption attacks, software attacks, authorization, surveillance, identity theft, vandalism, and secure communication. The findings of this research show that none of the IoT security architectures include a security layer.

Modern business is vital to finance, and AI has revolutionized the modern industry. Automation of many business operations has raised global concerns and alarms. Current business and related jobs are rising dramatically as the global population grows. Business administrators' conventional methods could be more efficient for these needs. These new tactics properly manage business products and services so industry persons may use technology to boost profits. It has protected harvest yield from environmental changes, overpopulation, changing business demands, and food safety challenges. Artificial intelligence can promote intelligent production methods to reduce loss and increase returns. Using artificial intelligence platforms, one can collect a considerable amount of data from government and public sites or real-time monitoring and collection of different data using IoT (Internet of Things) and then use it to empower business people to solve all their business problems. This research helps business people worldwide improve their business techniques. This paper uses the waterfall technique to develop and build an intelligent system by sequentially collecting data, analyzing requirements, planning, coding, testing, and implementing. This system can also generate ideas for managing common challenges in farm information systems, improving policy programs, augmentation and analysis, and managing production data. Finally, management information systems are analyzed, and suggestions for further development are made.