Multidisciplinary approaches in science are still rare, especially in completely different fields such as agronomy science and computer science. We aim to create a state-of-the-art floating ebb and flow system greenhouse that can be used in future scientific experiments. The objective is to create a self-sufficient greenhouse with sensors, cloud connectivity, and artificial intelligence for real-time data processing and decision making. We investigated various approaches and proposed an optimal solution that can be used in much future research on plant growth in floating ebb and flow systems. A novel microclimate pocket-detection solution is proposed using an automatically guided suspended platform sensor system. Furthermore, we propose a methodology for replacing sensor data knowledge with artificial intelligence for plant health estimation. Plant health estimation allows longer ebb periods and increases the nutrient level in the final product. With intelligent design and the use of artificial intelligence algorithms, we will reduce the cost of plant research and increase the usability and reliability of research data. Thus, our newly developed greenhouse would be more suitable for plant growth research and production.

This study evaluates several maze generation algorithms applied to generate mazes in a game-based Android mobile application designed to support children in learning basic programming concepts and computational thinking. Each algorithm is assessed for its ability to generate solvable and educationally effective mazes, varying in complexity and size. Key findings indicate that Wilson’s and Aldous–Broder algorithms were identified as the most time inefficient. In comparison, Sidewinder and Binary Tree algorithms perform best for smaller mazes due to their straightforward traversal methods. The Hunt-and-Kill and Recursive backtracker algorithms maintain higher ratios of longest paths, making them suitable for the more complex maze generation required for advanced game levels. Additionally, the study explores various maze-solving algorithms, highlighting the efficiency of the recursive algorithm for simpler mazes and the reliability of Dijkstra’s algorithm across diverse maze structures. This research underscores the importance of selecting appropriate maze generation and solving algorithms to balance generation speed, path complexity, and navigational characteristics. While the study demonstrates the practical applicability of these algorithms in a mobile educational application, it also identifies limitations and suggests directions for future research.

This paper presents a solution for upgrading a previous device model to an Industry 4.0 smart device, with the goal of maintaining high compatibility. A novel IoT architecture is presented that satisfies the characteristics of a smart device. We analysed existing IoT architectures and proposed a new architecture to achieve long-term security and usability. To ensure long-term security, we eliminated the possibility of device configuration outside the immediate vicinity of the device with a dedicated protocol. The security concepts of the existing architectures were also analysed and further modified. To improve compatibility with previous device models, we propose a new method to collect data from sensors by introducing a multithreaded microcontroller. We propose additional software components to ensure factory programming, maintenance, and cloud Big Data analysis. Based on our experiments, we adapted the algorithm to increase the accuracy of the temperature and flow sensors by using a temperature calibration device and known flow cycles. Measurement results are presented to confirm the successful upgrade. We designed a hardware architecture to ensure compatibility with previous and future device models. Issues with previous sensors encountered during the upgrade were discussed and resolved. A novel software architecture based on security for long-term IoT devices is proposed.

Botnets are considered as the primary threats on the Internet and there have been many research efforts to detect and mitigate them. Today, Botnet uses a DNS technique fast-flux to hide malware sites behind a constantly changing network...