The purpose of the study was to design a device for the dissolution of fertilizers for agricultural use in an automatic and environmentally sustainable way to facilitate the work of farmers. To achieve this goal, an outdated blade design was used, which generates turbulent and laminar flows thanks to the angle of inclination of its blades. In tests, the combination of these two flows gave a better result compared to laminar and turbulent flows separately. The best results were achieved by varying the spin and speed, the time between spins, and the rest time. The time it would take to dissolve the mixture was drastically reduced if it were conducted in the traditional way (manually) or compared with commercial mixers. In conclusion, the technique used for the dissolution of agricultural minerals is more effective and reduces time, energy, and effort. This was able to reduce the time necessary to dissolve the fertilizer by 93 percent compared to doing it manually and by 66 percent compared to using commercial mixers, in a solution of 100 L of water per 100 kg of ammonium sulfate.

In the current digital landscape, artificial intelligence-driven automation has revolutionized efficiency in various areas, enabling significant time and resource savings. However, the reliability and efficiency of software systems remain crucial challenges. To address this issue, a generation of self-adaptive software has emerged with the ability to rectify errors and autonomously optimize performance. This study focuses on the development of self-adaptive software designed for pre-programmed tasks on the Internet. The software stands out for its self-adaptation, automation, fault tolerance, efficiency, and robustness. Various technologies such as Python, MySQL, Firebase, and others were employed to enhance the adaptability of the software. The results demonstrate the effectiveness of the software, with a continuously growing self-adaptation rate and improvements in response times. Probability models were applied to analyze the software’s effectiveness in fault situations. The implementation of virtual cables and multiprocessing significantly improved performance, achieving higher execution speed and scalability. In summary, this study presents self-adaptive software that rectifies errors, optimizes performance, and maintains functionality in the presence of faults, contributing to efficiency in Internet task automation.