Applications of AI and Data Engineering in Science

Dear Colleagues,

Since around the middle of the last decade, artificial intelligence has emerged as one of the scientific subfields with the most rapid rate of advancement. However, while many researchers see this as an enormous opportunity for ever-faster product development, lower product manufacturing costs, and increased production efficiency, others are concerned about the possibility of massive layoffs and dependence on technologies, or even the possibility of people who are in possession of intelligent technologies seizing control of the entire world. Whoever is correct, one thing is certain: there is no turning back from the application of artificial intelligence to the majority of firms in the economy. This cannot be changed. A large amount of data on the execution of business processes in an organization are amassed as a result of the routine operational activities that take place in IT systems. In most cases, these are just logs, which certify the arrival of items or the starting up of machinery, as well as the time that employees clock in or leave. The use of such data is now feasible as a result of the development of algorithms. The use of algorithms enables the automatic identification of the process that is being carried out, as well as the analysis of that process. It enables the identification of bottlenecks, duplicate processes, and actions, as well as how the actual tasks completed in a corporation vary from those specified in authorized procedures, among other things. The dawn of the age of artificial intelligence heralds an increase in production and creativity. Artificial intelligence raises the bar in terms of speed, adaptability, and optimization. However, the most important fact is that businesses that automate their processes will gain a competitive advantage over their rivals and will maintain their position as market leaders in order to meet the ever-increasing expectations of their customers. This will be the case because these businesses will be able to meet their customers' needs more effectively.

Finally, I would like to thank Dr. Laith Baniata, Dr. Sulieman Ahmad Bani-Ahmad, Dr. Zoltán GÁL and their valuable work for assisting me with this Special Issue.

Dr. Fabrizio Marozzo
Guest Editor

Dr. Ashraf ALDabbas
Guest Editor Assistant

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• remote sensing
• Internet of Things
• artificial intelligence (AI)
• cloud computing
• big data
• knowledge representation