Using IoT and Mobile Robots to Model and Analyze Work Processes with Process Mining Techniques

Abstract

This research explores the practical application of Internet of Things (IoT) technology using mobile robots to collect and store data from their surroundings, including personal information from wearables on cloud systems. It then employs process mining techniques to analyze these raw data. There are three main processes. These processes are 1) Understanding the fundamental concepts of IoT, developing mobile robots, and learning about process mining principles. 2) Creating a system for storing data or event logs generated by IoT devices and mobile robots. 3) Analyzing the collected data using process mining techniques. Through this method, we can learn in-depth about the activities of an individual user. Therefore, the proposed method is an extension of the IoT system for increasing the performance of decision support systems and automated decision systems in real-world applications. Furthermore, the research showcases how services, particularly robots, can be accessed through the Fuzzy Miner model. These methods have practical applications in real-world scenarios, such as human-robot collaboration, inventory management, service tracking, supply chain management, retail, logistics, healthcare, transportation, agriculture, and manufacturing.