# Process Automation in an IoT-Fog-Cloud Ecosystem: A Survey and Taxonomy
## 1 Introduction  
Connecting various objects to the Internet has created a significant shift in the information-based economy. The flow of information will play a crucial role in future Information Technology (IT) ecosystems [1]. The connectivity of different types of objects, sensors, and end devices to the Internet is known as the Internet of Things (IoT). The expected large number of sensors connecting to the Internet will cause severe issues for IoT task management, data process, and decision-making systems. Because providing the same services to the users will face latency in data management and data processing of IoT sensors. Therefore, ensuring a good Quality-of-Service (QoS) with a low-latency resolution for IoT applications, IT services, user tasks, and client events in the ecosystem is crucial to support latency-aware real-time applications. [PERSON] and [PERSON] [2] show that the evolution of industrial production has occurred in four stages culminating in the IoT: (1) mechanization and the invention of the steam engine and water power, (2) mass production and assembly lines, (3) the computer and automation processing, (4) the Internet of Things (IoT), (5) the collaboration between man and machine in industry and robotic tasks conversion. These stages are referred to as Industry 1.0, Industry 2.0, Industry 3.0, Industry 4.0, and Industry 5.0. [PERSON] [3] describes that the advantage of the industrial Internet is to advance the management of value chains. Digitalization and interconnection are essential benefits provided by Industry 4.0. In addition to management, advanced computation, and intelligent decision making, IoT will provide us with control over the entirety of any process, such as the life cycle of products. [PERSON] et al. [4] depicts an example of industry 4.0 in supply chain management and asset monitoring. [PERSON] and [PERSON] [5] demonstrates another example of industry 4.0 in the optimization of pasta line production. The IoT sensors monitor and track the workflow tasks, and industry 5.0 is also added for double-checking of the production with image processing. Cloud computing is a global infrastructure environment that provides sophisticated resources for tasks and IT services. Google Drive, Dropbox, and Microsoft Azure are examples of Cloud computing. [PERSON] et al. [6] demonstrates a comprehensive framework of Cloud Computing according to its tools, models, structure, and methods. [PERSON] et al. [7] states in 2018 that 50 billion IoT devices will be connected to the Internet by 2020. According to their statement and now that we are in 2021, we should have faced more than 50 billion IoT devices, which continuously generate data. High latency is the reason that Cloud Computing cannot be employed for processing the generated data. Therefore, Cloud Computing is not an efficient solution for hosting IoT applications and data processing. [PERSON] [8] defines automation and automatic processes in industry. By the definition, automation is any task, method, technique, algorithm, process, and control, which can minimize human intervention and assistance. The significant advantage of automatic processes is to minimize latency in any points, where human decision-making is required and tasks are interrupted when human actions are still not made. When more devices and IoT sensors are joining the ecosystem, defining and designing automatic components for data process and task management of such massive IoT data is essential and pertinent. Since Cloud Computing suffers from high latency, and many IoT applications need on-demand processing and real-time decision making, relying on the Cloud is not a suitable solution. Additionally, the real-time and time-sensitive characteristics of Industry 4.0 IoT applications make the Cloud an unsuitable option for their hosting. Hence, data processing in the Fog environment is a preferable solution. Fog computing, a term first used by Cisco, evolves the Cloud to an extent close to end-devices and users to host the time-sensitive applications [9].