# Modeling Trust in IoT Systems for Drinking-Water Management
## 1 Introduction  
In the context of wastewater treatment plants, trust plays an essential role in guaranteeing the safety of the water supply, which is a fundamental priority. Failures or errors within these infrastructures have significant implications, going beyond mere technical malfunctions, as they can have serious consequences for both water quality and the availability of this vital resource [1]. In a collaborative environment within water-treatment plants, mutual trust between IoT devices, control systems (i.e., electronic and electromechanical components), and skilled personnel becomes pivotal to the operational chain. Maintaining a high level of trust between infrastructure components facilitates smooth coordination, helps to reduce the likelihood of mistakes, and enables rapid and effective response to incidents [2]. Measuring and understanding trust is of strategic importance and extends beyond mere technical performance monitoring. It involves quantifying and analyzing the reliability of human and automated interactions within the system. In this context, trust encompasses predictability, reliability of actions, transparency of communication, and the ability to anticipate the responses of various critical elements in exceptional circumstances. Furthermore, it is imperative for IoT devices and control systems to also demonstrate their trust in human entities (i.e., qualified personnel). This can be achieved by ensuring transparent data communication, providing accurate insights into their operation, and allowing some form of interaction and control from qualified personnel to ensure effective decision-making and proper system management in complex situations. These devices can also be designed to alert qualified personnel of potential issues, therefore indicating trust in the personnel's ability to intervene and resolve issues appropriately. Additionally, control systems can incorporate features enabling human operators to access detailed information about the status of IoT devices and electromechanical components, thus enhancing transparency and collaboration between human entities and automated systems. By building trust within the operational ecosystem, water-treatment plants can mitigate the risk of human or technological failure. High levels of trust foster a culture of safety, where each element of the infrastructure depends on the others to function optimally. This translates into reduced risk of error and downtime, as well as a greater ability to anticipate and mitigate potential problems. Given their role as essential pillars of water safety, water-treatment plants demand unwavering operational integrity, where trust is a critical factor. Failures or errors in this context can have serious repercussions on the safety of the water supply. This study aims to address the imperative need to measure, evaluate, and reinforce trust between various critical elements within water-treatment facilities. While previous research has explored the security of IoT systems in various sectors, one aspect of understanding trust within these facilities has often been overlooked. The limited research that has examined trust has primarily focused on security in the broadest sense, without specifically delving into the collaboration between IoT devices, control systems, and skilled personnel within water-treatment plants [3]. Furthermore, given the rapid evolution of IoT technology and the increasing demands on water management, there is an urgent need to investigate how trust can be maintained and assessed in dynamic environments. The complex interplay between critical elements within this kind of infrastructure requires in-depth examination to understand the emergence and evolution of trust over time [4], which our article aims to address, which our article aims to address by focusing on the key objective of measuring, evaluating, and enhancing trust within water-treatment facilities.