Affiliation:
1. GRIC, Sherbrooke University, Sherbrooke, QC J1K 2R1, Canada
2. Data4earth Laboratory, Sultan Moulay Slimane University, Beni Mellal 23000, Morocco
Abstract
This study focuses on trust within water-treatment IoT plants, examining the collaboration between IoT devices, control systems, and skilled personnel. The main aim is to assess the levels of trust between these different critical elements based on specific criteria and to emphasize that trust is neither bidirectional nor transitive. To this end, we have developed a synthetic database representing the critical elements in the system, taking into account characteristics such as accuracy, reliability, and experience. Using a mathematical model based on the (AHP), we calculated levels of trust between these critical elements, taking into account temporal dynamics and the non-bidirectional nature of trust. Our experiments included anomalous scenarios, such as sudden fluctuations in IoT device reliability and significant variations in staff experience. These variations were incorporated to assess the robustness of our approach. The trust levels obtained provide a detailed insight into the relationships between critical elements, enhancing our understanding of trust in the context of water-treatment plants.
Reference42 articles.
1. Brouwer, S., Hofman-Caris, R., and Van Aalderen, N. (2020). Trust in drinking water quality: Understanding the role of risk perception and transparency. Water, 12.
2. Is Trust Always a Precondition for Effective Water Resource Management?;Zhen;Water Resour. Manag.,2020
3. A survey on trust management for Internet of Things;Yan;J. Netw. Comput. Appl.,2014
4. On-line trust: Concepts, evolving themes, a model;Corritore;Int. J. Hum.-Comput. Stud.,2003
5. Xiaocong, M., Jiao, Q.X., and Shaohong, S. (2015, January 26–27). An IoT-based system for water resources monitoring and management. Proceedings of the 2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics, Hangzhou, China.