Decision support system (DSS) refers to any tool or task which has the potential to support decision-making activities. Decision making is one of the major and difficult tasks which ultimately results in the success or failure of a system in general and an application in particular. In Internet of Things (IoT), DSS has an immense potential to influence the outcome of various applications. The data streams originating from embedded sensors in various IoT applications, e.g., smart farming, industrial automation, healthcare, etc, need to be assessed in view of the sensitive information present in the data.

The role of DSS has never been as important as today. For example, in healthcare IoT, wearables and other sensors generate a massive amount of physiological data that mandates the use of DSS to obtain useful and deeper insights of the sensed data. In IoT applications, the underlying devices are becoming autonomous and self-aware of the environment. These features make the devices intelligent and capable of making decisions locally to reduce the burden on cloud, edge and fog computing resources.

This Special Issue aims to collect the latest approaches and findings, as well as to discuss the current challenges of decision support system in IoT applications. We welcome high-quality submissions on important tools, approaches, theories, and methods in emerging topics of DSS for the development of intelligent applications in IoT.

Potential topics include but are not limited to the following:

• Managing Information overloading using decision support system for IoT
• Mapping and modelling sensed data with precise application of IoT
• Self-aware configuration and management mechanisms for decision support system in IoT
• Real-time strategies for decision making and action recognition in IoT
• AI-techniques for decision making in IoT
• Interpretable machine learning techniques for decision making in sustainable applications of IoT
• Decision making support for traffic regulation and load balancing in IoT
• Soft computing and data mining approaches for decision support system in IoT
• Issues in deploying decision support systems and soft computing for sustainable development of intelligent applications
• Applications of AI for developing smart and intelligent applications of IoT
• Decision support system for mitigating threats and vulnerabilities in IoT