No abstract

-Smart homes have become increasingly popular for IoT products and services with a lot of promises for improving the quality of life of individuals. Nevertheless, the heterogeneous, dynamic, and Internet-connected nature of this environment adds new concerns as private data becomes accessible, often without the householders' awareness. This accessibility alongside with the rising risks of data security and privacy breaches, makes smart home security a critical topic that deserves scrutiny. In this paper, we present an overview of the privacy and security challenges directed towards the smart home domain. We also identify constraints, evaluate solutions, and discuss a number of challenges and research issues where further investigation is required.

No abstract

Abstract. We describe a decentralized system consisting of a collection of software agents that monitor and control an office building. It uses the existing power lines for communication between the agents and the electrical devices of the building, such as sensors and actuators for lights and heating. The objectives are both energy saving and increasing customer satisfaction through value added services. Results of qualitative simulations and quantitative analysis based on thermodynamical modeling of an office building and its staff using four different approaches for controlling the building indicate that significant energy savings can result from using the agent-based approach. The evaluation also shows that customer satisfaction can be increased in most situations. The approach here presented makes it possible to control the trade-off between energy saving and customer satisfaction (and actually increase both, in comparison with current approaches).

When planning interventions to limit the spread of Covid-, the current state of knowledge about the disease and specific characteristics of the population need to be considered. Simulations can facilitate policy making as they take prevailing circumstances into account. Moreover, they allow for the investigation of the potential e ects of di erent interventions using an artificial population. Agent-based Social Simulation (ABSS) is argued to be particularly useful as it can capture the behavior of and interactions between individuals. We performed a systematic literature review and identified articles that describe ABSS of Covid-transmission processes. Our review showed that ABSS is widely used for investigating the spread of Covid-. Existing models are very heterogeneous with respect to their purpose, the number of simulated individuals, and the modeled geographical region, as well as how they model transmission dynamics, disease states, human behavior, and interventions. To this end, a discrepancy can be identified between the needs of policy makers and what is implemented by the simulation models. This also includes how thoroughly the models consider and represent the real world, e.g. in terms of factors that a ect the transmission probability or how humans make decisions. Shortcomings were also identified in the transparency of the presented models, e.g. in terms of documentation or availability, as well as in their validation, which might limit their suitability for supporting decision-making processes. We discuss how these issues can be mitigated to further establish ABSS as a powerful tool for crisis management.

We present the Transportation And Production Agent-based Simulator (TAPAS), which is an agent-based model for simulation of transport chains that can be used, e.g., for analysis of transport-related policy and infrastructure measures. TAPAS is more powerful than traditional approaches to freight transport analysis, as it explicitly models production and customer demand, and it captures the interaction between individual transport chain actors, their heterogeneity and decision making processes, as well as time aspects. Whereas traditional approaches rely on assumed statistical correlation, TAPAS relies on causality, i.e., the focus is on the decisions and negotiations that lead to activities. TAPAS is composed of two connected layers, one that simulates the physical activities, e.g., production and transportation, and one that simulates the decision making and interaction between actors. We illustrate TAPAS with a scenario in which the consequences of three transport policy and infrastructure measures are studied.

Abstract-The Internet of Things (IoT) has a great potential to change our lives. Billions of heterogeneous, distributed, intelligent, and sometimes mobile devices, will be connected and offer new types of applications and ways to interact. The dynamic environment of the IoT, the involvement of the human in the loop, and the runtime interactions among devices and applications, put additional requirements on the systems' architecture. In this paper, we use the Emergent Configurations (ECs) concept as a way to engineer IoT systems and propose an architecture for ECs. More specifically, we discuss (i) how connected devices and applications form ECs to achieve users goals and (ii) how applications are run and adapted in response to runtime context changes including, e.g., the sudden unavailability of devices, by exploiting the Smart Meeting Room case.

No abstract