Abstract
Emerging applications of IoT (the Internet of Things), such as smart transportation, health, and energy, are envisioned to greatly enhance the societal infrastructure and quality of life of individuals. In such innovative IoT applications, cost-efficient real-time decision-making is critical to facilitate, for example, effective transportation management and healthcare. In this paper, we formally define real-time decision tasks in IoT, review cutting-edge approaches that aim to efficiently schedule real-time decision tasks to meet their timing and data freshness constraints, review state-of-the-art approaches for efficient sensor data analytics in IoT, and discuss future research directions.
Highlights
IntroductionIn the presence of alternative actions, a real-time decision-maker needs to select one of them that is currently feasible within decision-making deadlines using fresh sensor data that represent the current real-world status to minimize, for example, traffic congestion or mortality in an emergency department
We focus on event-driven sensing and data analysis for efficient real-time decision making based on the ECA (Event-Condition-Action) model depicted in Figure 1 using IoT devices equipped with sensors and a wireless communication module
We summarize the relative advantages and disadvantages of sensor data analytics in IoT devices, at the network edge, and the cloud in Table 1, and discuss them in the following
Summary
In the presence of alternative actions, a real-time decision-maker needs to select one of them that is currently feasible within decision-making deadlines using fresh sensor data that represent the current real-world status to minimize, for example, traffic congestion or mortality in an emergency department. We review cutting-edge research on efficient real-time decision support by analyzing logic predicates in a timely fashion using fresh sensor data in IoT. A set of pioneering works, such as [8,12,13,22,23,24], has been done to efficiently support real-time decision-making in IoT using fresh sensor data They aim to efficiently evaluate logic predicates that model alternative courses of action [8,12,13].
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