4.8 Article

A Novel Spatial-Temporal Specification-Based Monitoring System for Smart Cities

期刊

IEEE INTERNET OF THINGS JOURNAL
卷 8, 期 15, 页码 11793-11806

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2021.3069943

关键词

Monitoring; Smart cities; Safety; Runtime; Intelligent sensors; Tools; Internet of Things; Runtime verification; signal temporal logic (STL); smart cities

资金

  1. National Science Foundation [CCF-1942836, CNS-1952096]
  2. Austrian FFG-Funded IoT4CPS Project at TU Wien

向作者/读者索取更多资源

This article introduces a novel spatial-temporal specification-based monitoring system for smart cities, which develops a new spatial aggregation STL for efficient runtime monitoring of city requirements. Through a study of over 1000 smart city requirements, the article proposes two new logical operators to enhance STL for expressing spatial aggregation and spatial counting characteristics.
With the development of the Internet of Things, millions of sensors are being deployed in cities to collect real-time data. This leads to a need for checking city states against city requirements at runtime. In this article, we develop a novel spatial-temporal specification-based monitoring system for smart cities. We first describe a study of over 1000 smart city requirements, some of which cannot be specified using the existing logic, such as the signal temporal logic (STL) and its variants. To tackle this limitation, we develop spatial aggregation STL (SaSTL)-a novel spatial aggregation STL-for the efficient runtime monitoring of safety and performance requirements in smart cities. We develop two new logical operators in SaSTL to augment STL for expressing spatial aggregation and spatial counting characteristics that are commonly found in real city requirements. We define the Boolean and quantitative semantics for SaSTL in support of the analysis of city performance across different periods and locations. We also develop efficient monitoring algorithms that can check the SaSTL requirement in parallel over multiple data streams (e.g., generated by multiple sensors distributed spatially in a city). Additionally, we build an SaSTL-based monitoring tool to support decision making of different stakeholders to specify and runtime monitor their requirements in smart cities. We evaluate our SaSTL monitor by applying it to three case studies with large-scale real city sensing data (e.g., up to 10 000 sensors in one study). The results show that SaSTL has a much higher coverage expressiveness than other spatial-temporal logics, and with a significant reduction of computation time for monitoring requirements. We also demonstrate that the SaSTL monitor improves the safety and performance of smart cities via simulated experiments.

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