An event driven framework for assistive CPS environments

Makedon, Fillia; Le, Zhengyi; Huang, Heng; Becker, Eric; Kosmopoulos, Dimitrios

doi:10.1145/1859823.1859826

Cited by 19 publications

(7 citation statements)

References 27 publications

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“…The authors suggest that the degradation of the system state could potentially be used to detect failures. Makedon et al [2009] design an event-driven framework for assistant CPS environments. The event is modeled as the abnormal behavior of the system, such as accidents or acute needs.…”

Section: Trustworthiness Analysis In Cpsmentioning

confidence: 99%

“…As mentioned in Johnson and Mitra [2009], the complexity of this problem is the main challenge. Some studies use the strategies of abstraction and generalization to reduce the influences of false alarms [Ganti et al 2008] or to detect untrustworthy data by performance degradation of the system [Makedon et al 2009]. However, most works only propose such strategies as research directions and do not have detailed solutions.…”

Section: Trustworthiness Analysis In Cpsmentioning

confidence: 99%

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A Framework of Mining Trajectories from Untrustworthy Data in Cyber-Physical System

Tang

et al. 2015

ACM Trans. Knowl. Discov. Data

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A cyber-physical system (CPS) integrates physical (i.e., sensor) devices with cyber (i.e., informational) components to form a context-sensitive system that responds intelligently to dynamic changes in real-world situations. The CPS has wide applications in scenarios such as environment monitoring, battlefield surveillance, and traffic control. One key research problem of CPS is called mining lines in the sand. With a large number of sensors (sand) deployed in a designated area, the CPS is required to discover all trajectories (lines) of passing intruders in real time. There are two crucial challenges that need to be addressed: (1) the collected sensor data are not trustworthy, and (2) the intruders do not send out any identification information. The system needs to distinguish multiple intruders and track their movements. This study proposes a method called LiSM (Line-in-the-Sand Miner) to discover trajectories from untrustworthy sensor data. LiSM constructs a watching network from sensor data and computes the locations of intruder appearances based on the link information of the network. The system retrieves a cone model from the historical trajectories to track multiple intruders. Finally, the system validates the mining results and updates sensors' reliability scores in a feedback process. In addition, LoRM (Line-on-the-Road Miner) is proposed for trajectory discovery on road networks-mining lines on the roads. LoRM employs a filtering-and-refinement framework to reduce the distance computational overhead on road networks and uses a shortest-path-measure to track intruders. The proposed methods are evaluated with extensive experiments on big datasets. The experimental results show that the proposed methods achieve higher accuracy and efficiency in trajectory mining tasks.

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Section: Trustworthiness Analysis In Cpsmentioning

confidence: 99%

Section: Trustworthiness Analysis In Cpsmentioning

confidence: 99%

A Framework of Mining Trajectories from Untrustworthy Data in Cyber-Physical System

Tang

et al. 2015

ACM Trans. Knowl. Discov. Data

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“…A major concern in an assistive environment like the one we propose is how to transform the low-level signals to semantic knowledge and use it to identify security and safety events [19] [20]. Firstly given the sensor data the target has to be located, and then the behaviors have to be recognized.…”

Section: Noninvasive Activity Recognitionmentioning

confidence: 99%

Human centered computing for the development of assistive environments

Maglogiannis

2014

Proceedings of the 7th International Conference on PErvasive Technologies Related to Assistive Environments

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The paper presents the research conducted within the framework of the STHENOS project (www.sthenos.gr), which aims at the development of methodologies and systems for assistive environments. The research within the project aims at the development of methodologies and tools to compose pervasive human-centered systems, which will be able to understand the human state (identity, emotions and behavior) in assistive environments using audiovisual and biological signals. The proposed systems and applications are capable of offering services such as support for the aged/disabled/chronic patients, detection of critical situations from audiovisual content, biosignal and neurophysiology analysis for the detection of pathology (e.g. Alzheimer's disease), as well as for treatment follow-up. The paper includes an overview of the three perspectives of human centered computing studied in the STHENOS project, namely: audiovisual activity and status recognition, affective computing and neurophysiological analysis.

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“…In our assistive testbed experiments [9][10][11][12], we assume an apartment with sensor nodes located in various rooms and covering areas where human monitoring needs to take place. We use Sunspot wireless sensor nodes to monitor certain human activities, such as opening a door, getting onto bed, and passing through a hallway.…”

Section: Assistive Testbedmentioning

confidence: 99%

Modeling reliability for wireless sensor node coverage in assistive testbeds

Becker

Konstantinides

et al. 2010

Proceedings of the 3rd International Conference on PErvasive Technologies Related to Assistive Environments

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Wireless Sensor Networks (WSNs) is a prevailing technology in assistive environments. Assistive environments may include both home and work spaces such as factories, military installations, industrial spaces, and offices. Critical quality-of-service properties of WSN are reliability, availability, and serviceability. This paper focuses on reliability for healthcare applications. Reliable WSN-based monitoring services can prevent accidents, improve the quality of life, and even help with early health diagnosis and treatments. However, because patients/the elderly may have cognitive or other health problems, the reliability is the dominant factor of quality of services of WSN. This paper presents an approach to analyze the reliability of a WSN with the most popular tree structures. The analysis is based on two distribution models, exponential distribution and Weibull distribution. The simulation results also give options to users on the cost vs. reliability issue.

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An event driven framework for assistive CPS environments

Cited by 19 publications

References 27 publications

A Framework of Mining Trajectories from Untrustworthy Data in Cyber-Physical System

A Framework of Mining Trajectories from Untrustworthy Data in Cyber-Physical System

Human centered computing for the development of assistive environments

Modeling reliability for wireless sensor node coverage in assistive testbeds

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