Anomaly Monitoring Framework Based on Intelligent Data Analysis

Designing a Context-Aware Cyber Physical System for Smart Conditional Monitoring of Platform Equipment

“…The main challenge in developing a CPS is to create an interactive interface between the physical and cyber worlds the role of this interface is to acquire the context information from the physical world and to implement context-aware computing in the cyber world [6]. Figure 1 illustrates a conceptual framework for building context-aware cyber physical systems [9]. Each layer is dedicated to a certain context processing task, ranging from low-level context acquisition up to high level context application using either existing or acquired knowledge.…”

“…An optimal balance needs to be attained between data availability and its quality in order to effectively control the underlying physical processes. Figure 2 illustrates a systematic approach to handling the challenges related to context processing, which has been successfully applied by the authors to various real world applications [8,9]. As can be seen from Figure 2, the suggested approach segregates processing of the input stream into three distinct phases.…”

Intelligent Measurement in Unmanned Aerial Cyber Physical Systems for Traffic Surveillance

“…Due to the nature of UAS operation, the states of many secondary variables reflect the states of primary characteristics. For instance, surveillance data obtained from various sensors can indicate, and even identify, unusual or dangerous behaviour of drivers on the road [6].…”

“…This can further aggravate the lack of training data by the increased likelihood of intermittent anomalies. Computational intelligence techniques that are used to tackle dynamic problems should therefore be able to adapt to environmental/contextual changes [6].…”

“…This type of modelling utilises the computational capabilities of modern computing devices (smart sensors, DSP-based microcontroller, and microprocessors) to effectively process the acquired input and infer the desired information. The AI-based techniques are applicable at various layers of IMS -from the data acquisition (sensor) layer, through to the layer of instrument calibration and customisation, then to the layer of process modelling, control and optimisation, and finally to the knowledge acquisition layer [6]. The wide spectrum of possible applications is due to the capabilities of an IMS to gain insight into the behaviour of complex dynamic systems by means of data-driven modelling, a systematic approach to which is described in this section.…”