Real-time Event Data Research Articles

Multi-stage Monitoring of Abnormal Situation Based on Complex Event Processing

This paper focuses on the monitoring of abnormal situation in workspace where complicate production activities are performed and possible abnormal situations vary in different stages. The monitoring application should track the production process, identifying the production stage and detecting anomaly in every stage as defined. With the development of ubiquitous computing technology and widespread of sensing equipment, context information pertaining to smart working environment is available for monitoring applications. Complex event processing (CEP) is usually introduced to process and correlate context information for its attractive feature of extracting composite event from a large amount of event data in real time according to user-defined event patterns. In this paper, we present context model and event model in which discrete event such as acquiring context value at a point of time is represented by context. The abnormal situation in every stage of production can be transformed into event expressions, called abnormal event patterns. Contexts in different time captured by sensors form data streams and processed by CEP engine to detect abnormal situation. We propose to use state transition to model each stage so that the normal transition period in the beginning and end of stage can be distinguished from abnormal situation. Once a stage is identified to be starting or ending, the application will change abnormal event patterns accordingly. Case study about metallographic examination proves that the approach we propose is effective and feasible for some multi-stage abnormal situation monitoring.

Development of Real-Time Optimal Bus Scheduling and Headway Control Models

Infrequent bus service because of a sudden rise in international gas prices has created a significant social problem in South Korea. Bus service frequency is determined by considering bus operation costs to the service supplier, passenger demand, and so forth. Optimal bus frequency was determined and a timetable for each bus stop was created by applying the DTR (demand- and travel time–responsive) model or the DTRC (demand- and travel time–responsive model for critical scheduling areas); both use data for each bus stop and route segment. A bus headway control model that can monitor and assess punctuality of an operation was also developed. This model was based on real-time event data, such as bus stop departures and arrivals for buses operating on a line-based timetable, constructed for each bus stop. It was also based on the bus stop traffic cost, which was applied in the bus scheduling model. The model's ability to evaluate the punctuality of operation made it possible to transmit headway control instructions (when to decelerate or accelerate) to a bus driver via an onboard unit. A model verification process was implemented by using data collected from a bus management system and integrated transit fare card system for the bus route in Seoul. To evaluate the reliability and uncertainty of the optimal solution, a sensitivity analysis was implemented for the various parameters and assumptions used in the models.

DYNAMIC MANAGEMENT OF PERIOPERATIVE PROCESSES: A MODELING AND VISUALIZATION PARADIGM

Managing workflows for surgical services in large multi-speciality hospitals is a challenging task in part due to intrinsic as well as exogenous uncertainties and disturbances. Models and historical data are used to project utilizations and resource requirements for managing operating rooms (OR) over weeks and months. Such projection methods may be adapted in management decision making on the day of surgery if real-time event data can be obtained. A paradigm was developed to combine modelling, simulation, real-time sensor data processing, and visualization to assist coordination of the activities during perioperative processes.

Development of a System for Collecting Loop-Detector Event Data for Individual Vehicles

Typical freeway inductive loop detection systems, under normal operation, aggregate individual loop-detector actuations sampled at 60 Hz into 20-s or 30-s averages of velocity, flow, and lane-occupancy measurements. While such aggregations are appropriate for serving as inputs to control system algorithms, and they save disk space for archiving loop data, a large amount of useful data regarding individual vehicles is lost. For single-loop detectors, the lost information includes individual vehicle arrival, departure, and presence times. For speed traps, the lost information also includes the calculated individual vehicle speed and length. Yet this information about individual vehicles is desirable to transportation researchers and planners. The unavailability of this information makes in-depth investigation of detector errors difficult or even impossible. A system for collecting detector event data is proposed. This system can sample loop actuations with sampling rates of 60 Hz or higher and then save, process, and present the collected event data in real time without interfering with the detector controller’s normal operation. A stand-alone Windows program was developed for performing real-time high-frequency loop event data collection. A system reliability test and field application indicate that the system can collect realtime detector event data at a high sampling rate (60 Hz or higher). Additionally, this system makes real-time loop data quality evaluation, loop malfunction identification, and loop error correction feasible.

Bandwidth allocation scheme in CAN protocol

The CAN (controller area network) is a serial communication protocol for distributed real-time control and automation systems. Data generated from field devices in manufacturing automation and process control systems are classified into three categories: real-time event data, real-time control data and non-real-time data. These data share a common CAN medium. Unless the traffic of the CAN protocol is efficiently controlled, performance of the real-time application systems interconnected into the CAN bus can be degraded. The paper proposes a bandwidth allocation algorithm that can be applicable to the CAN protocol. The bandwidth allocation algorithm not only satisfies the performance requirement of real-time application systems interconnected into the CAN but also fully utilises the bandwidth of the CAN. The bandwidth allocation algorithm introduced in the paper is validated using a simulation experiment.