Tools for distributed application management

Distributed application management consists of monitoring and controlling an application as it executes in a distributed environment. It encompasses such activities as configuration, initialization, performance monitoring, resource scheduling, and failure response. The Meta system is described: a collection of tools for constructing distributed application management software. Meta provides the mechanism, while the programmer specifies the policy for application management. The policy is manifested as a control program which is a soft real time reactive program. The underlying application is instrumented with a variety of built-in and user defined sensors and actuators. These define the interface between the control program and the application. The control program also has access to a database describing the structure of the application and the characteristics of its environment. Some of the more difficult problems for application management occur when pre-existing, nondistributed programs are integrated into a distributed application for which they may not have been intended. Meta allows management functions to be retrofitted to such programs with a minimum of effort

Computational sensor networks

technical reportWe propose Computational Sensor Networks as a methodology to exploit models of physical phenomena in order to better understand the structure of the sensor network. To do so, it is necessary to relate changes in the sensed variables (e.g., temperature) to the aspect of interest in the sensor network (e.g., sensor node position, sensor bias, etc.), and to develop a computational method for its solution. As examples, we describe the use of the heat equation to solve (1) the sensor localization problem, and (2) the sensor bias problem. Simulation and physical experiments are described

Instrumented sensor system - practice

technical reportIn previous work, we introduced the notion of Instrumented Logical Sensor Systems (ILSS) that are derived from a modeling and design methodology [4, 2]. The instrumented sensor approach is based on a sensori-computational model which defines the components of the sensor system in terms of their functionality, accuracy, robustness and efficiency. This approach provides a uniform specification language to define sensor systems as a composition of smaller, predefined components. From a software engineering standpoint, this addresses the issues of modularity, reusability, and reliability for building complex multisensor systems. In this report, we demonstrate the practicality of this approach and discuss several design and implementation aspects in the context of mobile robot applications

FES-UPP: A Flexible Functional Electrical Stimulation System to Support Upper Limb Functional Activity Practice

There is good evidence supporting highly intensive, repetitive, activity-focused, voluntary-initiated practice as a key to driving recovery of upper limb function following stroke. Functional electrical stimulation (FES) offers a potential mechanism to efficiently deliver this type of therapy, but current commercial devices are too inflexible and/or insufficiently automated, in some cases requiring engineering support. In this paper, we report a new, flexible upper limb FES system, FES-UPP, which addresses the issues above. The FES-UPP system consists of a 5-channel stimulator running a flexible FES finite state machine (FSM) controller, the associated setup software that guides therapists through the setup of FSM controllers via five setup stages, and finally the Session Manager used to guide the patient in repeated attempts at the activities(s) and provide feedback on their performance. The FSM controller represents a functional activity as a sequence of movement phases. The output for each phase implements the stimulations to one or more muscles. Progression between movement phases is governed by user-defined rules. As part of a clinical investigation of the system, nine therapists used the FES-UPP system to set up FES-supported activities with twenty two patient participants with impaired upper-limbs. Therapists with little or no FES experience and without any programming skills could use the system in their usual clinical settings, without engineering support. Different functional activities, tailored to suit the upper limb impairment levels of each participant were used, in up to 8 sessions of FES-supported therapy per participant. The efficiency of delivery of the therapy using FES-UPP was promising when compared with published data on traditional face-face therapy. The FES-UPP system described in this paper has been shown to allow therapists with little or no FES experience and without any programming skills to set up state-machine FES controllers bespoke to the patient’s impairment patterns and activity requirements, without engineering support. The clinical results demonstrated that the system can be used to efficiently deliver high intensity, activity-focused therapy. Nevertheless, further work to reduce setup time is still required

An automatic visual analysis system for tennis

This article presents a novel video analysis system for coaching tennis players of all levels, which uses computer vision algorithms to automatically edit and index tennis videos into meaningful annotations. Existing tennis coaching software lacks the ability to automatically index a tennis match into key events, and therefore, a coach who uses existing software is burdened with time-consuming manual video editing. This work aims to explore the effectiveness of a system to automatically detect tennis events. A secondary aim of this work is to explore the bene- fits coaches experience in using an event retrieval system to retrieve the automatically indexed events. It was found that automatic event detection can significantly improve the experience of using video feedback as part of an instructional coaching session. In addition to the automatic detection of key tennis events, player and ball movements are automati- cally tracked throughout an entire match and this wealth of data allows users to find interesting patterns in play. Player and ball movement information are integrated with the automatically detected tennis events, and coaches can query the data to retrieve relevant key points during a match or analyse player patterns that need attention. This coaching software system allows coaches to build advanced queries, which cannot be facilitated with existing video coaching solutions, without tedious manual indexing. This article proves that the event detection algorithms in this work can detect the main events in tennis with an average precision and recall of 0.84 and 0.86, respectively, and can typically eliminate man- ual indexing of key tennis events

Semi-automatic semantic enrichment of raw sensor data

One of the more recent sources of large volumes of generated data is sensor devices, where dedicated sensing equipment is used to monitor events and happenings in a wide range of domains, including monitoring human biometrics. In recent trials to examine the effects that key moments in movies have on the human body, we fitted fitted with a number of biometric sensor devices and monitored them as they watched a range of dierent movies in groups. The purpose of these experiments was to examine the correlation between humans' highlights in movies as observed from biometric sensors, and highlights in the same movies as identified by our automatic movie analysis techniques. However,the problem with this type of experiment is that both the analysis of the video stream and the sensor data readings are not directly usable in their raw form because of the sheer volume of low-level data values generated both from the sensors and from the movie analysis. This work describes the semi-automated enrichment of both video analysis and sensor data and the mechanism used to query the data in both centralised environments, and in a peer-to-peer architecture when the number of sensor devices grows to large numbers. We present and validate a scalable means of semi-automating the semantic enrichment of sensor data, thereby providing a means of large-scale sensor management

Tools for distributed application management

Distributed application management consists of monitoring and controlling an application as it executes in a distributed environment. It encompasses such activities as configuration, initialization, performance monitoring, resource scheduling, and failure response. The Meta system (a collection of tools for constructing distributed application management software) is described. Meta provides the mechanism, while the programmer specifies the policy for application management. The policy is manifested as a control program which is a soft real-time reactive program. The underlying application is instrumented with a variety of built-in and user-defined sensors and actuators. These define the interface between the control program and the application. The control program also has access to a database describing the structure of the application and the characteristics of its environment. Some of the more difficult problems for application management occur when preexisting, nondistributed programs are integrated into a distributed application for which they may not have been intended. Meta allows management functions to be retrofitted to such programs with a minimum of effort

Operational Data Framework for Safety Instrumented Systems : A Case Study in Functional Safety and Reliability

In various industries, companies are adopting functional safety measures to address safety concerns, adhere to standards, and manage complex systems. This research is focused on ensuring the reliable operation of Safety Instrumented Systems (SISs) by emphasizing the reliability data. The study examines methodologies for collecting data, classifying failures, mitigating risks, and complying with international safety standards. Through a case study in the energy and marine power industry, a theoretical framework is developed to utilize operational data for assessing SIS performance in the form of a new Engine Safety System (ESS). By complying with IEC standards 61508 and 61511 and incorporating the framework into the ESS's Functional Safety Management Plan, the research addresses key challenges such as data collection, failure analysis, and performance verification. The primary research questions involve determining the type of data to be collected and establishing guidelines for analysing and evaluating that data. A mixed method approach is chosen, with a greater emphasis on qualitative aspects due to the nature of interpreting standards and establishing procedures. The developed framework is presented using tables that outline the required data inputs for reporting actual demands, spurious trips, failures of other barriers, and SIS element failures. Failure report templates are provided, emphasizing the importance of identifying root causes and categorizing failures into Safe or Dangerous failures, as well as Undetected or Detected. The reliability assessment involves comparing actual performance data against the criteria defined in the Safety Integrity Requirements that have been established for the SIS, based on the outcome of the risk assessment. Different risk assessment techniques, such as Layer of Protection Analysis, Fault tree analysis, and risk matrices, are presented in this context, while key performance indicators like demand rates and failure rates are explored to highlight their role in verifying SIS performance. The established framework, designed for the ESS to execute safety functions at Safety Integrity Level 2, is versatile and can serve as a robust foundation for the development of future Functional Safety projects within the organisation and can be applied to other SISs with different Safety Integrity level targets. The study concludes by addressing challenges associated with reliability and various data sources, such as human error and lack of functional safety training, emphasizing the significance of comprehending functional safety when operating with data of SISs