GridRM: an extensible resource monitoring system

GridRM is an open and extensible resource monitoring system, based on the Global Grid Forum's Grid Monitoring Architecture (GMA). GridRM is not intended to interact with applications; rather it is designed to monitor the resources that an application may use. This paper focuses on the dynamic driver infrastructure used by GridRM to interact with heterogeneous data sources, such as SNMP or Ganglia agents, and how it provides a homogeneous view of the underlying heterogeneous data. This paper discusses the local infrastructure and details work implementing and deploying a number of drivers.

The water quality of the River Enborne, UK: observations from high-frequency Monitoring in a rural, lowland river system

This paper reports the results of a 2-year study of water quality in the River Enborne, a rural river in lowland England. Concentrations of nitrogen and phosphorus species and other chemical determinands were monitored both at high-frequency (hourly), using automated in situ instrumentation, and by manual weekly sampling and laboratory analysis. The catchment land use is largely agricultural, with a population density of 123 persons km−2. The river water is largely derived from calcareous groundwater, and there are high nitrogen and phosphorus concentrations. Agricultural fertiliser is the dominant source of annual loads of both nitrogen and phosphorus. However, the data show that sewage effluent discharges have a disproportionate effect on the river nitrogen and phosphorus dynamics. At least 38% of the catchment population use septic tank systems, but the effects are hard to quantify as only 6% are officially registered, and the characteristics of the others are unknown. Only 4% of the phosphorus input and 9% of the nitrogen input is exported from the catchment by the river, highlighting the importance of catchment process understanding in predicting nutrient concentrations. High-frequency monitoring will be a key to developing this vital process understanding.

An enhanced fall detection system for elderly person monitoring using consumer home networks

Various fall-detection solutions have been previously proposed to create a reliable surveillance system for elderly people with high requirements on accuracy, sensitivity and specificity. In this paper, an enhanced fall detection system is proposed for elderly person monitoring that is based on smart sensors worn on the body and operating through consumer home networks. With treble thresholds, accidental falls can be detected in the home healthcare environment. By utilizing information gathered from an accelerometer, cardiotachometer and smart sensors, the impacts of falls can be logged and distinguished from normal daily activities. The proposed system has been deployed in a prototype system as detailed in this paper. From a test group of 30 healthy participants, it was found that the proposed fall detection system can achieve a high detection accuracy of 97.5%, while the sensitivity and specificity are 96.8% and 98.1% respectively. Therefore, this system can reliably be developed and deployed into a consumer product for use as an elderly person monitoring device with high accuracy and a low false positive rate.

A real-time measurement system for long-life flood monitoring and warning applications

A flood warning system incorporates telemetered rainfall and flow/water level data measured at various locations in the catchment area. Real-time accurate data collection is required for this use, and sensor networks improve the system capabilities. However, existing sensor nodes struggle to satisfy the hydrological requirements in terms of autonomy, sensor hardware compatibility, reliability and long-range communication. We describe the design and development of a real-time measurement system for flood monitoring, and its deployment in a flash-flood prone 650 km2 semiarid watershed in Southern Spain. A developed low-power and long-range communication device, so-called DatalogV1, provides automatic data gathering and reliable transmission. DatalogV1 incorporates self-monitoring for adapting measurement schedules for consumption management and to capture events of interest. Two tests are used to assess the success of the development. The results show an autonomous and robust monitoring system for long-term collection of water level data in many sparse locations during flood events.

A novel satellite-based ocean monitoring system for Mexico

To analyze patterns in marine productivity, harmful algal blooms, thermal stress in coral reefs, and oceanographic processes, optical and biophysical marine parameters, such as sea surface temperature, and ocean color products, such as chlorophyll-a concentration, diffuse attenuation coefficient, total suspended matter concentration, chlorophyll fluorescence line height, and remote sensing reflectance, are required. In this paper we present a novel automatic Satellite-based Ocean Monitoring System (SATMO) developed to provide, in near real-time, continuous spatial data sets of the above-mentioned variables for marine-coastal ecosystems in the Gulf of Mexico, northeastern Pacific Ocean, and western Caribbean Sea, with 1 km spatial resolution. The products are obtained from Moderate Resolution Imaging Spectroradiometer (MODIS) images received at the Direct Readout Ground Station (located at CONABIO) after each overpass of the Aqua and Terra satellites. In addition, at the end of each week and month the system provides composite images for several ocean products, as well as weekly and monthly anomaly composites for chlorophyll-a concentration and sea surface temperature. These anomaly data are reported for the first time for the study region and represent valuable information for analyzing time series of ocean color data for the study of coastal and marine ecosystems in Mexico, Central America, and the western Caribbean.

Monitoring results of combined pellet and solar heating system

In this study the monitoring results of prototype installation of a recently developed solar combisystem have been evaluated. The system, that uses a water jacketed pellet stove as auxiliary heater, was installed in a single family house in Borlänge/Sweden. In order to allow an evaluation under realistic conditions the system has been monitored for a time period of one year. From the measurements of the system it could be seen that it is important that the pellet stove has a sufficient buffer store volume to minimize cycling. The measurements showed also that the stove gives a lower share of the produced heat to the water loop than measured under stationary conditions. The solar system works as expected and covers the heat demand during the summer and a part of the heat demand during spring and autumn. Potential for optimization exists for the parasitic electricity demand. The system consumes 680 kWh per year for pumps, valves and controllers which is more than 4% of the total primary heating energy demand.

A user guide to simple monitoring and sustainable operation of PV-diesel hybrid systems : Handbook for system users and operators

This report contains a suggestion for a simple monitoring and evaluation guideline for PV-diesel hybrid systems. It offers system users a way to better understand if their system is operated in a way that will make it last for a long time. It also gives suggestions on how to act if there are signs of unfavourable use or failure. The application of the guide requires little technical equipment, but daily manual measurements. For the most part, it can be managed by pen and paper, by people with no earlier experience of power systems.The guide is structured and expressed in a way that targets PV-diesel hybrid system users with no, or limited, earlier experience of power engineering. It is less detailed in terms of motivations for certain choices and limitations, but rich in details concerning calculations, evaluation procedures and maintenance routines. A more scientific description of the guide can be found in a related journal article.

On-line tool condition monitoring and control system in forging processes

Cold bulk metal forming has made large-scale production of small complex solid parts economically feasible. Tooling used in metal forming poses many uncertainties in the preliminary cost estimation and production process and continual tool replacement and maintenance dramatically reduces productivity and raises manufacturing cost. In order to tackle this, an on-line tool condition monitoring system using artificial neural network (ANN) to integrate information from multiple sensors for forging process has been developed. Together with the force, acoustic emission signals and process conditions, information developed from theoretical models is integrated into the ANN tool monitoring system to predict tool life and provide the maintenance schedule.

An intelligent forex monitoring system

The need for intelligent monitoring systems has become a necessity to keep track of the complex forex market. The vast currency market is a foreign concept to the average individual. However, once it is broken down into simple terms, the average individual can begin to understand the foreign exchange market and use it as a financial instrument for future investing. We attempt to compare the performance of a Takagi-Sugeno, type neuro-fuzzy system and a feedforward neural network trained using the scaled conjugate gradient algorithm to predict the average monthly forex rates. We considered the exchange values of Australian dollar with respect to US dollar, Singapore dollar, New Zealand dollar, Japanese yen and United Kingdom pounds. The connectionist models were trained using 70% of the data and remaining was used for testing and validation purposes. It is observed that the proposed connectionist models were able to predict the average forex rates one month ahead accurately. Experiment results also reveal that the neuro-fuzzy technique performed better than the neural network