NodePM: A Remote Monitoring Alert System for Energy Consumption Using Probabilistic Techniques

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Design and implementation of wireless sensor networks for impedance-based structural health monitoring using ZigBee and Global System for Mobile Communications

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Automatic dimming multi-lamp fluorescent management system with active input power factor corrector stage

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Sistema automático para o controle eficiente de iluminação para multiplas lâmpadas fluorescentes

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Metodologia para análise e interpretação de alarmes em tempo real de sistemas de distribuição de energia elétrica

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Aplicação de um sistema de monitoramento remoto para auxiliar na manutenção preditiva e preventiva de componentes de uma subestação

The increase in energy consumption in the world has caused the electrical systems becoming ever larger and more complex. Because of that becomes necessary to use special tools to efficiently manage the equipment present in these systems. Nowadays a tool very used is the remote monitoring of assets which works collecting signals using sensors processing these signals and make them available to the system user. So the user can use informations that may assist him efficiently in making decisions when doing a maintenance. The system is technically efficient since it improves the measurement process and enables the asset management of a substation by using advanced technology for that and economically viable especially in cases where the user is subject to monetary loss due an interruption of power supply

WSPControl: aplicação distribuída baseada em Web Services para monitoramento remoto de computadores

The tool proposed, known as WSPControl, enables remote monitoring of computers across the Internet using distributed applications. Through a Web Services architecture is possible the communication between these distributed applications across heterogeneous platforms, also eliminates the need for additional settings in computer networks, such as release of ports or proxy. The tool is divided into three modules, namely: • Client Interface: developed in C Sharp, is responsible for capturing data on performance of the monitored computer also connects to the Web Services to report this data. • Web Services Interface: developed in PHP using the PHP SOAP library, is responsible for facilitating the communication between internet applications and client. • Internet Interface: developed in PHP, is responsible for reading and interpreting the information captured these available on the Internet

Orientação espacial em pessoas com deficiência visual: um estudo de triangulação por meio de monitoramento remoto

This study was conducted to investigate how visually impaired people perform distance estimation tasks by movement and navigation during deprivation of effective perceptual and proprioceptive information. For that they performed the task of walking three distances, being the first and second of 100 meters and the third of 140 meters (triangulation) from a point of origin in open field on a inverted L shaped trajectory and then returning to the origin. The first and second tasks were driven by means of a guide with GPS adapted to the study coordinates, and the third one was freeform with three sessions, the first without perceptual and proprioceptive restrictions, the second without auditory perception, and the third in a wheelchair, without proprioception. The objective of this study was to indicate the differences in distance reproduction in relation to accuracy and investigate the spatial representation of participants in a navigation task, in which there is active movement, but no effective perceptual and proprioceptive information. Results showed that the average participants underestimated distances producing average angles close to the value of 45°. And by means of the "t" students test no significant differences between subjects can be pointed out. To achieve these results we used remote monitoring by GPS and software TrackMaker.

Tarefas de triangulação com restrições perceptuais em pessoas com deficiência auditiva: um estudo por meio de gps

This study aimed to investigate how people with hearing disability perform tasks of distances estimation for locomotion and navigation when deprived of effective perceptual and proprioceptive information. For this, participants with hearing disability went three distances being the first and second 100 meters and the third 140 meters (triangulation) from a source point in an inverted L open field trajectory and then returned to the origin, and the first two were driven by a researcher guide with adapted GPS coordinates of the study, and the third being three free-form sessions, the first one without any perceptual and proprioceptive restriction, the second without visual perception, and the third on the wheel-chair, that is, without proprioception. The results showed that people with hearing disability without the knowledge of the path do not possess satisfactory accuracy but when they learn the way even with the restriction of visual perception and proprioception they can return to the starting point in a task of triangulation. The "t" students test with a significance level of 5% (2.131) indicates significant differences between the first task without any perceptual restriction and the third where they performed in the wheelchair. To achieve these results we used remote monitoring via GPS and the TrackMaker software.

Desenvolvimento de um sistema de SHM sem fio e com compensação automática de temperatura

Pós-graduação em Engenharia Elétrica - FEIS

Proposal of a dedicated telemetry device for real-time and remote measurements

This work aims to demonstrate an application of telemetry for monitoring process variables. The authors developed the prototype of a dedicated device capable of multiplexing, encoding and transmitting real-time data signals via amplitude-shift keying modulation to remotely located device(s). The prototype development is described in details, enabling the reproduction of the proposed telemetry system for a three-phase motor as well as for other devices. Furthermore, the proposed device has an easy implementation by using of accessible components and low cost, also presenting a tutorial and educational purpose. © 2011 IEEE.

Remote Sensing Detection of atmospheric pollutants using Lidar, Sodar and correlation with air quality data in an industrial area

Optical remote sensing techniques have obvious advantages for monitoring gas and aerosol emissions, since they enable the operation over large distances, far from hostile environments, and fast processing of the measured signal. In this study two remote sensing devices, namely a Lidar (Light Detection and Ranging) for monitoring the vertical profile of backscattered light intensity, and a Sodar (Acoustic Radar, Sound Detection and Ranging) for monitoring the vertical profile of the wind vector were operated during specific periods. The acquired data were processed and compared with data of air quality obtained from ground level monitoring stations, in order to verify the possibility of using the remote sensing techniques to monitor industrial emissions. The campaigns were carried out in the area of the Environmental Research Center (Cepema) of the University of São Paulo, in the city of Cubatão, Brazil, a large industrial site, where numerous different industries are located, including an oil refinery, a steel plant, as well as fertilizer, cement and chemical/petrochemical plants. The local environmental problems caused by the industrial activities are aggravated by the climate and topography of the site, unfavorable to pollutant dispersion. Results of a campaign are presented for a 24- hour period, showing data of a Lidar, an air quality monitoring station and a Sodar. © 2011 SPIE.

Applying machine learning based on multiscale classifiers to detect remote phenology patterns in Cerrado savanna trees

Plant phenology is one of the most reliable indicators of species responses to global climate change, motivating the development of new technologies for phenological monitoring. Digital cameras or near remote systems have been efficiently applied as multi-channel imaging sensors, where leaf color information is extracted from the RGB (Red, Green, and Blue) color channels, and the changes in green levels are used to infer leafing patterns of plant species. In this scenario, texture information is a great ally for image analysis that has been little used in phenology studies. We monitored leaf-changing patterns of Cerrado savanna vegetation by taking daily digital images. We extract RGB channels from the digital images and correlate them with phenological changes. Additionally, we benefit from the inclusion of textural metrics for quantifying spatial heterogeneity. Our first goals are: (1) to test if color change information is able to characterize the phenological pattern of a group of species; (2) to test if the temporal variation in image texture is useful to distinguish plant species; and (3) to test if individuals from the same species may be automatically identified using digital images. In this paper, we present a machine learning approach based on multiscale classifiers to detect phenological patterns in the digital images. Our results indicate that: (1) extreme hours (morning and afternoon) are the best for identifying plant species; (2) different plant species present a different behavior with respect to the color change information; and (3) texture variation along temporal images is promising information for capturing phenological patterns. Based on those results, we suggest that individuals from the same species and functional group might be identified using digital images, and introduce a new tool to help phenology experts in the identification of new individuals from the same species in the image and their location on the ground. © 2013 Elsevier B.V. All rights reserved.

A multisensor, multitemporal approach for monitoring herbaceous vegetation growth in the Amazon floodplain

The Amazon River floodplain is an important source of atmospheric CO2 and CH4. Aquatic herbaceous vegetation (macrophytes) have been shown to contribute significantly to floodplain net primary productivity (NPP) and methane emission in the region. Their fast growth rates under both flooded and dry conditions make herbaceous vegetation the most variable element in the Amazon floodplain NPP budget, and the most susceptible to environmental changes. The present study combines multitemporal Radarsat-1 and MODIS images to monitor spatial and temporal changes in herbaceous vegetation cover in the Amazon floodplain. Radarsat-1 images were acquired from Dec/2003 to Oct/2005, and MODIS daily surface reflectance products were acquired for the two cloud-free dates closest to each Radarsat-1 acquisition. An object-based, hierarchical algorithm was developed using the temporal SAR information to discriminate Permanent Open Water (OW), Floodplain (FP) and Upland (UL) classes at Level 1, and then subdivide the FP class into Woody Vegetation (WV) and Possible Macrophytes (PM) at Level 2. At Level 3, optical and SAR information were combined to discriminate actual herbaceous cover at each date. The resulting maps had accuracies ranging from 80% to 90% for Level 1 and 2 classifications, and from 60% to 70% for Level 3 classifications, with kappa values ranging between 0.7 and 0.9 for Levels 1 and 2 and between 0.5 and 0.6 for Level 3. All study sites had noticeable variations in the extent of herbaceous cover throughout the hydrological year, with maximum areas up to four times larger than minimum areas. The proposed classification method was able to capture the spatial pattern of macrophyte growth and development in the studied area, and the multitemporal information was essential for both separating vegetation cover types and assessing monthly variation in herbaceous cover extent.

Determining large scale actual evapotranspiration using agro-meteorological and remote sensing data in the northwest of Sao Paulo State, Brazil

The best irrigation management depends on accurate estimation of reference evapotranspiration (ET0) and then selection of the appropriate crop coefficient for each phenological stage. However, the evaluation of water productivity on a large scale can be done by using actual evapotranspiration (ETa), determined by coupling agrometeorological and remote sensing data. This paper describes methodologies used for estimating ETa for 20 centerpivots using three different approaches: the traditional FAO crop coefficient (K-c) method and two remote sensing algorithms, one called SEBAL and other named TEIXEIRA. The methods were applied to one Landsat 5 Thematic Mapper image acquired in July 2010 over the Northwest portion of the Sao Paulo State, Brazil. The corn, bean and sugar cane crops are grown under center pivot sprinkler irrigation. ET0 was calculated by the Penman-Monteith method with data from one automated weather station close to the study site. The results showed that for the crops at effective full cover, SEBAL and TEIXEIRA's methods agreed well comparing with the traditional method. However, both remote sensing methods overestimated ETa according to the degree of exposed soil, with the TEIXEIRA method presenting closer ETa values with those resulted from the traditional FAO K-c method. This study showed that remote sensing algorithms can be useful tools for monitoring and establishing realistic K-c values to further determine ETa on a large scale. However, several images during the growing seasons must be used to establish the necessary adjustments to the traditional FAO crop coefficient method.