2013
Salgado, C.; Cardoso, L.; Gonçalves, P.; Abelha, A.; Machado, J.
Tracking People and Equipment Simulation inside Healthcare Units Proceedings Article
Em: pp. 9-16, Springer Verlag, Salamanca, 2013, ISSN: 21945357, (cited By 2; Conference of 4th International Symposium on Ambient Intelligence, ISAmI 2013 ; Conference Date: 22 May 2013 Through 24 May 2013; Conference Code:98888).
Resumo | Links | BibTeX | Etiquetas: Algorithms; Application programs; Artificial intelligence; Data mining; Equipment; Forecasting; Health care; Sensors; Target tracking, Data mining algorithm; Healthcare environments; Intelligent tracking; RFID object tracking; Simulated environment; Simulation; SK-Means; Trajectory prediction, Trajectories
@inproceedings{Salgado20139,
title = {Tracking People and Equipment Simulation inside Healthcare Units},
author = {C. Salgado and L. Cardoso and P. Gonçalves and A. Abelha and J. Machado},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84882965823&doi=10.1007%2f978-3-319-00566-9_2&partnerID=40&md5=fe461106d775847023ee69c7d7fff500},
doi = {10.1007/978-3-319-00566-9_2},
issn = {21945357},
year = {2013},
date = {2013-01-01},
journal = {Advances in Intelligent Systems and Computing},
volume = {219},
pages = {9-16},
publisher = {Springer Verlag},
address = {Salamanca},
abstract = {Simulating the trajectory of a patient, health professional or medical equipment can have diverse advantages in a healthcare environment. Many hospitals choose and to rely on RFID tracking systems to avoid the theft or loss of equipment, reduce the time spent looking for equipment, finding missing patients or staff, and issuing warnings about personnel access to unauthorized areas. The ability to successfully simulate the trajectory of an entity is very important to replicate what happens in RFID embedded systems. Testing and optimizing in a simulated environment, which replicates actual conditions, prevent accidents that may occur in a real environment. Trajectory prediction is a software approach which provides, in real time, the set of sensors that can be deactivated to reduce power consumption and thereby increase the system's lifetime. Hence, the system proposed here aims to integrate the aforementioned strategies - simulation and prediction. It constitutes an intelligent tracking simulation system able to simulate and predict an entity's trajectory in an area fitted with RFID sensors. The system uses a Data Mining algorithm, designated SK-Means, to discover object movement patterns through historical trajectory data. © Springer International Publishing Switzerland 2013.},
note = {cited By 2; Conference of 4th International Symposium on Ambient Intelligence, ISAmI 2013 ; Conference Date: 22 May 2013 Through 24 May 2013; Conference Code:98888},
keywords = {Algorithms; Application programs; Artificial intelligence; Data mining; Equipment; Forecasting; Health care; Sensors; Target tracking, Data mining algorithm; Healthcare environments; Intelligent tracking; RFID object tracking; Simulated environment; Simulation; SK-Means; Trajectory prediction, Trajectories},
pubstate = {published},
tppubtype = {inproceedings}
}
Simulating the trajectory of a patient, health professional or medical equipment can have diverse advantages in a healthcare environment. Many hospitals choose and to rely on RFID tracking systems to avoid the theft or loss of equipment, reduce the time spent looking for equipment, finding missing patients or staff, and issuing warnings about personnel access to unauthorized areas. The ability to successfully simulate the trajectory of an entity is very important to replicate what happens in RFID embedded systems. Testing and optimizing in a simulated environment, which replicates actual conditions, prevent accidents that may occur in a real environment. Trajectory prediction is a software approach which provides, in real time, the set of sensors that can be deactivated to reduce power consumption and thereby increase the system's lifetime. Hence, the system proposed here aims to integrate the aforementioned strategies - simulation and prediction. It constitutes an intelligent tracking simulation system able to simulate and predict an entity's trajectory in an area fitted with RFID sensors. The system uses a Data Mining algorithm, designated SK-Means, to discover object movement patterns through historical trajectory data. © Springer International Publishing Switzerland 2013.
2011
Gongalves, P.; Alves, L.; Sá, T.; Quintas, C.; Miranda, M.; Abelha, A.; MacHado, J.
Object trajectory simulation - An evolutionary approach Proceedings Article
Em: pp. 409-413, EUROSIS, Guimaraes, 2011, (cited By 1; Conference of 25th European Simulation and Modelling Conference, ESM 2011 ; Conference Date: 24 October 2011 Through 26 October 2011; Conference Code:104378).
Resumo | Links | BibTeX | Etiquetas: Data mining; Forecasting; Modal analysis; Radio frequency identification (RFID); Sensors, Error metrics; Evolutionary approach; Evolutionary intelligence; Multiple dimensions; Object trajectories; Prediction model; Space between; Trajectory prediction, Trajectories
@inproceedings{Gongalves2011409,
title = {Object trajectory simulation - An evolutionary approach},
author = {P. Gongalves and L. Alves and T. Sá and C. Quintas and M. Miranda and A. Abelha and J. MacHado},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84899018956&partnerID=40&md5=a9b5426daa16b5fbb696ae8eaa0d561e},
year = {2011},
date = {2011-01-01},
journal = {ESM 2011 - 2011 European Simulation and Modelling Conference: Modelling and Simulation 2011},
pages = {409-413},
publisher = {EUROSIS},
address = {Guimaraes},
abstract = {The ability to successfully predict the trajectory of an entity can have numerous interests. Using trajectory prediction we propose to enhance Radio-Frequency IDentification embedding intelligent behaviours that allow these systems to improve their accuracy in the detection and guidance of personal in RFID enabled infrastructures. This paper proposes a representative approach to a simulated area filled with sensors and travelled by an object. The object has an initial and end points and does random movement between them. The remaining unknown path must be provided by the sensors and the prevision module while error metrics must be calculated dynamically to help the prediction of the followed path. In this scenario, a trajectory is a path that an entity follows through space between iterations, and it can be represented as a set, of coordinates sorted over time. The level of accuracy needed for the prediction model and objectives of this environment required a grid like representation. The presented solution is a multiple dimension structure that covers the environ-ment variables and entities of a move within the environment. An application has been developed to simulate a censored place driven by a random trajectory object and to calculate as accurate as possible the path of the object. ©2011 EUROSIS-ETI.},
note = {cited By 1; Conference of 25th European Simulation and Modelling Conference, ESM 2011 ; Conference Date: 24 October 2011 Through 26 October 2011; Conference Code:104378},
keywords = {Data mining; Forecasting; Modal analysis; Radio frequency identification (RFID); Sensors, Error metrics; Evolutionary approach; Evolutionary intelligence; Multiple dimensions; Object trajectories; Prediction model; Space between; Trajectory prediction, Trajectories},
pubstate = {published},
tppubtype = {inproceedings}
}
The ability to successfully predict the trajectory of an entity can have numerous interests. Using trajectory prediction we propose to enhance Radio-Frequency IDentification embedding intelligent behaviours that allow these systems to improve their accuracy in the detection and guidance of personal in RFID enabled infrastructures. This paper proposes a representative approach to a simulated area filled with sensors and travelled by an object. The object has an initial and end points and does random movement between them. The remaining unknown path must be provided by the sensors and the prevision module while error metrics must be calculated dynamically to help the prediction of the followed path. In this scenario, a trajectory is a path that an entity follows through space between iterations, and it can be represented as a set, of coordinates sorted over time. The level of accuracy needed for the prediction model and objectives of this environment required a grid like representation. The presented solution is a multiple dimension structure that covers the environ-ment variables and entities of a move within the environment. An application has been developed to simulate a censored place driven by a random trajectory object and to calculate as accurate as possible the path of the object. ©2011 EUROSIS-ETI.