9783847335795 - Intelligent Environment Monitoring System: Intelligent Environment Monitoring System For Built Environment de Kumar, Anuj; Kim, Hiesik (3 resultados)

Taschenbuch. Condición: Neu. Intelligent Environment Monitoring System | Intelligent Environment Monitoring System For Built Environment | Anuj Kumar (u. a.) | Taschenbuch | Englisch | LAP Lambert Academic Publishing | EAN 9783847335795 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Kartoniert / Broschiert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Kumar AnujAnuj Kumar received his Ph.D. Degree in Embedded System from IIT Delhi, India in 2011, M.Tech. degree in Instrumentation from NIT kurukshetra, Haryana, India in 2004 and M. Phil in Instrumentation from IIT Roorkee, UA, Indi.

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - An indoor environment monitoring system has been developed in compliance with the IEEE1451.2 standard. The sensor array is implemented using electrochemical sensors. The STIM is implemented using the PIC18F4550 microcontroller. Network capable application processor, implemented in LabVIEW 9.0, and is based on the IEEE 1451.1 standard. NCAP is connected to the STIM via a USB 2.0 transducer independent interface. The level of indoor environment parameters and information regarding STIM can be seen on the graphical user interface of the NCAP. Sensors are recalibrated using the potentiometer adjustment technique of signal conditioning circuits. The IEMS is low cost, energy efficient, and portable. Another important area is the real time processing applications. These are highly dependent on data acquisition which quite often suffers from the problem of missing input variables. Two techniques have been proposed as a solution to the problem of missing input variables for short durations. These are the radial basis function (RBF) based artificial neural network and the linear regression analysis. Thermal comfort is one of the most important applications based on devloped IEM System.