Automatica (Journal of IFAC) - Special issue on statistical signal processing and control
N4SID: subspace algorithms for the identification of combined deterministic-stochastic systems
Automatica (Journal of IFAC) - Special issue on statistical signal processing and control
Consistency and relative efficiency of subspace methods
Automatica (Journal of IFAC) - Special issue on trends in system identification
Statistical analysis of novel subspace identification methods
Signal Processing - Special issue: subspace methods, part II: system identification
Subspace identification from closed loop data
Signal Processing - Special issue: subspace methods, part II: system identification
Real-time streaming of environmental field data
Computers & Geosciences
Computers and Electronics in Agriculture
Computers and Electronics in Agriculture
Review: Wireless sensors in agriculture and food industry-Recent development and future perspective
Computers and Electronics in Agriculture
On Consistency of Subspace Methods for System Identification
Automatica (Journal of IFAC)
Closed-loop identification revisited
Automatica (Journal of IFAC)
Consistency and asymptotic normality of some subspace algorithms for systems without observed inputs
Automatica (Journal of IFAC)
Analysis of the asymptotic properties of the MOESP type of subspace algorithms
Automatica (Journal of IFAC)
Brief Consistency analysis of subspace identification methods based on a linear regression approach
Automatica (Journal of IFAC)
Computers and Electronics in Agriculture
Design and test of nodes for field information acquisition based on WUSN
ICICA'11 Proceedings of the Second international conference on Information Computing and Applications
A survey on wireless sensor network infrastructure for agriculture
Computer Standards & Interfaces
Prediction of quality parameters for biomass silage: A CFD approach
Computers and Electronics in Agriculture
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By monitoring silage temperature at different locations inside silage stacks, it is possible to detect any significant increases in temperature occurring during silage decomposition. The objectives of this study were: (1) to develop novel noninvasive wireless sensor nodes for measuring the temperature inside silage stacks; (2) to design a suitable sensor protection housing that prevents physical and chemical damage to the sensor; and (3) to mathematically model temperature variations inside a silage stack, using system identification techniques. The designed wireless nodes were used to monitor temperatures in a full-sized silage stack over 53 days. Results showed that the wireless sensor nodes accurately monitored the temperature inside the silage stack at depths of 25 and 50cm and reliably transmitted the measured data through the network; between 98.9% and 99.4% of the packets disseminated from the sensor nodes were successfully delivered to the gateway. The reliable performance of the network confirmed the correct choice of network characteristics (i.e., frequency range of 433MHz, a handshaking communication protocol, and 10mW transmission power). The designed sensor housings were capable of withstanding the high loads that occurred during ensiling, storage, and feed-out. Mathematical models estimating the relations between the silage temperatures (at depths of 25 and 50cm) and air and soil temperatures were obtained. Black-box modeling using the prediction error method (PEM) was selected as the identification method. Among different black-box models such as ARX, ARMAX, output-error (OE), and Box-Jenkins (BJ), with different model orders, a third-order Box-Jenkins model structure gave the best performance in terms of prediction accuracy. The success rate of the models proposed for silage temperature prediction ranged between 90.0% and 94.3%. Furthermore, there was no significant autocorrelation remaining in the residuals. The results of this study indicate that the designed wireless sensor nodes could potentially be used for detecting silage decomposition processes and improving the efficacy of silage conservation systems.