KEYWORDS: Humidity, Light emitting diodes, LED displays, Sensors, Surveillance, Temperature metrology, Temperature sensors, Lithium, Signal processing, Software development
The control to temperature and humidity of small civilian granary is great important to grain storage. In this paper, we propose a smart surveillance device to monitor temperature and humidity in real-time to ensure high quality food storage. This simple and small size device could achieve good anti-jamming at extremely low power consumption. It could automatically trigger the sound-light alarm when either temperature or humidity is higher than a preset threshold value.
In this paper, a general and efficient facial feature extraction approach, global search linear discriminant analysis
(GSLDA), is presented. It is designed to solve the puzzle of standard linear discriminant analysis (LDA) for small
sample size problems (SSSP). Compared with PCA-LDA, in GSLDA, raw data dimension can be greatly decreased
without discarding important discriminant information. In this process, all basis vectors of the non-null eigen-space of
the scatter matrix is worked out, and then the well-known global search strategy, genetic algorithm, is enrolled to select
basis vectors to construct a new feature space which has optimal discriminant ability. In contrast with PCA, this
approach reserves more information for recognition. Therefore, this process enhances the performance of LDA for SSSP,
and eventually the recognition performance. This strategy has been tested on the ORL and Yale face database.
Experiment results show that this approach works much better than classical facial feature extraction methods.
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