Energy efficiency improvements through surveillance applications in industrial buildings

Presence sensors for energy control based on classic technologies to detect movement are now commonly seen in many areas of life. However, their use in structurally complex environments is not very common, due to their lack of reliability in these types of situations. Falling prices in technologies associated with surveillance applications are leading to a huge increase in their use in all types of environment, with monitoring of traffic and people the most common of these. In this work, we carry out an analysis of occupancy patterns in manufacturing industries with the aim of determining the possible energy savings that could be obtained using these new technologies. We also carry out an analysis of the possibilities of using these technologies as presence sensors, analyzing the trends and limitations associated with them. © 2011 Elsevier B.V.This work is supported by the MCYT of Spain under the project TIN2010-21378-C02-02.Silvestre-Blanes, J.; Pérez Llorens, R. (2011). Energy efficiency improvements through surveillance applications in industrial buildings. Energy and Buildings. 43(6):1334-1340. https://doi.org/10.1016/j.enbuild.2011.01.017S1334134043

Garment smoothness appearance evaluation through computer vision

The measurement and evaluation of the appearance of wrinkling in textile products after domestic washing and drying is performed currently by the comparison of the fabric with the replicas. This kind of evaluation has certain drawbacks, the most significant of which are its subjectivity and its limitations when used with garments. In this paper, we present an automated wrinkling evaluation system. The system developed can process fabrics as well as any type of garment, independent of size or pattern on the material. The system allows us to label different parts of the garment. Thus, as different garment parts have different influence on human perception, this labeling enables the use of weighting, to improve the correlation with the human visual system. The system has been tested with different garments showing good performance and correlation with human perception. © The Author(s) 2012.Silvestre-Blanes, J.; Berenguer Sebastiá, JR.; Pérez Llorens, R.; Miralles, I.; Moreno Canton, J. (2012). Garment smoothness appearance evaluation through computer vision. Textile Research Journal. 82(3):299-309. doi:10.1177/0040517511424530S299309823López, F., Miguel Valiente, J., Manuel Prats, J., & Ferrer, A. (2008). Performance evaluation of soft color texture descriptors for surface grading using experimental design and logistic regression. Pattern Recognition, 41(5), 1744-1755. doi:10.1016/j.patcog.2007.09.011Villette, S. (2008). Simple imaging system to measure velocity and improve the quality of fertilizer spreading in agriculture. Journal of Electronic Imaging, 17(3), 031109. doi:10.1117/1.2956835Neri, F., & Tirronen, V. (2009). Memetic Differential Evolution Frameworks in Filter Design for Defect Detection in Paper Production. Studies in Computational Intelligence, 113-131. doi:10.1007/978-3-642-01636-3_7Carfagni, M., Furferi, R., & Governi, L. (2005). A real-time machine-vision system for monitoring the textile raising process. Computers in Industry, 56(8-9), 831-842. doi:10.1016/j.compind.2005.05.010Wang, W., Wong, Y. S., & Hong, G. S. (2005). Flank wear measurement by successive image analysis. Computers in Industry, 56(8-9), 816-830. doi:10.1016/j.compind.2005.05.009Cho, C.-S., Chung, B.-M., & Park, M.-J. (2005). Development of Real-Time Vision-Based Fabric Inspection System. IEEE Transactions on Industrial Electronics, 52(4), 1073-1079. doi:10.1109/tie.2005.851648Kawabata, S., Mori, M., & Niwa, M. (1997). An experiment on human sensory measurement and its objective measurement. International Journal of Clothing Science and Technology, 9(3), 203-206. doi:10.1108/09556229710168324Fan, J., Lu, D., Macalpine, J. M. K., & Hui, C. L. P. (1999). Objective Evaluation of Pucker in Three-Dimensional Garment Seams. Textile Research Journal, 69(7), 467-472. doi:10.1177/004051759906900701Fan, J., & Liu, F. (2000). Objective Evaluation of Garment Seams Using 3D Laser Scanning Technology. Textile Research Journal, 70(11), 1025-1030. doi:10.1177/004051750007001114Yang, X. B., & Huang, X. B. (2003). Evaluating Fabric Wrinkle Degree with a Photometric Stereo Method. Textile Research Journal, 73(5), 451-454. doi:10.1177/004051750307300513Kang, T. J., Kim, S. C., Sul, I. H., Youn, J. R., & Chung, K. (2005). Fabric Surface Roughness Evaluation Using Wavelet-Fractal Method. Textile Research Journal, 75(11), 751-760. doi:10.1177/0040517505058855Mohri, M., Ravandi, S. A. H., & Youssefi, M. (2005). Objective evaluation of wrinkled fabric using radon transform. Journal of the Textile Institute, 96(6), 365-370. doi:10.1533/joti.2004.0066Zaouali, R., Msahli, S., El Abed, B., & Sakli, F. (2007). Objective evaluation of multidirectional fabric wrinkling using image analysis. Journal of the Textile Institute, 98(5), 443-451. doi:10.1080/00405000701489156Yu, W., Yao, M., & Xu, B. (2009). 3-D Surface Reconstruction and Evaluation of Wrinkled Fabrics by Stereo Vision. Textile Research Journal, 79(1), 36-46. doi:10.1177/004051750809049