Hyperspectral Remote Sensing Technology in Intelligent Buildings & Engineering - Research Paper Example

Other (s) Hyperspectral Remote Sensing Technology in Intelligent Buildings & Engineering Hyperspectral remote sensing is one of the emerging technologies with a wide range of applications in a diverse number of fields including the intelligent buildings and engineering in recent years. Also known as imaging spectroscopy, the technology particularly involves collecting and processing of information or images across narrow electromagnetic spectrum using remote sensors such as cameras, films and other digital instruments. This is normally done in order to find the spectrum of each pixel of the image for purposes of identifying materials, finding objects or detecting various processes. In Intelligent Buildings & Engineering, Hyperspectral Remote Sensing Technology is primarily being used to provide an effective means of monitoring and analysis of various real-time data that can help enhance the operational efficiency and reduce costs and energy expenses of smart buildings thereby making them to be more comfortable, safe, and healthy as well as enhance the productivity of the occupants. Unlike multispectral imaging which normally deals with numerous images at discrete, narrow bands, Hyperspectral remote sensing is primarily based on narrow spectral bands produced over a continuous spectral range. This is critically important as it makes the images more detailed. One of the areas of intelligent building and engineering where hyoerspectral remote sensing imaging can be used is to make buildings safer and more comfortable by providing reliable geological and rock information, seismic and environmental data regarding the construction sites prior to the commencement of the construction of the buildings. Generally, this is critically important in helping choose the appropriate building and engineering project designs as well as materials that best fit a particular geographical area. Fig.1: Hyperspectral remote sensing image Another possible application of hyperspectral remote sensing in intelligent buildings and engineering is the collection and processing of information relevant for the integration of various systems related to safety that can help in the optimization of the performance of smart buildings. For example, the technology can easily be applied to monitor the various facilities related to the construction and design of intelligent buildings some of which may include air condition, temperature and the distribution of trees within the location of the intelligent buildings. For example, by observing the spectral absorption features of a particular location, intelligent building engineers can easily determine and measure various environmental and atmospheric parameters such as the level of pollution, aerosols and water vapor in a given region. According to Borengasser et al. (73), the hyper-spectral signature can also be effectively used detect the individual absorption features of the materials used to construct the smart buildings since all the materials are normally bounded by chemical bonds. For example, previous studies have revealed that hyperspectral remote sensing can successfully be used in intelligent building and engineering to identify asbestos-containing roofs thereby enabling the engineers to take appropriate measures. Some of the other important information of the building construction sites that can be collected and analyzed through the technology includes changes in the surrounding vegetation, water of soil and air condition. This kind of information is particularly important in the development of a more comfortable working or operating environment for the would-be occupants and tenants of the building. On the other hand, the spatial information obtained through hyperspectral remote sensing can also effectively be used to in the planning and development of intelligent buildings to help improve lighting, security and other key installations needed in an intelligent building (Rashed 352). In order to make buildings more livable and meet the relevant standards, smart building engineers can employ the use of hyperspectral remote sensing technology to develop spatial maps that are critical in the planning of population centers, traffic, and drainage and utility networks among others. Finally, hyperspectral remote sensing technology is important in impervious surfaces know-how especially regarding the geometry, magnitude, spatial patterns of perviousness-imperviousness ration and impervious surfaces patterns; are significant considerations in the remote sensibility constructions. The knowledge on impervious engineering structure surfaces provides a wide-ranged themes and issues necessary in global environmental change, environmental engineering field and human milieu interactions (Lagaris 145). A key futuristic aspect of this remotes classifier is its intelligent ability to use highly-regarded dimensional data with unusual resources to a feature sensible selection step which adversely reduce the data presented dimensionality. For this intelligence engineering structural design, the hyperspectral data application is achieved through hundreds of hundreds contagiously spectral channels. Generally, remote sensing of impervious surfaces’ structures in engineering structures has in the recent past attracted unpredicted attention in the engineering field. Data/remote fusion ensures a perfect extraction and estimation of impervious surfaces. Mapping requirements of these impervious surfaces in hyper spectral sensing technology in intelligent buildings and engineering structures impacts on the spatial, spectral, geometric and time-based solutions on the mapping estimates addressed. Pixel-based inclusive of regression and image classification and sub-pixel based approaches such as linear spectral un-mixing provides for an object oriented algorithms special resolution and landscaping contextualized classification methods. Multimedia hyper spectral remote sensing technology in intelligent buildings and engineering structures: An example of a multimedia hyper spectral engineering structure is the support vector machine. The support vector machine structurally paves way technologically for a newly initiated way to design classification sensory algorithms which learn exceptionally from examples (Chang 111). The learning examples from these technologically advanced structures include supervised sensory learning which are generalised during intelligence remote sensing application of new data. The technological remote sensibility success of support vector machines in relation to difficult intelligence classifications problems from hyper spectral remote sensing has been structurally recorded higher performance. In conclusion, hyperspectral remote sensing is an important new technology that has numerous applications in the field of intelligent buildings and engineering. Although the technology was originally developed for geology and mining, it is increasingly being used in a wide range of areas such as to provide an effective method of monitoring and analysis of various real-time data that can help enhance the operational efficiency and reduce costs and energy expenses of smart buildings thereby making them to be more comfortable, safe, and healthy and enhance the productivity of the tenants. Works Cited Borengasser Marcus, Hungate William S., Watkins Russell. Hyperspectral Remote Sensing: Principles and Applications Principles and Applications. New York: CRC Press, 2007. Print. Chang, Cheng-Wen, et al. "Near-infrared reflectance spectroscopy–principal components regression analyses of soil properties." Soil Science Society of America Journal 65.2 (2001): 480-490. Lagarias, Jeffrey C., et al. "Convergence properties of the Nelder--Mead simplex method in low dimensions." SIAM Journal on optimization 9.1 (2008): 112-147. Rashed, Tarek. “Remote sensing of within-class change in urban neighborhood structures.” Comput. Environ. Urban Syst., 32.5(2008): 343-354. Print. Read More