992 resultados para Infrastructure sustainability
Resumo:
Sustainable aquaculture in Asia is discussed, considering in particular the loss of mangroves associated with the rapid increase in production of cultured shrimp. Southeast Asia's development and population growth brought non-sustainable exploitation of its coastline; the destruction has increased through the years as development proceeded and the international markets entered the scenario. An outline is given of the current status of mangroves in some Asian countries. Some worldwide remedies for sustainable aquaculture are described.
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A business model for integrating global-production efficiencies with sustainability is discussed. Two trends that emulate some of the aspects of the wealthy are the increasing willingness of many to pay extra for customization such as clothes, of kitchens and the increasing acceptance of purchasing a service as a product substitute. Two final trends that are also based in the attitudes of people is an increased awareness of the value of local culture and an increased concern with issues of sustainability. The results show that the goal congruence between for-profit and not-for-profit organizations puts emphasis on value and belief of the organization.
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Just under half of all energy consumption in the UK today takes place indoors, and over a quarter within our homes. The challenges associated with energy security, climate change and sustainable consumption will be overcome or lost in existing buildings. A background analysis, and the scale of the engineering challenge for the next three to four decades, is described in this paper.
Resumo:
Just under half of all energy consumption in the UK today takes place indoors, and over a quarter within our homes. The challenges associated with energy security, climate change and sustainable consumption will be overcome or lost in our existing buildings. A background analysis, and the scale of the engineering challenge for the next three to four decades, is described in this paper.
Resumo:
This paper discusses the sustainability of two different approaches to upgrade water and sanitation infrastructure in Kenya’s largest informal settlement, Kibera. A background to the urbanization of poverty is outlined along with approaches to urban slums. Two case-studies of completed interventions of infrastructure upgrading have been investigated. In one case-study, the upgrading method driven by an NGO uses an integrated livelihoods and partnership technique at community level to create an individual project. in the other case-study, the method is a collaboration between the government and a multi-lateral agency to deliver upgraded services as a part of a country-wide programme. The ‘bottom-up’ (project) and ‘top-down’ (programme) approaches each seek sustainability and aim to achieve this in the same context using different techniques. This paper investigates the sustainability of each approach. The merits and challenges of the approaches are discussed with the projected future of Kibera. The paper highlights the valuable opportunity for the role of appropriate engineering infrastructure for sustainable urban development, as well as the alleviation of poverty in a developing context.
Resumo:
This response does not only include greening the campus but also transforming curricula and teaching and learning. This book explains why this is necessary and--crucially--how to do it.
Resumo:
A number of methods are commonly used today to collect infrastructure's spatial data (time-of-flight, visual triangulation, etc.). However, current practice lacks a solution that is accurate, automatic, and cost-efficient at the same time. This paper presents a videogrammetric framework for acquiring spatial data of infrastructure which holds the promise to address this limitation. It uses a calibrated set of low-cost high resolution video cameras that is progressively traversed around the scene and aims to produce a dense 3D point cloud which is updated in each frame. It allows for progressive reconstruction as opposed to point-and-shoot followed by point cloud stitching. The feasibility of the framework is studied in this paper. Required steps through this process are presented and the unique challenges of each step are identified. Results specific to each step are also presented.
Resumo:
The commercial far-range (>10 m) spatial data collection methods for acquiring infrastructure’s geometric data are not completely automated because of the necessary manual pre- and/or post-processing work. The required amount of human intervention and, in some cases, the high equipment costs associated with these methods impede their adoption by the majority of infrastructure mapping activities. This paper presents an automated stereo vision-based method, as an alternative and inexpensive solution, to producing a sparse Euclidean 3D point cloud of an infrastructure scene utilizing two video streams captured by a set of two calibrated cameras. In this process SURF features are automatically detected and matched between each pair of stereo video frames. 3D coordinates of the matched feature points are then calculated via triangulation. The detected SURF features in two successive video frames are automatically matched and the RANSAC algorithm is used to discard mismatches. The quaternion motion estimation method is then used along with bundle adjustment optimization to register successive point clouds. The method was tested on a database of infrastructure stereo video streams. The validity and statistical significance of the results were evaluated by comparing the spatial distance of randomly selected feature points with their corresponding tape measurements.
Resumo:
As-built models have been proven useful in many project-related applications, such as progress monitoring and quality control. However, they are not widely produced in most projects because a lot of effort is still necessary to manually convert remote sensing data from photogrammetry or laser scanning to an as-built model. In order to automate the generation of as-built models, the first and fundamental step is to automatically recognize infrastructure-related elements from the remote sensing data. This paper outlines a framework for creating visual pattern recognition models that can automate the recognition of infrastructure-related elements based on their visual features. The framework starts with identifying the visual characteristics of infrastructure element types and numerically representing them using image analysis tools. The derived representations, along with their relative topology, are then used to form element visual pattern recognition (VPR) models. So far, the VPR models of four infrastructure-related elements have been created using the framework. The high recognition performance of these models validates the effectiveness of the framework in recognizing infrastructure-related elements.
Resumo:
Infrastructure spatial data, such as the orientation and the location of in place structures and these structures' boundaries and areas, play a very important role for many civil infrastructure development and rehabilitation applications, such as defect detection, site planning, on-site safety assistance and others. In order to acquire these data, a number of modern optical-based spatial data acquisition techniques can be used. These techniques are based on stereo vision, optics, time of flight, etc., and have distinct characteristics, benefits and limitations. The main purpose of this paper is to compare these infrastructure optical-based spatial data acquisition techniques based on civil infrastructure application requirements. In order to achieve this goal, the benefits and limitations of these techniques were identified. Subsequently, these techniques were compared according to applications' requirements, such as spatial accuracy, the automation of acquisition, the portability of devices and others. With the help of this comparison, unique characteristics of these techniques were identified so that practitioners will be able to select an appropriate technique for their own applications.
Resumo:
Infrastructure spatial data, such as the orientation and the location of in place structures and these structures' boundaries and areas, play a very important role for many civil infrastructure development and rehabilitation applications, such as defect detection, site planning, on-site safety assistance and others. In order to acquire these data, a number of modern optical-based spatial data acquisition techniques can be used. These techniques are based on stereo vision, optics, time of flight, etc., and have distinct characteristics, benefits and limitations. The main purpose of this paper is to compare these infrastructure optical-based spatial data acquisition techniques based on civil infrastructure application requirements. In order to achieve this goal, the benefits and limitations of these techniques were identified. Subsequently, these techniques were compared according to applications' requirements, such as spatial accuracy, the automation of acquisition, the portability of devices and others. With the help of this comparison, unique characteristics of these techniques were identified so that practitioners will be able to select an appropriate technique for their own applications.