Conference Agenda

The building footprint is likely to increase five-folds by 2030. These buildings consume a large chunk o energy in the form of electricity for running systems like air conditioning, artificial lighting, and equipment to name a few. The energy consumption in building sector can be decreased. This can be done by carrying out building performance evaluation studies, which will help in understanding the energy losses inside a building. This research focuses on developing an affordable monitoring and sensing system for building performance evaluation studies. Different hardware and software platforms are explored, and component selection was done after comparative analysis based on various aspects. The aspects considered for selection include: specifications, the ease of use, cost, and complexity of the system. The expected outcome is a methodology tailored for custom needs of the user, and a prototype for building performance evaluation studies.

The study addresses issues of the detection of built-up areas based on satellite images and prediction of changes in spatial planning using artificial neural networks. Using satellite images from the Landsat satellite, the authors have developed a built-up areas detection model using a combination of indexes such as NDBI, NDVI and MNDWI. The quality of classification was empirically verified on the basis of a set of randomly selected image points. Forecasts of changes in spatial planning were carried out with the use of two types of neural networks: MLP and RBF. For MLPs, the activation functions, such as logistic, hyperbolic tangent, Gaussian and sine, were tested. In total, more than 5.000 different models of artificial neural network have been built and verified. The simulations covered two areas diversified in terms of building density – fragments of the cities of Lodz and Zgierz located in central Poland in central Europe. Developed model provided changes in built-up areas between 1998 and 2006. In order to confirm the quality of model’s operation, the authors calculated percentage correctness of the area classification, which was 94.06% for the area with a higher degree of urbanization and 91.86% for the less urbanized area.

The semi-outdoor space is an important space in the hot-humid climate for preventing indoor environments from overheating and reducing building air-conditioning energy consumption. This paper presents a case study to find out the uncomfortable locations in a university building through field measurement, and proposes strategies for improving the thermal environment in the thermally uncomfortable locations. The improvement effect of the proposed strategies was analyzed using a microclimate simulation tool (ENVI-met) in terms of PMV and etc.

Laterite stone is an integral part of vernacular architecture in konkan belt of India. Procurement of these stones involve quarrying by small scale industries that have no further action plan in disposal of the scrap generated during the stone cutting. The paper looks at utilising the laterite quarry scrap to make blocks and exploring the opportunities the material holds in terms of its thermal properties, environmental factor, economic factor and structural factor. To establish the thermal properties of the scrap block in comparison to laterite stone and concrete block, a wall module of the respective material was built to determine a comparative decrement factor and time lag. The paper recommends the use of scrap, utilising locally available material, curbing the pollution generated and providing a cost-effective solution for the locals.