Utilization of Water Resources and Sustainable Crop Production

BIM is representing a shift in the traditional process of building delivery. Its adoption in US reached 71% in 2012 rising from 17% in 2007; moreover, Europe is going to adopt BIM for public contracting as promoted by the European Union Public Procurement Directive. Meanwhile, BIM is widely diffused in UK and Northern Europe, as it includes a more accurate documentation, less rework and shorter project timelines. The use of BIM to provide data for energy performance evaluation and sustainability assessment is defined Green BIM and pioneering design organizations are adopting this approach to enable integrated design, construction and maintenance towards Net Zero Energy buildings. Green BIM includes Building Energy Modelling dealing with project energy performance to identify options optimising building energy efficiency during the life cycle. By allowing revisions during the design phase, project teams can ensure that customers' green ambitions beyond regulation compliance can be realized, together with technical and economic requirements. Thus, BIM can provide information to support the calculation of a number of credit points to define goal levels of sustainability related to rating systems. The aim of the paper is to investigate the opportunity to include the "green dimension" in BIM considering the more diffused rating systems.</p

Tracking users' behaviors through real-time information in BIMs: Workflow for interconnection in the Brescia Smart Campus Demonstrator

An intelligent building supports the needs of its occupants by data analytics. Nowadays, buildings are evolving from being products to become effective service providers for end-users: thus, occupancy topics become crucial. The paper focuses on building operations, pointing out how advantages in supporting the needs of users could be derived through the implementation of Building Management Systems (BMS) into a Building Information Modeling (BIM) environment, connecting real-time information collected by sensors to a BIM database. The connection and the integration of information between BIM and BMS have been established based on the Industry Foundation Classes (IFC) neutral data format; moreover, web-interfaces and apps have been tested for enhancing information to be visualized by different end-users. The ongoing research has a twofold scope: 1) to point-out how buildings should evolve, managing knowledge coming from sensors in order to anticipate the needs of users, and 2) to analyze whether and how the centrality of users should change the building process. The proposed workflow has been tested on the Brescia Smart Campus Demonstrator, a building equipped with 94 off-the-shelf sensors

Managing Real-Time Information Within BIM-Based Processes for Assessing Building Behaviours in Operation

Considering the remarkable shift that the digitalisation is nowadays bringing about in the building sector, the paper focuses on how the great amount of data collected around assets is changing the way buildings are operated, particularly for what concerns innovation on products, processes and technologies. By establishing a connection between as-designed virtual models and as-delivered physical assets, the paper presents methods and tools based on information management and developed for assessing building behaviours in operation and for defining control strategies for satisfying user needs. The research aims to investigate how the building process could benefit from the availability of multi-faceted information collected in real time (e.g. through sensors) during the operational stages of buildings. Digitally-enabled practices and technologies have been developed and tested for improving a data-driven asset management, by enriching Building Information Models through data gathered through Building Management Systems, according to the Industry Foundation Classes schema

Lean construction applied to a BIM process: how to control point attribution in MEAT tender process

Lean Construction (LC) and Building Information Modelling are the two methodologies linked by the same objectives. The former is an industrial optimization, which want to achieve the aim of performance increasing with the application to the AEC industry. These two concepts leaded Melzo school tender process writing. There are huge differences from a traditional process approach compared with BIM one, which leads project to a coherence high level. A deep LC principles understanding entail a distribution of the point to the different categories. The importance of LC criteria, in terms of points, imposes to the companies a change in the mind-set, from a lowest bid approach to a performance one. The study is based on the analysis of the responses to the case study procurement. Different competitors answer differently in function of Lean principles weight and their knowledge. The change in the state of mind leads the companies to offers value. In some cases, even if, many points were not able to change their behaviour. The behaviour' modification will be a difficult transformation for the AEC sector

Occupancy profile variation analyzed through generative modelling to control building energy behavior

Nowadays, building energy models use parametric analyses to optimize design strategies considering multiple variables. Integrated dynamic models combining design tool and visual programming language (VPL) and simulation tools to calculate building performance with BIM tool for the whole-building energy simulation have been adopted in the recent studies. Through these tools, it is possible to identify parametric systems, which become a "genome", where a rapid comparison of different alternatives is possible through fitness criteria defined by design goals. The aim of the paper is to use this concept and the suitable parametric tools such as Grasshopper for Rhinoceros to handle variable hypotheses on users' occupancy that influence building energy performance. The paper focuses on occupancy variability applying the methodology to a university building located in northern Italy in the University of Brescia Campus to evaluate how generative modelling can represent an adequate approach to energy simulation of occupant behaviour. Sensors are now monitoring the real occupancy trend of the case study building and different scenarios defined in the parametric model could be compared to the real weekly. Using parametric tool and GA (Genetic Algorithms) can be analysed hundreds of occupancy patterns in order to better understand the influence of the occupancy on the building energy use and at the same time evaluate different strategies to save energy.</p

Cognitive Adaptve Urban Systems for the Living Built Environment

The research proposes the use of structured data systems to define by connected attributes the buildings, the users and the infrastructure information as the kay scenario of the future development of the Cognitive Adaptive Urban Systems able to learn and respond to sustainable requirement, users’ behavior and anticipating and supporting their needs. In order to test the usability and to demonstrate the potential of a georeferenced, integrated information system on buildings in a practical use case, Politecnico di Milano and University of Brescia are focusing on the implementation of a district-wide heating energy need estimation: assuming current TDB contents as rough informational basis for energy modeling. The study aims to progressively evaluate the benefits related to different levels of data enrichment. Starting from rough TDB data, building information are integrated initially with semantic data coming from other existing datasets and furtherly with geometric data coming from BIMs. The final goal of the research is to measure improvements in accuracy related to a progressive data refinement and, at the same time, evaluate costs and efforts required for the realization of such refinement. The proposed methodology is intended to support designers and decisionmakers, providing a fully-integrated design process moving into a digital environment in which to test and track the users to predict the effects of the built environment on the human wellbeing