Case study based approach to integration of sustainable design analysis, performance and building information modelling

This paper presents a case study based research of both the method and technology for integration of sustainable design analysis (SDA) and building information modelling (BIM) within smart built environments (SBE). Level 3 BIM federation and integration challenges are recognised and improvements suggested, including issues with combining geometry and managing attribute data. The research defines SDA as rapid and quantifiable analysis of diverse sustainable alternatives and ‘what if’ scenarios posed by a design team and client during the early stages of the project, where the benefits of correct decisions can significantly exceed the actual investment required. The SDA concept and BIM integration findings are explained through a convergence from conceptualisation to calculation stages, emphasising the importance of an iterative over a linear approach. The approach allowed for a multitude of “what if” scenarios to be analysed, leading to more informed sustainable solutions at the right stages of the project development, with a generally lower level of detail (LOD) and computational/modelling effort required. In addition, the final stage of Building Regulations Part L compliance calculations was reached with a lot greater level of certainty, in terms of its requirements. Finally, a strategy for long term performance monitoring and evaluation of the building design in terms of its environmental sustainability is presented, via integration between BIM and SBE (Smart Built Environment) technologies

Bridges Structural Health Monitoring and Deterioration Detection Synthesis of Knowledge and Technology

INE/AUTC 10.0

Enhancing smart environments with mobile robots

Sensor networks are becoming popular nowadays in the development of smart environments. Heavily relying on static sensor and actuators, though, such environments usually lacks of versatility regarding the provided services and interaction capabilities. Here we present a framework for smart environments where a service robot is included within the sensor network acting as a mobile sensor and/or actuator. Our framework integrates on-the-shelf technologies to ensure its adaptability to a variety of sensor technologies and robotic software. Two pilot cases are presented as evaluation of our proposal.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Flexible data input layer architecture (FDILA) for quick-response decision making tools in volatile manufacturing systems

This paper proposes the foundation for a flexible data input management system as a vital part of a generic solution for quick-response decision making. Lack of a comprehensive data input layer between data acquisition and processing systems has been realized and thought of. The proposed FDILA is applicable to a wide variety of volatile manufacturing environments. It provides a generic platform that enables systems designers to define any number of data entry points and types regardless of their make and specifications in a standard fashion. This is achieved by providing a variable definition layer immediately on top of the data acquisition layer and before data pre-processing layer. For proof of concept, National Instruments’ Labview data acquisition software is used to simulate a typical shop floor data acquisition system. The extracted data can then be fed into a data mining module that builds cost modeling functions involving the plant’s Key Performance Factors

Discrete event simulation and virtual reality use in industry: new opportunities and future trends

This paper reviews the area of combined discrete event simulation (DES) and virtual reality (VR) use within industry. While establishing a state of the art for progress in this area, this paper makes the case for VR DES as the vehicle of choice for complex data analysis through interactive simulation models, highlighting both its advantages and current limitations. This paper reviews active research topics such as VR and DES real-time integration, communication protocols, system design considerations, model validation, and applications of VR and DES. While summarizing future research directions for this technology combination, the case is made for smart factory adoption of VR DES as a new platform for scenario testing and decision making. It is put that in order for VR DES to fully meet the visualization requirements of both Industry 4.0 and Industrial Internet visions of digital manufacturing, further research is required in the areas of lower latency image processing, DES delivery as a service, gesture recognition for VR DES interaction, and linkage of DES to real-time data streams and Big Data sets