The Future of BIM

“Civilisation advances by extending the number of important operations we can perform without thinking about them”

150 Three business effects were identified by Fox (2006) as part of the BIM – VBE Measurement Framework (see figure 3.53). The sequence these effects are likely to occur in the order of automation change, informational change, then transformational change.

Figure 3.53: The changes brought about by BIM (Fox 2006)

The future development of BIM has been predicted by the Bew and Richards model (see figure 3.54). The capabilities of the IFC file format also are developing with proposals for any aspect of an IFC model to be “data driven”.

Figure. 3.54: The development of BIM Level 1, Level 2, Level 3 (Department of Business, Innovation and Skills 2011)

151 On this Bew and Richards model different levels of BIM development are indicated. These are:

- Level 0 - Computer Aided Design (CAD) - Flat CAD with no 3D data. Only traditional drawings are produced often in the form of DWG.

- Level 1 - 2D and 3D - builds upon CAD but it is creating data that is only used for visualisation purposes. These models are not creating useful data that can be shared with other members of the team.

- Level 2 - BIM - Individual discipline models used to collaborate which contain intelligent data. The full potential of the data may not have been realised at Level 2. Data will be provided from these models in COBie format for UK Government projects over £5 million.

- Level 3 - iBIM or Integrated BIM - Shared and Integrated BIM models and shared data providing information including facilities management and lifecycle costing data.

The UK government has mandated that public projects should have reached Level 2 by 2016.

Reaching Level 3 or “IBIM” (intelligent BIM) the use of data management servers will be required. The further development of big data and use of multi media databases within the construction domain are also likely to be part of Level 3 IBIM.

A parallel view of BIM development was put forward by Consult Australia (2010) (see figure 3.55).

152 Figure 3.55: The Australian maturity index for BIM development

Linking of BIM objects with real world objects is likely to have a significant impact. The development of object tagging and specifically RFID (radio frequency tagging) linked to GUID is already taking place (see figure 3.56 and 3.57). Vela Systems a provider of such technologies has recently been purchased by Autodesk to be integrated into BIM 360 Field and Revit. Object tagging has a role to play during construction phases but also during the operations and commissioning stages of a project.

153

Ali

Motamedi

and Amin

Hammad

Figure 3.57: The use of RFID Tags in the project lifecycle (Motamedi 2011) Currently the majority of BIM applications like the CAD systems they replace use a window, icon, mouse, pointer (WIMP) interface. The predicted progression interface technology is to a virtual reality (VR) interface (see figure 3.58). An increase in emphasis needs to be placed on the usability of the user interface (UI) (Chuang 2011) and the appropriateness of the models selected. This again will change the way BIM is worked with and perceived. Links between BIM and virtual environments such as “Second Life” are being developed (Pathmeswaran 2009). The use of virtual environments can be used for simulation and also virtual collaboration.

154 Figure 3.58: The evolution of the human computer interface (Fernando 2012) An ability to develop contextual adaption visualization environments (CAVE) which respond to the problem, the knowledge operator and the purpose have the potential to provide better decision support utilizing BIM data (see figure 3.59).

Figure 3.59: Development of contextual adaptive systems to aid decision support (Bai 2012)

155 Suggestions have also been made to link BIM models to case base reasoning systems (see figure 3.60) and evidence based design (Pati 2010). This has the ability to increase the capabilities of BIM in assisting in decision support.

Figure 3.60: Developing BIM by linking it to a case base reasoning library (Motowa 2013)

Information changes how we experience the physical world. Working with information rich models will change architects capabilities and insight into the architectural domain. How data should most effectively be modelled depends on the type of the data and the decisions to be made from that data. Owen and Horvath (2002) classified five types of knowledge representation (see figure 3.61) which can be used as appropriate.

156 Further analysis has taken place as to when these forms are typically used in the development process (see figure 3.62).

Figure 3.62: Types of Knowledge Representation traditionally used in the product development process (Chandrasegaran 2012)

The challenge of BIM will be to integrate all of these forms of knowledge representation into an effective process.

The amount of data particularly in digital form is increasing rapidly (see figure 3.63). In the UK the Open Data Institute has been set up to promote the UK governments Open Data Policy.

157 Figure 3.63: Rise of the digital information age (Vastag 2011)

The decrease in the cost of digital storage and the development of cloud computing has encouraged this rapid growth of data (see figure 3.64).

158 Figure 3.64: The growth in the percentage of data stored on the cloud by small and

medium size companies (Pham 2011)

The implication of cloud computing on the development of BIM can be considered in several ways (see figure 6.65). Autodesk chief executive officer Carl Bass boldly describes his company’s recent and radical expansion of cloud-based products and functionality as “the biggest thing to happen to computing since the invention of the PC” (Ijeh, 2012). Private BIM clouds have also been developed by BIM9.

Figure 3.65: Approaches to cloud computing (based on Varkonyi 2011)

This explosion in data will be augmented by data captured through sensing devices which are now becoming part of our built environment. Cloud computing is already used for rendering and computational processes by the Revit BIM software. In the

159 future cloud computing is likely to address processing speed and storage issues which have traditionally limited computerised systems being used for architectural design and PLM (Project Lifecycle Management) systems.

The variety of data available is increasing along with the velocity at which it can be accessed and the range of devices on which it can operate (see figure 3.66).

Figure 3.66: Data from multiple sources populating multiple interfaces

BIM represents one component in the explosion of digital data and the development of “the internet of things” (Ashton 2009). By using data rich BIM objects as a foundation, larger structured data stores can be potentially created. As BIM becomes more widely adopted there will develop an increased emphasis on the usability of such systems and the removal of the lean waste of processing unnecessary data. A new-generation business analytics solutions comprising of agile business intelligence (BI) and analytical database technology that have the capacity to quickly, effectively and efficiently produce knowledge representations and actionable intelligence need to be developed using BIM data.

Data visualization and computer simulation can support strategic thinking, by reducing cognitive load, offloading short-term memory, allowing for easier comparisons, and generally facilitating inferences. Research has indicated data driven decision making increases productivity in organisations by 5-6% higher than would be expected given their other investments and information technology use (Brynjolfsson 2011).

160 Information visualization is already used in many areas of BIM. Examples include clash detection (see figure 3.67) and rule based design checking (see figure 3.68 and 3.69) both use visual forms to allow analysis.

Figure 3.67: Navisworks BIM software being used to visualize clash detection

Figure 3.68: Setting up rule based checking for building access standards in Solibri Model Checker

161 Figure 3.69: An example of rule based checking using Bluethink house designer

(Khemlani 2009)

BIM using visual analytics is an emerging field of development. It combines the strengths from information analytics, geospatial analytics, scientific analytics, statistical analytics, knowledge discovery, data management and knowledge representation, presentation, production and dissemination, cognition, perception and interaction.

Some of the model forms that can be adopted to aid BIM decision making are illustrated (see figure 3.70 and 3.71). Models maybe form models, statistical models or process models. Using information visualization it will be possible to move from syntactic interoperability (data exchange) to semantic interoperability where the meaning is exchanged.

162 Figure 3.71: Form models, statistical models and process models all assisting in

decision support (contains work by Eppler and Burkhart 2005)

What is required is a move form descriptive analytics to prescriptive analytics (Richardson 2013) (see figure 3.72).

163 Running in parallel to BIM is the development of point cloud data from laser scanning (see figure 3.73). Products such as Autodesk Recap show the future potential of integrating point cloud data with BIM models.

Figure 3.73: Timeline for laser scanning development (Randall 2013)