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European Bim Summit Barcelona 2018. CAATEEB Fotos
European Bim Summit Barcelona 2018
European BIM Summit Barcelona 2018. CAATEEB photos

Public and private promoters, in particular from the north of the country, are committed to Passivhaus, seeing the maturity of its solutions around the world and the simplicity of the certification protocol itself. This year, strategic buildings such as the Tower of Bolueta (the highest Passivhaus block in the world), the “carrer Nou2” building in Girona (the first EnerPhit in multi-residential use) and the rehabilitation of an office building in Oviedo have just been certified under this standard.

When we refer to digitalisation in the construction industry, we don’t just mean working in BIM. BIM is essential for ensuring that the documentation of the projects ceases to be anonymous and becomes recognisable and allows us to do so in all the phases of the life cycle. The phases which are currently most developed are those related to the project and the construction work, while the use and demolition phases are less developed.

When we mention BIM, we commonly refer to the information contained in a digital model (if we aren’t directly referring to specific software) on the scale of a building or civil work. Focusing solely on the information of a single digital model enables us to recognise said model, which is a lot, but not enough, as it doesn’t guarantee continuous improvement, a basic aspect of a digitalisation process.

A simple example which can help us to understand the degree of digitalisation of the models used is to consider what questions these models are capable of answering. How much does it cost? How much water and energy does it consume? What will the deconstruction capacity be? If we start asking these questions, we will see the real limitations of the current work models, although we will barely obtain any information on geometry and price.

This is a first level, that of the incorporation of information into our constructive models. The different BIM dimensions, 3D, 4D, 5D, 6D and 7D, provide us with the necessary clues regarding the information we can add to these models and the questions they can answer.

Management of the information of a building during its use. CENSEO software

The second level is communication, understanding said communication as the ability to share information. At this point, I’d distinguish between two different areas that can enrich the industry in the same way.

Firstly, the ability to pool the information of the model with different technologies. We could mention IoT (the Internet of things), virtual reality, augmented reality, 3D printing, etc. It’s very easy to group them together in this way because their relationship with our digital models is very different. All in all, it helps to simplify the idea.

The Internet of Things opens up a door to knowledge of our construction activity and use of buildings we could never have imagined. Only in terms of use, the amount of data provided by the IoT about how we’re able to use our buildings would require its own article. Of course, it’s clear that, in many cases, the information we can obtain from the sensors (the set of devices which can acquire data in buildings) will provide us with answers to questions we haven’t yet come up with, although this forms part of a level of digitalisation that I’ll explain later.

The second area is the ability to share the information of the model with different players in the construction industry. There’s a long way to go before all the information managed in the construction industry becomes digitalised and the first step is for each of the players to be aware of the importance of digitalisation. In this regard, we’re only beginning.

Manufacturers should understand that their products’ data must be structured in such a way that, in addition to providing information on their prices and basic characteristics, can be used to make thermal, acoustic or environmental impact calculations by means of their incorporation into the digital models. Otherwise, we’ll be losing an important part of what we can obtain from said digitalisation.

The public administrations should begin to share the information on their management in usable formats. We must not only be aware of all the work generated by a public administration, we must also be able to use it, obviously in compliance with the Data Protection Law. We must also know, for example, the energy consumption of the public infrastructures, what materials and products these have been made with, how long they last and so on. It’s necessary for this data to be shared in a structured way in order to obtain enough information to extend the continuous improvement.

The fact that the public administrations share this information enables us to progress from the single digital model, from the building level, to the city level. This is where the efforts of each of the participants in the digitalisation process acquires meaning.

This responsibility for digitalisation involves construction companies, architectural studios, engineering firms, etc. The disclosure of their information should be regarded as part of a link in the Life Cycle chain of a building/project/city.

At this point, we should be aware that one of the objectives of such digitalisation must be for our actions to generate less impact, for us to be able to expand with the growth capacity of the future generations in mind, as the Bruntland Report mentioned.

Digitalisation is ideal for us in meeting these objectives. The current complexity of the impact analysis, during which we may manage more than twenty environmental indicators, makes it difficult to be aware of all the environmental impacts caused while at the same time provoking our decisions. When proposing building work, we’ll really be able to identify whether it is sustainable, not only in terms of the present of these decisions, but also their future: the lower the potential global impact, the better the waste management, the lower the water consumption, etc.

Applying the concept of the Life Cycle of a project, we’ll begin to work with the information on all its phases: design, construction, use and deconstruction. We’ll be able to use all the collected data to improve the impact predictions. For example, not only will we be able to estimate the environmental impact of our buildings (construction or civil work, energy consumption, materials, CO2 emissions) more accurately, we’ll also be able to determine, with the help of Big Data analysis and artificial intelligence, which use profiles are the most appropriate, which orientations are the most beneficial in accordance with the aforementioned use profiles, which kinds of constructions are most easily dismantled and have less impact, depending on their locations, what product needs will exist in a specific area, what the capacity for growth based on existing resources will be and so on.

Obviously, this digitalisation process requires us to speak the same language. The data must therefore be shared and disclosed in the most standard formats possible.

Visualisation of data on cities. MIT Open Documentary LAB. POV Company. Docubase

Disclosing and sharing the data will not only help us, it will also help others to learn from us. And vice versa, in other words, “I can work in the project phase, and another technician, unknown to me, can work on the future use, potentially reporting what aspects have not been properly covered in the design”. All those involved in the construction Life Cycle will thus not only work for themselves, but also for those involved in the other time phases.

We must encourage a work structure which is increasingly collaborative. Cooperation greatly helps to improve society and therefore, to build, rehabilitate, exploit and deconstruct in a more efficient manner and with a lower impact, in other words, a more sustainable impact. This brings us to the third level of digitalisation, data processing. This gradual digitalisation process will lead us to obtain a huge amount of data that we must be able to turn into information.

The great advantage at this point is that the new management of such data, commonly known as Big Data, leaves no data out, unlike traditional data management. It analyses everything and then filters the information, refining it in a way that ends up answering questions which have never been asked before. It will thus be able to establish relationships which, in accordance with human logic, would never have been generated. Regarding this aspect, we’re starting to see examples of large data management companies. Without looking any further, Amazon has already stated that it can send a purchase before the user has placed the order.

On the one hand, we’ll have Big Data analysis, but also artificial intelligence. In the latter case, the experience, not of the programmers but of the technicians who thoroughly understand the construction process, will be key when it comes to creating really smart intelligence. From my point of view, one of the challenges is to train technicians to suitably convey and programme their knowledge, otherwise it will be difficult to achieve it.

In my opinion, there is a last level. It involves the transmission of the results and the users’ relationship with this whole new digitalised world. I’m referring to the usability or the ability of the user to interact with all this data, as we aren’t prepared to absorb so much information. There are cases in which all this information is not humanly digestible and, therefore, mechanisms for communication with the end user should be designed and validated. We should consider systems which only provide access to what is necessary in each case so that the rest of the analysis remains in the background, waiting to be used in other situations. Similarly, we must work on understandable visualisations which simplify the transmission of the information.

According to Peter Drucker (the father of modern management), long-term planning is not thinking about future decisions but rather about the future of present decisions. The application of the Life Cycle Analysis concept is fully aligned with this vision. The collection of information by means of digitalisation and the analysis we carry out on it will enable us to identify the ability we have to predict our future. And this capacity will only be possible if we have as much information on our activity as possible. What is not analysed can’t be predicted.