Introducing the Advanced-Infrastructure Toolbox
Overview and History
From the time ancient humans first abandoned their nomadic ways and began to construct permanent shelters, society and individual quality-of-life have been both bound and enhanced by the technical proficiency of civil engineers---their ability to invent and apply tools and technologies as new challenges arose. During the course of history, these engineering tools naturally evolved from the groma used for surveying
roads in ancient Rome, to the slide rules that helped humans land on the Moon, to the spreadsheets and computer-aided-drafting tools used by civil engineers today. As a result, the Civil Engineering Toolbox of this generation is vastly different than the toolbox of my grandfather's generation. The toolbox of my grandchildren will be vastly different still - of this I am convinced. This post is Part 1 of an extended series dedicated to exploring this next logical evolution of the Civil Engineering Toolbox. The overall purpose of this series - and this website as a whole - is to introduce what I affectionately call the Advanced Infrastructure Toolbox, to define the various tools within the toolbox, and to explore the profound impact these tools will have on the future of civil engineering and infrastructure management.
What exactly is the Advanced Infrastructure Toolbox?
In order to achieve long-term sustainability, our infrastructure systems and the processes to design, build, and operate those systems must evolve. They must become more data-rich - able to continuously monitor their conditions, model and store the collected data for real-time and future use. They must become more intelligent - able to perform self-assessment and support proactive decision making that improves their performance, increase their life spans and reduce life-cycle costs and impact. They must become more green - such that we are confident that Earth’s resources are being used at a rate at which they can be replenished. By necessity, our infrastructure systems will evolve to become advanced infrastructure systems. The tools by which we reach this level of technological advancement essentially comprise the Advanced Infrastructure Toolbox.
In general, I tend to think of the Advanced Infrastructure Toolbox as an add-on package to the traditional Civil Engineering Toolbox. These tools are not intended to replace the traditional tools of civil engineering. Rather, they have the potential to enhance them greatly. As the cost of real-time sensing technology decreases and the volume of information at our fingertips increases, the future of civil engineering and infrastructure management will increasingly involve information technology, advanced numerical and computing techniques, artificial intelligence and other exciting emerging technologies. Hence, the Advanced Infrastructure Toolbox.
What Tools are Included in the Advanced Infrastructure Toolbox?
Although these definitions are subject to considerable overlap and interpretation, I tend to divide the Advanced Infrastructure tools into four (4) broad categories, illustrated below:
I call this the Advanced Infrastructure Pyramid. As the form suggests, decision support systems are built upon established knowledge discovery and management systems, which are built upon data management systems, which are built upon raw data. Now, for those of you who are familiar with the growing field of knowledge engineering, it is no coincidence that the Advanced Infrastructure Pyramid generally follow the popular Pyramid of Wisdom model, illustrated below:
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In order to better understand the Advanced Infrastructure Pyramid, therefore, it may
be helpful to make a direct comparison with the Pyramid of Wisdom. The D-I-K-W heirarchy of the Pyramid of Wisdom are best described by Bellinger, Castro and Mills (1), which is summarized below:
| Pyramid of Wisdom | Advanced Infrastructure Pyramid |
|---|---|
| Data Data is raw. It simply exists and has no significance beyond its own existence. It can exist in any form, usable or not, and has no meaning of itself. It is generally devoid of context and reveals nothing about its identity or its relationship with other objects. |
Sensing and Data Acquisition: The advanced infrastructure system utilizes advanced sensors and continuous state monitoring devices to extract raw data from the natural world. Once the data is acquired, it may be processed, organized, stored, queried and leveraged for future application. |
| Information Information consists of data that has been given meaning by way of relational connection. It relates to description, definition, or perspective - in other words, it answers the questions who, what, where and where. Generally, it does not provide a foundation for why the data is what it is, nor an indication as to how the data is likely to change over time. |
Data Management In order to be useful, raw data is organized so that access and retrieval are easy and reliable. In advanced infrastructure systems, databases and data models provide this level of functionality. Flat-file and relational databases are still popular in engineering applications today. However, in order to meet the infrastructure management challenges of tomorrow, we will have to move increasingly towards newer and more robust data management strategies, including geospatial information systems (GIS), building information models (BIM) and object-oriented (OO) models. |
| Knowledge Knowledge is the collection and organization of information, so that we may better understand its intent. In order to become useful, information must generally be analyzed, evaluated, weighted and filtered, in a process that traditionally requires significant human judgment, practical experience. It should be noted that this process is also heavily dependent on context, and so information from past scenarios may have substantially different significance and value in future scenarios. |
Knowledge Management For the reasons listed to the left, information alone does not help infrastructure managers and engineers make critical and difficult decisions. Decision-making requires knowledge (and ultimately wisdom). Advanced infrastructure system, therefore, strive to capture, represent and store the insight and previous experiences of the collective masses. This is perhaps the most challenging aspect of advanced infrastructure management and it is at this level that advanced infrastructure systems departs most significantly from traditional ones. Many applications that engineers use today do, in fact, implement some type of stored knowledge. Structural engineer design software, for example, typically perform code checks to ensure that the proposed design meets established engineering criteria. However, the predominantly numerical and logical format this type of knowledge is relatively easy to code in a design software program. Knowledge management in an advanced infrastructure system, on the other hand, can be considerably more complex and subjective. Instead of dealing with fixed, numerical and logical knowledge - as in the structural design example - advanced infrastructure knowledge systems may have to account for partial knowledge, fuzzy and probabilistic knowledge, semantic knowledge, or even knowledge that is learned "on-the-fly". Furthermore, it may have to do so in varying spatial, temporal or combined contexts. |
| Wisdom Knowledge does not provide for, in and of itself, the ability infer future knowledge. To correctly answer such a questions requires understanding and a basic appreciation of "why". Through understanding, we synthesize new knowledge and gain wisdom. Unlike the previous levels, wisdom asks questions to which there is no easily-achievable answers, and in some cases, to which there can be no humanly-known answer, period. Wisdom is therefore, a process by which we discern between right and wrong, good and bad, and ultimately make decisions. |
Decision Support Wisdom is a uniquely human quality - one not easily obtained and therefore highly revered. As such, many would argue vehemently that computer systems can never possess true wisdom. I agree with this assertion, and so I prefer the phrase "decision support" when speaking in the context of advanced infrastructure systems. After all, humans are ultimately the ones who make the hard decisions - computers can only lend support. Decision support systems vary considerably in their design and objectives, and fall into numerous broad categories. The following are just a few general uses for decision support systems:
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What to Expect in Future Posts in This Series
The future posts of this series will attempt to break-down and explore the above-mentioned concepts in greater detail. In general, each individual post in this series will focus on one specific technology, and how it relates to civil engineering and the concept of advanced infrastructure management. The posts will include case studies, practical guidance for adopting these technologies in the real-world, and resources about where the reader can learn more. Future topics include radio-frequency identification (rfid), fiber optic sensors, computer vision, genetic algorithms, neural networks, building information models (BIM), augmented reality, the semantic web, and many more.
As a final note, although the nature of advanced infrastructure methods tends to be highly technical and somewhat abstract, my overall goal is to reach out to the widest possible segment of curious-minded engineers, infrastructure managers and policy-makers. Therefore, my general intention will be to focus more on the practical application of these advanced infrastructure tools, their potential capabilities and limitations, and to provide information about how the reader may learn more and more easily adopt these technologies to solve real-world problems. Enjoy.
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