The Geospatial Dimensions of Intelligent Infrastructure
The concept of intelligent infrastructure involves the combination of sensors, network connectivity and software to monitor and analyze the inputs for more efficient operations. This concept meshes nicely with advancements in geospatial technology that are moving toward more real-time data inputs, 3d visualization, and the ability to track change over time. The first-generation of geospatial tools have largely addressed asset tracking, answering what is where. Intelligent infrastructure requires the creation of detailed models of our networks, allowing us to answer how and why. The evolution from a static and passive network to a dynamic and reactive network holds great promise for improved efficiency, and geospatial technologies play a vital role in realizing the vision.
Defining Intelligent Infrastructure
The technology triad that makes intelligent infrastructure possible is sensors, network connectivity and software to monitor and analyze complex networks. The sensor component collects operational detail over time as well as providing real-time inputs on current conditions. The network connectivity ensures the flow of information between systems, other sensors, and practitioners. The software component provides oversight and analysis, integrating insight from various systems and personnel. The approach integrates the management of multiple processes for more collaborative and multidisciplinary workflows. Intelligence is constantly improving from such a system of systems through incremental process improvements that are informed through constant monitoring and analysis.
The idea of intelligent infrastructure has been around for a long time in one form or another. Early forays into real-time monitoring of systems include industrial control systems such as SCADA. This newer concept of intelligent infrastructure advances that vision through technology innovation to enable us to go beyond simply monitoring. Instead of the more passive approach where alarms signal when inputs exceed accepted norms, intelligent infrastructure is a more holistic approach that provides a greater understanding of the interconnectivity of systems and the implications of events through a detailed digital model.
Supporting Trends in GIS
The move toward intelligent infrastructure comes with a need for transformation on how software tools model our world, how they handle increasing quantities of data input, and how they analyze and help predict performance of our infrastructure in response to our changing world.
In the realm of mapping and modeling there is historic division between those that use computer-aided design (CAD) software and those that use geographic information systems (GIS), but that division will need to come down in order to realize the full benefits of intelligent infrastructure. Increasingly, each of these tool sets are addressing this gap, by expanding their own functionality and enabling interoperability between the different data and models.
The advent of building information modeling (BIM) provides a way to capture and catalog all of the components of a building in a way that can yield different reports regarding the cost and performance of a building. BIM brings intelligent modeling to the CAD world, with a greater understanding of building, facility, and network performance. Combining these detailed models with the larger modeled geography within GIS provides context for this infrastructure within the natural world.
There is growing talk of the concept of GeoDesign, where tools to sketch and plan are informed by the spatial intelligence that are contained in the GIS. This ability to design within GIS will be tuned to specific planning processes. GeoDesign hopes to achieve a deep understanding of place that allows us to make optimal land use plans, and to build communities and systems that are well tuned to their environments.
In order to design and visualize this concept of intelligent models of infrastructure and the landscape, we’ll be required to move beyond 2D abstractions of our world toward full 3D representations. Creating our models in three dimensions provides a better means to understand our surroundings, to add real-time simulation to show the inner-workings of our built environment, and to communicate plans on changes to our world. The three-dimensional view provides a more accessible and inclusive model, and with an open and interchangeable 3D model, we can effectively break down the barriers between different design tools and systems.
The next step beyond the intelligent model is the ability to simulate change over time within the model. This capability is essential to the realization of intelligent infrastructure, because without the captured performance of our infrastructure we can’t build or exploit intelligence about our built world beyond the day that it was created.
New Workflows Focus on Process
With more intelligence within models, the workflow between and across disciplines becomes more inclusive. A greater amount of collaboration will naturally follow when a common system and model are used.
The design, engineering, operation and maintenance life cycle of infrastructure has traditionally dead-ended at each of these phases, because the intelligence has been trapped in a paper drawing rather than a model. Intelligent models create a pathway for sharing intelligence from inception of the infrastructure all the way through its lifecycle. With constant updates of the model to reflect changing conditions, the model becomes more detailed and useful as time goes on.
Flexible systems are the key toward unlocking multiple uses from the same data and models. The current enterprise-grade capabilities of GIS make great use of central data repositories and the Internet to deliver data and services that serve specific business practices. Flexibility provides the ability to tailor to both specific process workflows and to fit different steps within complex cross-disciplinary projects.
The creation of flexible systems and more inclusive models fosters more holistic thinking where we begin to better understand the sum of the parts or the impacts of individual processes. The big picture becomes much more accessible. In this new integrated solutions ecosystem for intelligent infrastructure, the need for experts that can create more inclusive models and synthesize model performance will grow greatly.
There are a number of information technology trends that are spurring the move toward intelligent infrastructure.
The “Internet of Things” is upon us, where ubiquitous network connectivity provides a means for sensors or devices to communicate. The ability for each sensor or device to have their own IP address adds a two-way communication that goes beyond reporting on current conditions. This communication ability creates a rise toward the semantic web, where machines understand the meaning of information.
The great explosion of social networking creates entirely new interactions between friends and families, but also among colleagues and communities of interest. The use of these social networking tools provides different connections where groups create their own monitoring and reporting channels. With social networking there’s the advent of humans as sensors that self-organize, self-monitor, and automatically aggregate information.
The open architecture of Internet-based systems have given rise to dashboards and other tools that synthesize information for better visualization and understanding. Dashboards combine inputs and read-outs to gain a better picture through the visualization of multiple data feeds in one view. Checklists and wizards are another means to walk users through the intricacies of a detailed analysis, helping eliminate human error where complex systems often require counter-intuitive thinking.
The global rise of the smart mobile phones has fostered a “Mobile First” mantra among software developers. There are far more phones than computers on a global scale, and the increasing capabilities of these devices will provide a whole new means of capturing and exploiting models of our intelligent infrastructure. One of the more promising capabilities is augmented reality, where our detailed models inform the world around us by presenting overlays on the device in the context of where the device camera is pointed.
Together, these technology trends provide a compelling vision for what our future will hold. The Internet of Things will enable our computing systems to act as independent agents to perform set tasks, greatly freeing up managers, and creating better-tuned processes. Our systems will factor in input from individuals through social networking tools in order to improve data and our understanding of the built world by harnessing input from the users of the infrastructure who have a vested interest in its performance. The increasing knowledge in our systems will giver rise to more machine learning, where our systems are tuned to take over more mundane tasks, and allow us to focus more on analysis. Augmented reality will eventually replace all map books, and provide a far greater efficiency for field workers by providing greater context for their work.
A number of challenges present themselves that are both technical and human resource oriented. The pieces to realize the vision of intelligent infrastructure largely exist now, but a varying degree of obstacles mean that the realization of this vision will take time.
While making the move toward more enterprise-scale systems, we once spoke of system silos that barred information exchange. On the human resource side of the equation there are entrenched business practices and departmental silos that hinder the interaction and collaboration of different work teams. There will need to be an embrace of more collaborative business process in order for the full rewards of intelligent infrastructure to be realized.
The quantity of sensors returning constant measurements will create a huge amount of data to be sifted and stored. We’ll need to develop entirely new tools and workflows in order to deal with this data deluge. The large IT vendors are salivating over the growing momentum for intelligent infrastructure, because the demands on the network and computing power will provide the next greatest leap in demand for computing. The level of research and development to tackle the storage and network bandwidth issues are growing rapidly based upon the anticipated increased demands.
With the data feeds from all quarters, and a great degree of different inputs regarding the current conditions across different scales of geography, there’s a great need for integration and synthesis capabilities to make sense of all the inputs. The ability to fuse different types of sensor information has seen a good deal of investment from the military space as defense missions have seen the utility in geospatial intelligence, and the need for a more enhanced common operating picture. Intelligent infrastructure is a different kind of common operating picture, but it will benefit greatly from investments that seek to improve data synthesis.
And perhaps the greatest challenge of all is the “Catch-22” at the heart of intelligent infrastructure for utilities. More streamlined and efficient operations are counter to the business model of a utility that profits more when it sells more. With greater conservation, there is less revenue. Mandates such as cap-and-trade could provide the incentive to shift to more efficient operations, by levying charges based on carbon emissions. With cap-and-trade, more efficient operations will mean fewer charges on emissions, effectively spurring the business benefits. Use-based pricing will also serve to put some of the burden on consumers, while ensuring a relatively stable rate base.
There is an overwhelming need across countries and the globe to invest in the replacement of aging infrastructure. The older infrastructure is underperforming, and in some cases unsafe. With the need to replace old infrastructure comes the opportunity to rethink how we do things. The promise of intelligent infrastructure to save money and improve performance provides a powerful incentive to at least consider this new approach.
The current state of the global economy has spurred a number of infrastructure investments as a means to stimulate jobs and spending. The funds have largely gone to existing operations, but a fair amount has been invested on intelligent infrastructure such as smart grid pilot studies. Funding this application of forward-looking technology helps to spur innovation, and to provide proofs of concept. These valuable studies should help spur further investments and further innovation.
Global change, including the implications of increased global temperatures, is driving a lot of contingency planning and policy directives. Utilities are being singled out for their high carbon emissions that contribute to this warming trend. We can expect more regulations to mandate more efficient power generation, with a greater emphasis on monitoring. Intelligent infrastructure puts the right systems in place for a more detailed accounting of operations, along with the tools to help oversee improvements.
Governments around the world are embracing open data distribution as a means of fostering greater transparency in communicating how taxpayer dollars are spent. This move toward a more transparent view of operations is likely to take hold outside of government circles, and it may only be a short time before citizens demand more insight into the inner working of utilities and the cause of rate hikes. With this demand for more information, it makes sense for utilities to formulate a plan now for data sharing. First and foremost is the need to make certain that the quality and accuracy of their data is good, followed by an audit to make sure they’re collecting the kinds of data that they would want to share.
Today’s students are gaining a much more collaborative and multidisciplinary education than previous generations. Over the past few years a number of new environmental and engineering schools have reorganized to provide new collaborative perspectives. Schools of environment and sustainability have combined a number of earth sciences disciplines, schools of engineering have increasingly incorporated design, and there are even a few schools specifically focused on intelligent infrastructure. This growing trend will feed new ways of thinking that will demand a more monitored network.
With the adoption of intelligent infrastructure there is a classic win-win-win benefit to people, profit and planet. The customer benefits with greater insight into their utility use along with the means to manage their consumption to meet their budget. The utility wins by becoming more efficient and delaying or reversing the need for major capital investments in new plants and capacity. The planet wins by gaining systems that are in tune with the environment, and by operations that focus on lower impacts.
The intelligent infrastructure models provide a much better handle on the details of operations that will improve worker safety, and help manage business risk. The better-managed utility will have incentive to innovate in order to draw down their resource use and maximize performance.
Intelligent infrastructure is an opportunity across all vertical markets within the utility industry. There is a separate flavor for each of these markets as the benefits of the combination of sensors, network connectivity, and systems to make sense of the data have a different focus for each. The concept has a great deal of momentum based upon its benefits. Geospatial vendors and practitioners can help speed adoption along by picking reasonable first-step deployments at minimal capital cost that provide immediate business benefits.