I'll be speaking today about the unprecedented growth at Toronto Pearson to set the context for what I'm presenting: existing and emerging ground transportation challenges as a result of this growth, and the new developments that we have in our plan in response. I'll also touch on transportation and technical challenges as far as regulatory and design implementation is concerned.
Toronto Pearson is experiencing a period of unprecedented growth. In 2016 we moved more than 44 million passengers. It's estimated that in 2035 we will move as many as 80 million passengers. A global hub status would be achieved should we meet that number of 80 million, and we would be in a group of airports—much like JFK or Heathrow—providing global connectivity.
Global hubs provide prosperity to the region in which they operate through job growth, foreign direct investment, and tourism. Keeping up with this growth within our physical facilities is difficult, and the expectation of the passenger is key. People have a choice about where they travel or which airport they choose to connect through. Our direct competitors are JFK, Detroit, Chicago O'Hare, and other airports that provide connectivity, such as Atlanta. Passengers have a choice of which airport they choose. We want them to choose ours.
One key deliverable to achieve that is to provide connectivity for the passenger using various transportation mechanisms to allow them to move freely and quickly through the facility from gate to gate, from check-in to gate, or from gate to ground transportation.
We'll increasingly rely on technology to move our passengers and their bags in an expedited fashion. We've explored the use of accelerating high-speed moving walkways, personal rapid transit vehicles—PRTs—and automated people mover systems to move people efficiently.
I have an example of this. I met a passenger who was travelling on Air Canada from Frankfurt. She was going to be travelling out to Calgary on WestJet. The distance from gate to gate was likely three kilometres. She travelled on various moving walkways, escalators, vertical transportation systems, the automated people mover or accelerated moving walkway, and she arrived at her gate in less than 30 minutes. That wouldn't have been possible without these technologies.
One thing I want to mention is that the high-speed walkways that exist at Toronto Pearson are unique. There are two of them in the world, both at Toronto Pearson. They're the result of a research and development project that we undertook with ThyssenKrupp in Spain to develop these high-speed walkways, which move at three times the speed of a normal moving walkway.
Yet the movement of people and goods outside of the airport is arguably a greater challenge and is more out of our direct control. Toronto Pearson is located within the second-largest concentration of jobs, the airport employment zone, and accounts for about a million trips per day. Of that, less than 10% is on transit. As the region grows and our traffic grows, transit becomes so important to preventing our roads from reaching critical levels, affecting the movement of airport employees, cargo, and passengers.
To ensure that Toronto Pearson is able to continue operating efficiently in serving our community, we have recently announced plans for a regional transit centre at the airport. The facility is strategically located to provide a missing link for a number of existing and planned transit lines that come close to the airport but don't actually connect. We're asking our government partners to connect these lines to this facility so that we can keep people and goods moving freely through the region.
We'll also be looking for technology to help solve problems. The transit centre could provide important connections in all directions, including important economic zones like the Kitchener–Waterloo corridor. However, we're looking at innovative transit solutions for passengers for that “last mile” from the transportation centre to the airport terminals.
This could employ the use of digital technologies, automated vehicles, or other emerging technologies. Existing emerging technologies, such as electric vehicles and autonomous vehicles, will require changes in road design and electrical utilities infrastructure. It is expected that as different types of technologies become established there will be a need for the integration of regulatory standards and design.
As an example, the UP Express connecting Pearson to Union Station's heavy rail system and the automated people mover system that connects the terminals to other elements of Toronto Pearson are on the same platform system. Nowhere in the world does this exist, to my knowledge.
It was an interesting exercise to integrate the regulatory framework that guides the safety of workers and passengers in the heavy rail system with a mature regulatory structure around automated people movers. Nowhere else do they exist on the same platform, in the same space, and in the same dynamic envelope. I think you can expect to see this more and more frequently as different technologies emerge, and there is a requirement for those technologies to be in the same space or a relatively similar space.
Some airports have begun integrating new transportation technologies and processes. As an example, Hartsfield-Jackson Atlanta International Airport, along with MARTA, the regional transit provider, partnered with Uber to provide critical connectivity to and from the airport.
As the airport operator, we invest in tools that we need to keep people and goods moving through our airport and our ever changing region. We ask government to support us and partner with us to ensure that Toronto Pearson, one of Canada's most important commercial assets, continues to operate efficiently and to flourish.
Thank you, Mr. Chair. I'd like to thank the committee for having me.
The objective of my presentation is twofold. First, I want to provide some context for the smart city concept. Second, I'd like to share the approach the City of Québec is taking. Those are the two elements I plan to address.
The City of Québec has a population of 532,000 people spread across a 454-square-kilometre area. More than 40% of the population has a post-secondary education. In addition to being more francophone, the population is older than the provincial average. The Internet use rate is above 80%, and the unemployment rate is below 5%. That is a quick snapshot of the City of Québec.
Now I'd like to talk about what a smart city is. The use of smart technologies to make a city's infrastructure and services more efficient and interconnected. You'll find countless definitions out there, but that is the one we chose to go with. As we see it, a smart city is a better-managed and better-performing city thanks to the support of information technology, or IT. It is not, however, the use of IT, strictly speaking, that gives rise to a smart city but, rather, the context in which it functions.
A variety of smart city models and references exist. A number of private firms have developed concepts, including IBM. In fact, more and more ISO standards are emerging in the area, namely, the 37000 series of standards.
The smart city concept has really evolved. It's something we, in the City of Québec, have been interested in for eight or nine years now. We began by exploring what a smart city was through joint research with Université Laval and research partners around the world. That gave rise to some very interesting findings.
It's important to understand the reason for wanting a smart city; that is a basic point. The issues facing the City of Québec are certainly not the same as those facing Mexico City, for instance, where air quality was the most defining element at the time of the study. That isn't necessarily the case in the City of Québec.
Implementing technology all over the place is not enough; sound choices governing its use have to be made. A smart city is built around the needs of its residents and partners, who are stakeholders in the city's development. That is the logic guiding our efforts.
Our efforts, in the City of Québec, hinge on the co-operation and engagement of a variety of business sectors. I am, indeed, talking about an overall approach. It is based on certain elements such as information gathering, data interconnectivity, and analyses. All of that helps us to understand what a smart city entails and how to turn that understanding into reality.
In the City of Québec, we sought to figure out why we wanted to become a smart city. We adopted two strategic directions. On the one hand, we wanted the city to be appealing to tourists and immigrants from all over the world. On the other hand, at the city level, we wanted to improve our performance as an organization, primarily to improve the quality of life enjoyed by residents, business people, and tourists.
In tangible terms, a pillar of the city's 2012 economic development strategy was innovation and creativity. One of the fundamental objectives is to evolve as a smart city.
The City of Québec's technology sector is made up of 540 companies and employs nearly 20,000 people, 2,000 of whom work in research. The sector generates $1.7 billion in annual revenues and encompasses 65 research centres, chairs, groups, and institutes. Clearly, economic development is the way to attract people.
Specifically, the city chose to focus on six key areas. We have services to the public. In the services we deliver, first and foremost, are basic services such as water, public safety, and communication and interaction with the public.
We have services to the public, such as garbage collection. We have water, transportation, safety, economic development, and buildings and infrastructure.
How does technology bring a smart city to life?
Those are the areas our approach is based on. Unlike other organizations, the City of Québec did not set up an administrative body, office or service for the smart city. Mainly, we chose to synchronize the various initiatives and monitor how the city evolved.
Of course, the smart city concept helped us to better understand the phenomenon and work with other entities. Our efforts have been recognized by organizations such as the New York-based Intelligent Community Forum. We had the opportunity to take part in a philanthropic challenge put on by IBM. We explored the issue of digital inclusion. Although less focused on technology, the idea was to determine where in our region Internet service was least accessible.
We were interested in figuring out how we could incorporate libraries in our service offering. Naturally, we held a number of discussions and consulted multiple articles on the subject. Our approach focused on six key areas.
Now I would like to share with you the projects that emerged.
The city wants to better plan its network of bike paths and has sought the help of residents. It developed an app, called Mon trajet vélo, to track the routes that cyclists take throughout the city and to better understand their overall travel patterns. Albeit a less conventional form of civic engagement, this information-sharing initiative sheds light on cyclists' movements and leads to better city planning.
In addition, a series of technology showcases give businesses the opportunity to use city data and work with the city to pilot business projects they are interested in launching. Also available is a collection of digital books. City residents currently have access to more than 7,700 titles, accounting for nearly 100,000 book loans.
The city's transit provider, Réseau de transport de la Capitale, known as RTC, developed an app to make travel easier. The city is one of RTC's largest shareholders. We are working with the company to improve the flow of travel using traffic signal preemption. Normally reserved for fire trucks, this mechanism allows for better traffic light synchronization.
On the open data front, in conjunction with other large cities in the province, the City of Québec contributed to the implementation of a common data portal. The data belongs, of course, to the public, so we provided access to certain data sets, which can be leveraged to build all kinds of applications.
I should stress that the first objective of becoming a smart city is to improve residents' quality of life and support the activities provided to them by the city.
Thank you very much for the opportunity to address the Standing Committee on Transport, Infrastructure and Communities on the issue of smart cities.
My research on smart cities is from a law and policy perspective. I have focused on issues around data ownership and control and related issues of transparency, accountability, and privacy.
The “smart” in “smart cities” is shorthand for the generation and analysis of data from sensor-laden cities. The data and its accompanying analytics are meant to enable better decision-making around planning and resource allocation, but the smart city does not arise in a public policy vacuum. Almost in parallel with the development of so-called smart cities is the growing open government movement, which champions open data and open information as keys to greater transparency, civic engagement, and innovation. My comments speak to the importance of ensuring that the development of smart cities is consistent with the goals of open government.
In the big data environment, data is a resource. Where the collection or generation of data is paid for by taxpayers, it's surely a public resource. My research has considered the location of rights of ownership and control over data in a variety of smart cities contexts. It raises concerns over the potential loss of control over such data, particularly rights to reuse the data, whether for innovation, civic engagement, or transparency purposes.
Smart cities innovation will result in the collection of massive quantities of data, and this data will be analyzed to generate predictions, visualizations, and other analytics. For the purposes of this very brief presentation, I'll characterize this data as having three potential sources. First, there are newly embedded sensor technologies that become part of smart cities infrastructure. Second, there are existing systems by which cities collect and process data. Third, there's citizen-generated data—data that is produced by citizens as a result of their daily activities and captured by some form of portable technology. Let me briefly provide examples of these three situations.
The first scenario involves newly embedded sensors that become part of smart cities infrastructure. Assume that a municipal transit authority contracts with a private sector company for hardware and software services for the collection and processing of real-time GPS data from public transit vehicles. Who will own the data generated through these services? Will it be the municipality that owns and operates the fleet of vehicles, or the company that owns the sensors and proprietary algorithms that process the data? The answer, which will be governed by the terms of the contract between the parties, will determine whether the transit authority is able to share this data with the public as open data.
This example raises the issue of the extent to which data sovereignty should be part of any smart cities plan. In other words, should policies be in place to ensure that cities own and/or control the data they collect in relation to their operations? To go a step further, should federal funding for smart infrastructure be tied to obligations to make non-personal data available as open data?
The second scenario is one in which cities take their existing data and contract with the private sector for its analysis. For example, a municipal police service provides its crime incident data to a private sector company that offers analytics services such as publicly available crime maps. Opting to use the pre-packaged private sector platform may have implications for the availability of the same data as open data, which, in turn, has implications for transparency, civic engagement, and innovation. It may also result in the use of data analytics services that are not appropriately customized to the particular Canadian local, regional, or national contexts.
In the third scenario, a government contracts for data that has been gathered by sensors owned by private sector companies. The data may come from GPS systems installed in cars, from smart phones or their associated apps, from fitness devices, and so on. Depending on the terms of the contract, the municipality may not be allowed to share the data upon which it is making its planning decisions. This will have important implications for the transparency of planning processes.
There are also other issues. Is the city responsible for vetting the privacy policies and practices of the app companies from which it will be purchasing its data? Is there a minimum privacy standard governments should insist upon when contracting for data collected from individuals by private sector companies? How can we reconcile private sector and public sector data protection laws when the public sector increasingly relies on the private sector for the collection and processing of its smart cities data? Which normative regime should prevail, and in what circumstances?
Finally, I would like to touch on a different yet related issue. This involves the situation in which a city that collects a large volume of data, including personal information, through its operation of smart services is approached by the private sector to share or sell that data in exchange for either money or services. This could be very tempting for cash-strapped municipalities. For example, a large volume of data about the movement and daily travel habits of urban residents is collected through smart card payment systems. Under what circumstances is it appropriate for governments to monetize this type of data?
My comments have only briefly touched on some of the law and policy issues regarding data in the smart cities context. I will be happy to address these issues, as well as any others, in the time allotted for questions.
It's a pleasure to be here. Thank you for the opportunity to speak to you.
I am the director of the Cambridge Centre for Smart Infrastructure and Construction, which is based in the department of engineering at the University of Cambridge.
We are slightly interesting for a research organization in that we're jointly funded, not just by the research council, but also by Innovate UK, which is the government's innovation funding arm. They normally give their money purely to industry, but in the case of centres like mine, they give it to universities to help us bridge the innovation gap between good research coming out of the university and its implementation in industry.
The reason they chose to fund an innovation and knowledge centre in smart infrastructure and construction was that they perceived there to be a market failure at the moment. There's a real opportunity with the sort of fourth industrial revolution and this huge burgeoning of the capability to sense things with newly invented sensors and to gather data to understand the condition of our infrastructure better, understand how well our designs perform, and get better value out of our infrastructure on behalf of the citizens.
However, the infrastructure and construction industry is being very slow at responding to this fourth industrial revolution. If we look at the manufacturing industry, particularly in Germany, they're pushing something called industry 4.0. They are really embracing the opportunity that sensor data gives them to understand their assets, to get better models of how they're degrading and, therefore, to offer different kinds of service models to their customers. In infrastructure and construction, certainly in the U.K.—and, actually I think it's fair to say, globally—we are far behind the curve on this. But there is a huge potential to deliver massive value to the public through better use of our infrastructure.
One of the challenges we have in the U.K.—and I suspect you have similar challenges in Canada—is that a lot of our infrastructure is very old. A lot of it was built in the Victorian era, and we have very limited information about it. If we're really lucky, we might have a drawing of a bridge that's 120 years old, but we don't know whether they built what they drew. We don't know quite what lies behind the abutment walls and so forth.
When we come to try to maintain these assets, we are really working in the dark, and we aren't doing a very good job as an industry of gathering our data in a consistent way so that we can use it to start to understand these assets and also to understand even our new assets and get better models for how we design them, construct them more efficiently and effectively, and then manage and operate them better.
The issue with that is as follows. The previous speaker talked about data being a resource. It's also an asset. What's tending to happen in the infrastructure and construction industry is that people are going and inspecting things, for example, going and inspecting a bridge, but the data isn't well gathered. It isn't well curated and it's not retrievable later on. If you then have a problem further down the line with that asset, it's very hard to look back and get value from that, to get good deterioration models, to get good understanding of how the condition of an asset is impacting its serviceability, and so forth.
There have been, however, some interesting steps forward in the U.K., partly through the setting up of our centre. We work with 40 partners in industry and government to demonstrate potential solutions. We've done everything from send our guys out onto construction sites in lovely luminous orange jackets to install sensors and understand how to interpret the data from that to understand the assets better through to working at an organizational level with asset management teams to look at how they structure their data, how they share their data, and enable them to get better use from that data. But we are very much in the foothills, I think, as an industry.
The U.K. government has made some interesting moves in this area. They decided about four years ago that, from the year 2016, any publicly funded construction project would have to comply with the requirements of what's called BIM level 2—that's building information modelling level 2—which is essentially a way of using 3-D, CAD-generated data and other kinds of data to collaborate around the design of something, but then also around the construction of it. You can use this BIM protocol to manage everything from the design through to the construction and potentially the handover of the asset.
That has really driven the industry to embrace this. Our industry is typically very conservative because it works with very low margins. It's heavily regulated for reliability, safety, and so forth. But if the government, as a client says, expects industry to deliver this, then people have no choice but to deliver it. That's enabled a big step forward in the U.K.
The industry is still a little nervous and struggles somewhat with the challenges of making sense of data. The big data arena that the previous speaker alluded to is a great opportunity, but it's also quite frightening, particularly if you're sitting in a contractor's organization and wondering how on earth you process it all.
One of the other challenges, certainly in the U.K. context, is that our supply chain is very segmented and so there are a lot of split incentives. If you have an organization that's responsible for building an asset, it's very hard for them to justify, in their own business case, investing in something that will bring benefits 20 years down the line in operation. At the same time, as a client, you might want that because 20 years down the line, you will still have your asset, your bridge, your tunnel, whatever it is, and you want to be able to use the benefits that would bring. So there's quite a challenge at the moment in the way the industry is structured and the way we carry out contracting. I'm afraid I don't know anything about the way contracts work in Canada, but these things are set up quite adversarially and, therefore, we're struggling to get the benefits over the whole lifetime of a project.
Then there is this challenge of getting data protocols. That will help to enable people to share data more easily, both between organizations that are given points in the assets' life, be that design, construction, or management, and also over the lifetime of the asset. Most assets will have several organizations responsible for them over the time they exist physically for 100 to 120 years, and we need to find ways that data can be passed from one organization to another.
The other interesting aspect that we're starting to focus on in the U.K.—and I'm involved in some of the standards organizations on this—is cybersecurity. I'll touch very briefly on this, but if people want more information, I can expand on it a bit later. The Centre for the Protection of National Infrastructure in the U.K. realized quite quickly when we started getting engaged with these BIM models—these wonderful 3D models or assets that we were plastering up all over presentations everywhere—was that we were inadvertently revealing a huge amount of information about pretty critical assets.
There's a major station in London called Victoria Station, which has several underground and overground lines running through it. It's also very close to Parliament, so there are quite a lot of parliamentary-related buildings around there. As engineers we were happily throwing up these BIM models rather naively and saying, “Look how brilliant BIM is. We can use it in these ways to manage construction and make sure we don't interfere with operations and so forth.” This chap from CPNI saw one of these presentations and said he could see three or four critical national asset components there that we really shouldn't be showing to anybody who happens to be able to get hold of a set of these slides. That has initiated a process of trying to bring in cybersecurity protocols and good practice around security at as early a stage as possible with these digital protocols we're using.
Just to make sure that we get over our naïveté—it was in the early days, and we got over our naïveté pretty quickly—so we can get the best use out of these maps—
Thank you, Madam Chair, and members of the committee, for the opportunity to present before you this afternoon. I'll try to keep my introductory comments brief.
My name is Sriram Narasimhan. I'm an associate professor in the department of civil and environmental engineering at the University of Waterloo. I'm also cross-appointed with the department of mechanical and mechatronics engineering for the University of Waterloo. There, I also hold the title of Canada research chair in smart infrastructure.
I received my Ph.D. in 2005 from Rice University in Houston, Texas. I joined the University of Waterloo shortly thereafter, in 2006. Prior to joining the University of Waterloo, I was employed with American Bureau of Shipping in the risk consulting division, in Houston, Texas. I'm a registered engineer in the province of Ontario.
With regard to a bit about what my students and I are doing in research, the overarching aims of my chair here at Waterloo are to understand issues surrounding infrastructure and to enable condition assessment of critical infrastructure, such as bridges, airport systems, and water distribution networks, primarily through the use of sensors and smart data acquisition systems and hardware. This is so that we can develop strategies to mitigate unanticipated failures in vulnerable and aging infrastructure and develop cost-effective maintenance and capital projects planning.
My research spans across the areas of structural dynamics, condition assessment of vulnerable infrastructure, and structure control. Most of my work in the context of my chair pertains to how best to extract pertinent information regarding the health of infrastructure from measurements acquired from sensors installed on structures and systems. For example, I'm working with my team of students and post-doctoral fellows in developing hydrant-mounted sensors that can effectively determine leaks and other disruptive events within varied water distribution networks. Similarly, we are working towards better understanding what measurements tell us are going to help aging bridges.
I'm partnered with several public and private entities in pursuit of our research goals. We are now witnessing an era of digital transformation, where our ability to measure infrastructure performance during operation using sensors and processors has far surpassed our wildest imagination from just a few decades ago.
The smart communities of the future are ones that will effectively utilize this explosion of technology for the betterment of the life of their citizens. For example, our ability to measure energy demands within a smart community will help us to better balance generation and storage. Our ability to assess the health of aging bridges using sensors will help planners to come up with maintenance and refurbishment plans, taking into account budgetary and manpower constraints. Such technology will also help us identify and repair leaks in water mains before they flood our streets and hospitals.
For us to realize the goal of smart communities, we should overcome the technical gaps and technological gaps to using this technology, specifically how best to infer knowledge from data and through investments that enable the adoption of this technology within communities.
In Canada, we have some unique challenges related to geography and weather constraints. Hence, we cannot expect manual inspections in remote areas to ensure structural integrity. In my role as a witness to this important committee, I can offer my perspective on where and how sensors can transform our lives and better balance budgetary constraints and aging infrastructure needs.
Just to help the others along as well.... This is synergistic with what this committee has been working on for past year.
When we look at the assets in our part of the world, such as the Great Lakes, the St. Lawrence, and the natural assets of our location in general; when we look at our other assets such as airports, the St. Lawrence Seaway system in relation to water, rail, short and main lines, spur lines and, of course, a road network; when we look at innovation, research and development, and technology; when we look at the private sector and the partnerships we're trying to create, we see that those are different pillars.
Now take it up a level, to the next level. We're working on a national transportation strategy. We're working on a smart infrastructure strategy, and there are many other strategies that the government and our partners in the House of Commons are working on in forming that strategy—and which is also a result of those pillars I just mentioned.
Now take it up to the next level and how it then relates to creating a smart city, community improvement and growth strategies, and therefore, proper—and this is the key part—infrastructure investments, and then, attached to those investments, proper asset management plans and financing plans. That's where I'm going with this question for you about what, then, are the key components for establishing all the above.
If I could go to the other two participants, I would appreciate your comments on that as well.