About four-fifths of the Dutch port is below sea level. As Paul van Roosmalen, the city official overseeing sustainable public real estate, puts it: “The water comes from all sides” – the sea, the sky, the river and ground water. “It’s always been a threat.” But he also sees an opportunity to use a marriage of technology and green design to elevate the role of rooftops in managing Rotterdam’s water pressures. 

While typical green roofs function like sponges and look like gardens, Rotterdam is working with public and private landlords to develop a “green-blue grid.” Instead of simply fitting out roof areas with plantings, these spaces can also be equipped with reservoirs or tanks to retain excess flow – blue roofs. The tanks, in turn, are equipped with electronic drain valves that can be opened and closed remotely, in some cases via a smart phone app.  

“The problem,” says van Roosmalen, “is that when they’re full, they’re full.” The city’s vision, he explains, is to develop a system for coordinating the water levels in these tanks to help manage sewer capacity. The idea is to link the valve control devices into a grid of blue roofs that function, in effect, like a dispersed network of storm water reservoirs. When there’s rain in the forecast, the reservoirs can be drained automatically. Then, during heavy weather, they can store rainwater, reducing pressure and flooding in the sewer system.  

While Rotterdam’s blue-green grid is still far from completion, it represents an example of how a set of digital sensing technologies can be potentially harnessed to produce a smart city solution to an urban sustainability problem.  

The technological lynchpin in Rotterdam’s strategy has been the installation of a highly sensitive weather radar on the roof of the city’s tallest building. The device is capable of detecting rainfall 16 to 20 kilometres away. Remotely operated blue-green roof control systems can be programmed to dynamically respond to those forecasts and release water that sits in the reservoirs. (A similar project, the Resilience Network of Smart and Innovative Climate Adaptive Rooftops, or Resilio, is underway at several Amsterdam social housing complexes.)  

As of 2021, Rotterdam officials were testing a pilot version of this grid. To scale it up, the city has to figure out how to co-ordinate with Rotterdam’s water board, which manages the sewer infrastructure, as well as property owners. The strategy potentially complements other water management planning moves, among them retrofitting public squares with “rain gardens” – i.e., clusters of water-absorbing shrubs and perennials planted in a small depression in the ground. “Instead of making bigger sewer pipes, we made a choice to invest in redesigning public space in a way that contributes to a nicer, better, more attractive district,” Arnound Molenaar, Rotterdam’s chief resilience officer, told Thomson Reuters in 2019.  

Van Roosmalen adds that a green roof can absorb about 15 milometres of rain per square-metre, whereas a roof with a reservoir can retain 10 times as much. The city’s goal is to convert one million square metres of flat roofs to include water retention systems and solar panels. Aggregated across even a portion of the city’s flat roofs, he says, “it’s a tremendous amount of water.” 

The Netherlands’ climate policies reflect a sense of urgency, given its exposure to sea level rise and flooding on rivers that flow into the country from the east. For that reason, both adaptation and mitigation have been central to the country’s plans for future-proofing its cities.   

Rob Schmidt, a sustainability policy expert with the City of Rotterdam, points out that the Netherland’s nine largest city-regions collaborate to develop and test approaches and technologies. “We learn from each other how to cope with these so-called smart city projects.” Each city has adopted a policy area: Rotterdam is focused on climate adaptation; Amsterdam, circular economy; Eindhoven, low-carbon mobility and energy transition, and so on.  

The national government has launched an Urban Agenda that involves negotiating “city deals” many involving smart city projects that typically include multiple partners, including research institutions. “Our approach is focused on the opportunity and finding everyone you need to get to a solution,” says Urban Agenda program manager Frank Reniers. “You put them in a room and try to innovate your way out of the problem.” 

“We learn from each other how to cope with these so-called smart city projects.”

-Rob Schmidt, a sustainability policy expert with the City of Rotterdam

The Netherlands wasn’t always so collaborative. According to Frank Kresin, dean of the Faculty of Digital Media and Creative Industry at the Amsterdam University of Applied Sciences, Amsterdam in the late 2000s and early 2010s “was doing everything in its power to become `smart.’” The city’s appetite for tech drove a great deal of investment in automation and digitization.  

But the infatuation with these corporate solutions, Kresin wrote in a 2016 study, “had some flaws,” including the risk of excessive surveillance and an unquestioning embrace of the idea that the smart city was “a machine that needs to be optimized, with no consideration or understanding of the organic reality. It wants to maximize efficiency and avoid friction, so it simply and non-negotiably imposes top-down, non-transparent technological solutions.” 

Kresin wasn’t the only one concerned about this drift. Beginning in the mid-2010s, citizens groups, entrepreneurs and academic institutions pushed Dutch policy-makers and companies to swap out the top-down approach in favour of a more grass-roots philosophy that features extensive public engagement, citizen-science projects and applied research.  

“The big threat is loss of autonomy,” says Jan-Willem Wesselink of Future City Foundation, a Dutch network of municipal agencies, civil society organizations, universities and technology companies seeking to promote a democratic approach to smart urbanism that aligns with a U.N. social development goal (#11) about resilient, sustainable and inclusive cities. “Does Google or some other company decide how you use the city?”  

Kresin describes one early effort at broadening the conversation. In 2014, Amsterdam Smart City, a tech incubator, distributed several hundred “smart citizen kits,” which provided rudimentary sensors to allow people to perform environmental indicator tests on water and air quality around the city. Their findings were fed to the city. While the readings fell short of research-grade data, this experiment in citizen science attracted many participants, generated upbeat media coverage and, in a few cases, led the city to clean up local beach areas. Its popularity also inspired Kresin and some colleagues to establish the Amsterdam Smart Citizens Lab, where civil society groups, academics and government officials work together to find solutions to other urban problems.  

The distribution of the kits “was a surprisingly successful project,” says soil chemist Gerben Mol, a resilient cities researcher at Amsterdam’s Advanced Metropolitan Solutions Institute (AMS), a university-municipal government joint venture established to conduct more formal applied urban research.  

In recent years, a growing number of Dutch city-dwellers are finding venues to engage in local conversations or projects about how to put urban data and technology to work in addressing the problems they see in their communities – in effect, a cultural, as opposed to corporate or bureaucratic, response. One example: an AMS project that created a composite out of a glue-like bacterial residue and de-contaminated wood fibre culled from septic waste (i.e., used toilet paper). A potential application is being tested to use this composite as a binding agent in road asphalt.  

There are other more traditional tech ventures, such as Amsterdam Smart City, an incubator with numerous public and private partners, all working collaboratively to benefit the city. Community manager Nancy Zikken says the City of Amsterdam has “embraced” TADA.city, a network of European organizations that have pledged adhere to six core principles for digital city initiatives (inclusive, locally focused, controlled by residents, monitored, transparent and broadly accessible).  

She also says that Amsterdam Smart City screens applicants, such as start-ups, to ensure their proposals align with broader policy goals and have what Zikken calls “social value.” As an example, she cites a firm that recently pitched a parking app but was rejected because it would likely encourage car use in a congested city that wants the opposite. “Most of the companies we’re working with really do see the value of incorporating citizens and using the wisdom of the crowd.” 

In Rotterdam, city officials, who are driving the blue-green grid initiative, are also using public education, open houses and other engagement tools to promote these projects, many of which will be installed on privately owned dwellings, using private capital, if the strategy is to attain sufficient scale to make an impact.  

Rotterdam, interestingly, hasn’t created financial incentives. Rather, in discussions with private property owners, Paul van Roosmalen says his team stresses the benefits and explains the options for what’s possible, for example combining a roof-top reservoir with solar. “They can pick what they think would add to the quality of their specific land,” he says. But there’s also a more urgent appeal, too: “You can save your city from drowning.”  

Adapted with permission from Dream States: Smart Cities, Technology and the Pursuit of Urban Utopias (Coach House Books, 2022).  

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For several years, the so-called HVAC industry – heating, ventilation, air-conditioning – has been turning out increasingly sophisticated programmable thermostats with a range of features designed to allow users to adjust a home’s temperature automatically (including smartphone apps that let users make changes remotely). However, the promised energy reductions and related savings associated with the set-and-forget features go right up the chimney when an occupant decides the dwelling is too hot, too cold or too stuffy, and intervenes. Depending on the device, the settings may not revert, paradoxically enabling all the carbon-wasting inefficiencies these devices were meant to prevent.

Yet with the advent of sophisticated cloud computing, artificial intelligence (AI) analytics and internet-connected sensors, some companies in this market, like Toronto-based Ecobee, are creating smart thermostats that continually readjust temperatures based on incoming real-time data from occupancy and humidity sensors, exterior temperature readings and predictions based on historical patterns of user behaviour drawn from tens of thousands of wirelessly connected thermostats.

Last summer, Ecobee added one more element through its new Peak Relief pilot program launched in partnership with several thousand customers. The company’s AI algorithms allow its thermostats to dynamically adjust to the time-of-use energy pricing policies now in place in Ontario, California and Arizona. Fatima Crerar, Ecobee’s director of social impact and sustainability, says the analytics also enable the company’s thermostats to learn how well a given house holds heating or cooling, and to set temperatures accordingly, especially when no one is at home.

Since 2016, Ecobee has adopted a policy of making anonymized user data available to researchers (customers have to opt-in) in order to suss out new insights about energy consumption. “It feels like a values alignment,” Crerar says. “Ecobee wouldn’t be here if we didn’t hang out with scientists.”

In fact, one team of University of Toronto and University of Carleton researchers is using data culled from over 70,000 active Ecobee smart thermostats over three and a half years to search for patterns in a huge tranche of granular operational data, such as run times and set points.

According to doctoral candidate Brent Huchuk, an HVAC expert, the team (which includes engineering profs Scott Sanner and William O’Brien) analysed the data using AI algorithms to understand when and why users tend to hit override. The idea is that this information can give the devices additional predictive chops, for example, by automatically turning up the thermostat just enough on cold days based on observations about when an occupant is most likely to override the controls.

These insights, Huchuk says, allows the technology to “pre-adapt.”

Such applications hint at the role AI and machine learning will soon play in the broader world of low-carbon, smart building design. Climate change experts estimate that buildings generate about 40% of all emissions, and HVAC systems account for up to half of a building’s energy consumption (the rest goes to lighting, other electrical systems, etc.).

There are a growing number of engineering and architectural innovations for mitigating building-related emissions, including passive design (e.g., making use of building orientation, insulation, materials and other sources of ambient heat or cooling), various heat and cooling recovery systems (e.g., heat recovery pumps attached to drains or air vents), and emerging technologies like electrochromic windows (a.k.a, “smart glass”), whose tint automatically adjusts to sunlight intensity to prevent excess solar loading within west-facing condos, for example.

Increasingly, sensors powered by AI and connected to the Internet of Things are becoming crucial tools in this narrative.

The federal government’s 2016 emissions reductions plan in 2017 incorporated a smart buildings strategy. Since it was released, researchers at Natural Resources Canada have begun testing various AI-based projects that draw on the data generated by smart buildings, according to an NRCAN spokesperson. “While the uptake of AI techniques has been somewhat slower in the world of buildings than in other fields, the potential is significant.”

For example, AI applications in highly automated suite-based HVAC systems can draw on historical patterns and other sources of information to model user behaviour, says Kim Pressnail, a University of Toronto civil engineering professor. He cites the case of apartments in new condo towers, which can be notoriously difficult to heat and cool properly due to their large glass windows.

Researchers and design firms, he says, are now working on a two-step process for significantly improving the thermal controls in these apartments. “It’s not glitzy but it makes a huge difference in how buildings perform.”

The first step, he says, is to create air-tight units so the internal heating and cooling systems within each apartment can be regulated properly, including with fresh air ventilation. Then, with occupancy sensors that allow smart thermostats to learn how the residents come and go, these AI-based systems can be “trained” to come on and shut down automatically, with significant potential energy savings. “It sounds simple, and it is,” he says. The payoff, Pressnail adds, isn’t just about reduced energy bills and emission reductions; the units and potentially entire buildings become less expensive to operate and more comfortable to be in. “An AI building will be worth more in the marketplace.”

In fact, proof of Pressnail’s prediction is already visible in other corners of the real estate world. Universal mCloud (MCLD: TSX Venture), a publicly traded Vancouver clean tech firm, has developed cloud-based AI systems designed to improve the energy efficiency of commercial buildings like fast-food restaurants, bank branches and other retail stores, including those operated in Canada by Telus. Unlike commercial office towers, observes Dave Weinerth, president of mCloud’s smart buildings division, many of these structures are operated by landlords who aren’t especially sophisticated about their energy consumption.

In the past few years, mCloud has installed WiFi-connected thermostats and sensors in these modest structures, with the operational data constantly being uploaded to a cloud-based system. There, AI algorithms will optimize temperatures and set points by constantly comparing against historical performance while factoring in exterior temperatures, occupancy levels, and so on. The combination of the wireless sensors and the AI analytics can also alert landlords when the performance of their HVAC systems, which are generally situated on the roofs of such buildings, are beginning to flag and require preventative maintenance.

The savings aren’t trivial: For a modest 3,500 square foot fast-food restaurant that spends $20,000 on its HVAC-related energy expenditures per year, mCloud claims its optimization technology can slash that figure by 15-20%, which represents both a financial savings and a move towards a zero-footprint building.

Aggregate the savings from the thousands of small commercial buildings lining North America’s suburban arterials, and the scale of the emission reductions related to just this one AI application becomes apparent.

“We’ve got to do better with buildings because of climate change,” says Pressnail. “The jury [on this issue] isn’t out. It’s returned its verdict.”

John Lorinc is a Toronto-based journalist and author specializing in urban issues, business, and culture.

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