What does smart cycling look like?

I’m super interested in how we can leverage technology for sustainability, including mobility. But I also hate seeing people turn to technology to provide the solution when other options might be better suited. So a few articles caught my eye that are exploring smart mobility. They are all from a special issue of the Journal of Urban Technology called “Cities and Smart Technology: The Case of Cycling.” It was published earlier this year.

Before we get going, let’s quickly define what smart cities are. According to the Government of Canada, “a ‘smart’ city collects and analyses data interactions with, and usage of, public infrastructure to improve service delivery and user experience. This data is collected through connected sensors and individual devices which are part of centralized networks that manage service delivery.” Smart, then, is largely based on digital technologies’ role in improving city life. My first thought is that things like bikes aren’t a part of the smart city. This is raised by Behrendt (as cited by Nikolaeva & Latham, 2024). However, increases in bike-sharing services, smart traffic management tools that can react to cyclists, and other recent developments are changing this. I admit, I really like the road sensors that detect bikes and allow me to trigger the cross light (and am incredibly frustrated by the sensors that a bike won’t trigger, leaving me stranded at an intersection). I’ve also heard of cities that have installed bike counters to help demonstrate the use of cycling infrastructure.

In this light, I can see some elements of the “smartification” of cycling. However, I also see how this emphasis can compromise the sustainability of cycling by needing to build and power all of the technologies and the basic low-tech aspects of cycling. Nikolaeva (2024) discusses two case studies, Copenhagen and Amsterdam, to investigate the impact of ‘techno-solutionism’ on cycling. Techno-solutionism is the idea that within the framework of smart cities, urban problems are, by default, framed in a way that requires technology to be part of the solution. This kind of goes back to Maslow’s hammer: if you only have a hammer, everything looks like a nail. If your focus is on technology, then technology will solve every problem.

Fortunately, this isn’t what Nikolaeva found in the two case studies. Each one was focused on priorities independent of technology — travel time and use of existing space and infrastructure. However, there was also fear that as mobility is driven towards smartness, the low-tech nature of cycling may result in it being left behind.

Nixon and Schwanen (2024) propose that we need to expand what we view as smart. They recommend the integration of “community smarts” into planning active transportation and argue that its use can create smart mobility with or without digital technologies as the community sees fit. This arises from the examples they considered in London and Sao Paul, often completed with minimal budgets and targeted disadvantaged groups. Although technologies were used, they served the community smarts by increasing the availability of information, collecting data, or connecting with specific groups of people. They also raised the concern that the data collected by sensors often missed important understandings that had to be collected through conversations with the community themselves.

I like the idea of bringing community smarts into all smart city planning. To me, cities are about people and their environment, and I fear that making it about data and numbers will miss key components, such as the example from Nixon and Schwanen’s research about the failure of a smartphone app designed to improve safety for women in risky neighbourhoods that suffered from cultural biases about gender among the community.

Smart is fundable. It’s eye-catching and attracts investment. This is where the fear of cycling being left behind arises. I think there is also an element of time. We don’t like things to take time in Western culture. And data from sensors and devices can be collected much faster than through community engagement. When I talk with students about using generative AI, I talk about it as a tool that can support them, but they still need to share their voices, exercise critical thinking, and be creative. I feel like we have the same risk with smart cities, particularly when discussing things like cycling and walking. We can’t let the technology or the push for technology overrun what is actually smart in the conventional sense of the word.