Upon arrival at the station, I tapped on at the entry gate with my credit card, and made my way to the platform, where I consulted the digital signage for the next city-bound departure. Once aboard, I was able to connect to a WiFi hotspot for the duration of the 30 minute journey, after which I alighted, tapped off to complete payment and made my way to the event. All very normal activities for the average commuter - and nothing out of the ordinary among the 2.53 million trips collectively undertaken on any average school day in NSW.
Still, a lot has to go right consistently behind-the-scenes to ensure those millions of trips occur seamlessly.
Perhaps unsurprisingly, several elements of my journey - specifically the tap-on and tap-off, the train scheduling, and the ability to connect to wi-fi in-journey - lean on the same foundational technology.
When I tapped on at the gate with my credit card, a graph database ran anti-fraud and other credit checks on the legitimacy of my chosen payment method. Once on the rail platform, a graph database was managing the scheduling and sequencing of trains arriving and departing from the station. And once on the train, a graph database was helping to manage the configuration of the WiFi hotspots I was connecting to.
In one 30 minute commute, I encountered four different systems underpinned by graph database technology - and I wasn’t the only one that day to benefit from this technology’s existence.
The connected commute that graph technology enables is emblematic of the direction that city life is headed, yet is also the tip of the iceberg in terms of what’s possible when cities become truly connected.
This World Cities Day, it’s worth examining how the emergence and growing use of graph database technology is enriching the livability of cities both in Australia and farther abroad, what kinds of connected experiences are being enabled now, and what’s coming in the immediate future.
Data is redefining livability
Smart cities have been on the policy agenda for several decades. We’ve seen a number of examples domestically and overseas - Finland’s Turku being a prime example - where the interconnection of assets enables data-driven decision-making that can and does have a profound impact on a city’s planning and overall livability.
Cities get smarter over time by becoming more instrumented. Sensors produce greater volumes of data that, with assistance from graph technology engines, can be converted into actionable intelligence.
Transportation is an obvious win for connectedness: helping people to plan their journeys between two or more locations with real-time information about road conditions or passenger load on buses and trains.
Sensors and data intelligence also impact the timing of traffic lights and street lamps, for example. Increasingly, council vehicles are fitted with sensors or computer vision technology that can detect potholes or measure the strength of cellular connectivity as they move through different parts of the city, assisting with maintenance while identifying coverage blackspots.
These services generally are the domain of a handful of state or local government organisations. But livability can be greatly enhanced by also bringing in a range of other data sources that can collectively contribute to a more accurate composite picture of the livability of a particular location.
This could mean tapping data on heavy vehicle movements through a particular area, data from electricity infrastructure such as poles or smart meters, data from fibre optic sensors deployed as part of telecommunications or signalling infrastructure, and so on.
Cities are complex structures - shared spaces in which many service providers participate and collect their own data on their own assets. Individually, and disaggregated, these data sources are helpful to that service provider only. Collectively, if all the data-generating sources in a city are brought together into a kind of ‘data hub’ and analysed with a graph database, hidden patterns and relationships in this data can be uncovered. This can help to gain a much more granular understanding of how citizens experience the city, and all the different factors that both drive and impact the overall experience.
The next step beyond that is for intelligence not only to be actionable at a whole-of-population level, but also at an individual citizen level. This involves creating a more personalised view of government and city services for the individual, ensuring that city services can evolve to meet citizens where their needs are.
The intent is to connect individual citizens to the government services and benefits that they are eligible to receive. Just as cities are complex data-producing structures to manage behind-the-scenes, the same complexity is often present in the citizen-facing experience. Without assistance, it can be difficult to sift through all available data on services to find an experience that best suits a person.
The creation of a 360-degree view of citizens promises to show relevant services to individuals, ensuring they reach those that need them the most, which is the mission of governments everywhere.
