Smart cities are the new cities. Like their predecessors, these municipalities need money to run their services. With changing demographics and population habits, traditional revenue systems are drying up. For example, as more individuals choose Mobility-as-a-Service (MaaS) for personal transportation, fee-heavy byproducts from personal vehicle ownership, such as toll roads, are less lucrative. Instead, these cities must learn to monetize new technology, especially transportation technology, to profit from their services.
What is MaaS?
Mobility-as-a-Service, also called Transportation-as-a-Service, is the genre of private products that deliver mobility solutions as a subscription or fee-based service. Famous examples of these include Lyft ridesharing and DoorDash food delivery. Tools such as bikesharing and mass transit also fall into this category. While MaaS has existed since the era of stagecoaches, new companies applying this approach grew ubiquitous due to the ease of convenience, relative sustainability benefits and affordability. They primarily serve metropolitan areas but are making a name for themselves in smaller cities and even college towns: wherever highly mobile populations exist.
These systems have become commonplace with the advent of app-based technology and e-commerce. Lyft riders simply input a destination and push a button to get a ride; they pay with a simple ApplePay swipe. Fees required to use these products also tend to be cheaper than personal vehicle ownership. Younger generations don’t mind doing away with the complications of a car to deal exclusively with app-based purchasing and membership or subscriptions services that can be canceled at any time.
Public Opportunities for Monetization
As smart cities develop, their leaders need funds to pay for intelligent upgrades and to subsidize less profitable services, such as healthcare and social programs. However Lyft and other MaaS products tend to precede smart city infrastructure because they are easier to implement. MaaS services dry up revenue streams, such as toll roads, car taxes and other vehicle-affiliated taxes.
Luckily for smart city leaders, they do have one thing MaaS companies and other new tech companies need: data. By collecting the data to which they have ample access and then selling it, government bodies of these high-tech municipalities can fund their plans. However, monetizing a system also happens via hefty savings. Leaders can use technology to diminish the costs of services, lessening the need for subsidies. Here are three methods cities can use to stay in the black.
Creating and Updating Modern Infrastructure
The phrase “if you build it, they will come” is especially true for smart cities. As cities grow in intelligent capability, and AI tools such as machine learning and predictive analytics are applied to data stores, people will look for markets where they can sell their products. While it is always risky to implement new structures to preempt business, some infrastructure systems have low risk costs associated with their implementation. Consider the already available parking in a city. Imagine creating a cloud-based data log with detailed costs overlaying the city’s sectors and incidences of parking tickets populating the data. This information could then be sold to app-based parking tools or tow companies trying to sell their plans as MaaS to business owners.
Another place where cities could update is mass transit, which is usually controlled by public branches. Mass transit systems are divisive issues. In some cases, they are a burden, such as with the NYC Metro, which requires millions of repairs and subsidies to cover fares. In other cases, they diminish congestion, reduce the number of CO2 producing vehicles on the road and gain a profit.
Often, the key difference between viability is the modernization of the system. Public transportation with Wi-Fi on-board draws mobile-connected populations. Riders who can navigate train systems with mobile app-based maps for trips and use e-commerce options during checkout tend to rely on public transport. Interfacing with private companies helps raise the profitability. Helsinki, Norway, an intelligence-oriented city, interfaces many of their services to achieve a mutually-profitable relationship. For example, transit maps of Helsinki’s metro available on Google Maps push riders to other Google services.
As well, building or equipping the system with IoT-enabled sensors circumvents costly downtime. These sensors can collect data about runtime, environmental conditions and typical behavior. As soon as risky circumstances arise, or the data indicates an atypical situation, these sensors can alert transport authorities. Maintenance can be completed in hours or less, instead of days required by total failures, catastrophic or otherwise. Companies will feel more comfortable relying on government infrastructure if there is a plan in place to predict issues.
Leveraging Environmental and Infrastructure Data
Governing bodies have unparalleled or even exclusive access to roadways, bridges, climate monitors, certain transportation properties and population activities. Historically, the data collected was stored for historical and liability reasons. However, new IoT and edge network devices enhance and improve data collection, making it useful for analysis, predictive services and monetization. This data can be sold to private companies for use in their products and services.
Climate data is one of the more specific examples in this category. While national and non-profit bodies have publicly available weather data, cities often have private services that are very localized. They have historical data for events that drive up costs for MaaS companies and even traditional businesses such as developers. These may be things such as seasonal geese populations, how rainfall affects downtown traffic patterns and which areas are prone to electricity failures. Kyle Connor of Cisco illustrates this same capability with fog and logistics companies.
Streamlining Emergency Services
In previous blogs, Sealevel has discussed different ways technology is improving public safety. However, that information concerned technology deployed in cities still operating on traditional governance models. In smart cities, the opportunities for technology-based streamlining abound in public safety. These possibilities exist primarily in emergency services because they operate at the center of an integrated network of public-private institutions coordinated by public entities.
Returning to climate data, imagine a smart city aware of an approaching fog pattern. However, the city has run smart analytics on these patterns previously and shown that they tend to cause catastrophic accidents over a few key bridges. City officials have pre-empted these occasions by installing sensor-based fog lights on these bridges that activate when detecting the weather pattern. They have also installed acoustic sensors to monitor traffic and events.
However, imagine that despite those precautions, a wreck still occurs. Smart cities are often connected communities, which means the data can be shared to drive costs and risk down, especially concerning population health. In this foggy scenario, emergency response vehicles are equipped with software that allows access to the acoustic sensor data. They respond immediately to the wreck, without any 911 phone calls. Ambulances carrying passengers harmed during the event can use crowd-sourced navigation software with AI enhancement that accounts for dangerous roads and nighttime traffic patterns. Updates are sent during the ride, speeding up the patient’s intake.
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