Nokia’s Outi Niemi looks at the potential offered by automation in a smart city context and shares examples from related industries.
Automation is a key emerging theme for enterprises of all kinds. Today we are seeing a wave of digital transformation sweeping industries such as manufacturing, energy, transportation and more.
Advanced technologies such as artificial intelligence (AI), cognitive/machine learning and machine-to-machine communications also promise to transform the industrial environment.
As cities look to become smarter, many are exploring how they can take advantage of these same capabilities to better manage their assets and operations. For example: how can they best apply the principles behind digital automation and the ubiquitous connectivity of the internet of things (IoT) to address urban management challenges — from maintenance of city resources to sanitation to public safety?
In certain ways, cities resemble industrial environments (albeit on much larger scale), and face many of the same challenges. As a result, they need to be able to predict mechanical problems within municipal infrastructure of all kinds, from waste-water processing plants to traffic management systems to street lighting installations. They also need to be able to deliver a wide range of city services to residents and visitors alike; in many cases, as their populations and geographic footprint expand rapidly as well.
In certain ways, cities resemble industrial environments (albeit on much larger scale), and face many of the same challenges.
To manage these vital processes, they need to be able to collect and analyse enormous quantities of data from a vast number and variety of sensors, actuators, video cameras and other connected devices. To accomplish this, these data sources need to be interconnected using a high-capacity, secure and reliable network.
Localised computing resources — to provide rapid processing capabilities — are also an essential ingredient for responsive city services. All of this is necessary to provide meaningful information to city managers, and to enable more advanced functions like machine learning and automated decision-making, which can help make city services more intelligent.
At the heart of this strategy are high-performance wireless communications systems, typically based on industry standard LTE technology, that can be deployed in both indoor and outdoor environments using unlicensed, shared and licensed spectrum; giving cities enormous flexibility. These connectivity solutions can then be coupled with real-time applications to support various aspects of digital automation.
One approach being actively explored is the development of digital automation ‘building blocks’ that can be mixed and matched as needed to support emerging services. For instance, high-accuracy object-positioning and real-time video processing capabilities can be used to support advanced IoT solutions such as automated guided vehicles, analytics and robotics. These in turn can be combined to support automated waste collection services, which could be particularly useful in regions where the cost of labor is at a premium, making delivery of basic services a challenge.
Of course, these systems need to deliver huge amounts of computing power at the “edge” of the network (close to end-users) and must be sufficiently scalable to support a wide variety of applications simultaneously; and with high efficiency, while meeting stringent privacy and security requirements. Fortunately, networking technologies are available today that can address these needs and these strategies are not purely speculative.
Industry players in a variety of fields have already begun to employ digital automation techniques to streamline operations and improve critical processes.
In the area of logistics, for instance, shipping companies are already increasing their use of scanners and sensors to improve tracking of containers, equipment and vehicles. Online vehicle inspections are enabling technicians to perform proactive maintenance, helping reduce fleet downtime. Analytics offers the potential to forecast and report on traffic congestion and estimate delivery times.
Each of these capabilities could be of enormous value in the smart city context, in areas such as waste removal, roadway maintenance, management of bus fleets and more.
Similarly, companies in natural resource industries are already using drones — that support real-time video feeds — to inspect pipelines, check on the progress of crops and a range of comparable services. These same techniques can be used to improve situational awareness for public safety organisations and rescue teams as well as for visual inspection of city infrastructure such as bridges.
These are just a few examples of the innumerable ways that advanced networks can bring the power of digital automation to city services. The potential created by the integration of a wide variety of sensors, machines, people, vehicles and more — across a wide range of applications and use cases — promises to transform city management and impact the lives of millions (ultimately, billions) of people.
As a society, we are really at the very beginning of this process. A small, but growing number of forward-looking cities have begun to deploy the kinds of capabilities described above; typically in relatively limited geographic areas, and often sited in and around technical universities and industrial campuses. However, these early trials are all but certain to lead to broader deployments once network architectures and use cases are validated.
Still, it is important to note that the kinds of applications and services described here are being employed today using existing, commercially-available technologies. Over time, emerging technologies such as 5G (which is expected to be deployed over the next several years) and more advanced AI technology (which is only in its infancy) will offer additional capabilities that can further enhance how services are delivered in cities of the future.