What can smart cities administrators learn from enterprise networks?
Urban planning is entering a new era. Breaking the mold with centuries of agricultural living, urbanisation has taken place on an unprecedented scale since the industrial revolution. Today cities are home to more than half of the world’s population,andit’santicipated there will be a further 2.5 billion urban dwellers by the year 2050.
With this dramatic shift in demographics, pressures on infrastructure systems increase exponentially, particularly with the expectation quality of life should continue to increase. That’s why we‘ve seen smart city projectsmake up the largest segment in the IoT space over the last few years.
With hundreds of active initiatives, vendors and municipal governments around the world are paving the way for the digital cities.As an example,in the US, telecoms operator Verizon has been working with city authorities inSacramento, San Jose, Boston, and elsewhere to roll out IoT connectivity for a variety of areas from traffic management and integrated public transport, to energy-efficient street lighting.
An interconnected smart city is certainly complex – but we can also see it as a larger version of existing enterprise networks
A smart cities programme in Singapore has been rolled outtodeploy sensors and automated metersin orderto improve the efficiency of the city’s power grid—and to also incrementally reduce the use of air conditioning in residential areas. Meanwhile, even closer to home,the city of Cambridge’s “Smart Cambridge” initiativefocuseson improving the city’s public transport.
Smart cities consist of multiple, interconnected networks of remote sensors and endpoints—both fixed and mobile—that continuously record and exchange data. This data is then stored and analysed to identify underlying patterns and trends across the ecosystem. But the sheer volume of data, plus the complexity of the many interconnected networks involved, means that it won’t just be the city that never sleeps at night; system administrators face a monumental task of maintaining this added complexity within the sensors’ underlying systems.
An interconnected smart city is certainly complex. But we can also see it as a larger version of existing enterprise networks that connect offices in different locations, collect and analyse large volumes of data from different sources, and work closely with third-party partners and providers. The important difference is a smart city involves a broader scale and scope—with more network layers and endpoints. But a smart city requires the same skills needed by administrators to manage and maintain a conventional enterprise network.
The features and functions associated with smart cities, such as traffic management systems and integrated public transport networks, aren’t just interwoven, they must operate in real time. They’re coordinated by, and dynamically adapt to, variable circumstances such as vehicle congestion levels or constantly changing locations and speeds of buses and trains in and around the city. These features reply upon low-latency and two-way connectivity between sensors. But if this connectivity breaks down, even for a few seconds, consequences result, whether missed connections for commuters traveling to work or even a sudden gridlock on the streets—and could send the city into standstill. It will be the administrator’s job to rapidly identify the source of a problem across the network.
