Look at the potential benefits for citizens and the whole world, and the prospect of smarter cities is hugely attractive. But look at the obstacles, and the prospect is daunting. But, to the networking industry, these problems are not new, but simply more extensive. The basic skills and knowledge to solve them is already available, Stephen Douglas solutions & Technical Strategy Lead IoT, Spirent explains
Satellite-based images of the Earth by night present a dramatic picture of global urbanisation. There still seems to be a lot of dark space between those bright lights but – according to the 2014 revision of the World Urbanization Prospects by UN DESA’s Population Division – more than half (54%) of the world’s population now live in urban areas, and the figure will increase to two thirds (66%) by 2050. The concentrations are also increasing: in 1990 there were ten “megacities” with 10 or more million inhabitants; today there are 28 and by 2030 we expect there to be more than 40 such cities.
Strictly speaking those bright lights do not represent people so much as the electrical energy they are burning. That is why the USA is so much brighter than India, despite having only one quarter of India’s population. The fact that 75% of energy is consumed in cities that cover just 2% of the earth’s surface does present one clear message: if we want to reduce global energy wastage, we should begin by concentrating on those urban areas.
That is just one reason why there is so much and increasing interest in “smart cities”. There are also many more immediate benefits – such as cost savings, a safer, healthier environment and reduced traffic congestion – but even these can indirectly save energy. In today’s thinking: what is truly good for us is often good for the planet.
So, what makes a city smart? And why are all cities not already smart?
The word smart can mean ‘stylish’, and we surely prefer our cities to be smart in that sense. But smart can also mean ‘clever’ and, more recently, it has been extended to mean something that integrates computers in such a way that it can do more things while needing less instruction – such as smartphones. That is what is meant by a smart city.
Take traffic congestion for example. This was first addressed by having police at important junctions directing traffic. Automation began by replacing them with timed traffic lights. This was a backward step – until systems were devised so that the timing could adjust to the relative amounts of traffic from each direction, as the police would do. True smartness begins when individual lights become linked by a control network, so that traffic becomes more of an integrated and optimised flow, rather than a broken sequence of stop-starts. Once such a network has been established, it could also accept feeds from other sources: such as weather forecasts, news about major events, public holidays, school times, rush hour or goods delivery schedules as well as accident reports. Such additional data would enable proactive decision making to anticipate and avoid traffic jams – and this has become a truly smart traffic system.
This same principle can be applied to most other city services. The air conditioning system in a single flat can be totally independent, or it could be networked with other systems in the same building, or it could be part of a city wide environmental control system that takes account of expected weather conditions and optimizes cost-effectiveness by levelling peaks in power demand. It could also provide Internet connection – so that residents could remotely turn off the system when away and restart it before they return home.
This type of thinking could result in a whole range of smart services being delivered across the city from co-ordinated shopping delivery and laundry collection, though waste recycling and collection on demand, to integrated emergency and police services. But a truly smart city means more than just a collection of separate services, however smart. It means bringing together as many of these separate functions as possible to create something that is far greater than the sum of all those parts.
This entails seeing useful connections between apparently quite separate functions. For example: the security system in a residential block might link to the traffic management system described above and, at times when residents are away, it could allow non-residents to use the empty parking bays and so reduce pressure on public car parks.
Smart is good
The real secret of smart success is not merely to design only for a specific goal, but also to build a flexible foundation that adds potential for future developments. Unless starting with a greenfield site, and able to plan a very smart city from the ground up, most smart city projects will begin with one or more key goals.
Traffic management will be a high priority – city vehicle congestion costs the US economy around $124 billion a year according to INRIX, and the American Public Health Association adds a further $50 to 80 billion in associated health care costs. That looks like reason enough to direct a lot of development resources into simply solving that one problem, but do not forget that further benefits will be possible if the resulting solution is open to integration with other future smart systems, such as the public parking example above, or a smart waste disposal operation where the lorries can be scheduled around ideal traffic conditions.
Key components for a smart city can embrace:
- Transport: not just traffic management but also integration with public transport, goods delivery and parking
- Building automation, environmental control and smart lighting
- Energy grids and smart meters, energy harvesting and storage
- Healthcare: not only emergency services but eHealth provision and fitness services
- Education: as well as building management and school security there are positive benefits of online education, reference and special needs provision
- Governance: overall environmental management, disaster provision and eGovernment
These last elements lead us to the extraordinary potential for social change in a smart city – both for good and for bad. Personal devices – smartphones, watches, fitness monitors and other wearable devices – carry colossal amounts of data on every citizen, but also real time data such as location and communications. Wisely directed, such data could form the basis for open data initiatives that would inform and empower people to generate a stronger sense of citizenship and involvement. It could restore that old-fashioned sense of ‘civic pride’.
Or it could lead to, or be seen as, a George Orwell type nightmare of a ‘Big Brother’ dystopia, generating simmering discontentment or outright rebellion. This brings us to the consideration that, for all the potential benefits offered by smart cities, there are corresponding hazards that also need to be addressed.
Too smart for its own good?
Following that last example: even if the City could reassure people of its noble intentions and build trust in a citizen-wide network, there is still the fear of cyber attack, government or commercial snooping or other invasions of privacy from outside the system.
Extending networks to embrace a smart city means vastly increasing the potential attack surface area by the addition of millions of portable devices, smart meters, and sensors. Whereas a mobile phone or computer is a relatively expensive device that justifies the extra cost of built in security features, a sensor in a waste bin that tells the city when it needs to be emptied, or a sensor that tells the city’s irrigation system that the soil in a flower bed is too dry, such devices can only be justified if they stay small and cheap. They cannot afford much internal security, and their vulnerability means they could be used as base camps for cyber attack. So one major consideration in planning a smart city must be how to design high security into the networks themselves. And planning alone is not enough: it must be followed by rigorous performance testing of not only the components but also the whole system for every type of normal extreme of attack operating condition to make sure it does not break down.
Ruggedness and future-proofing will often be a further priority. Rolling out thousands of sensors to measure traffic, or to control street lighting, is a labour intensive operation that cannot be justified unless they are going to serve with minimal maintenance for ten or more years ahead.
Added to that is the sheer difficulty of retro-fitting smart functions in an existing city with a heritage of planning regulations and legacy design. Even the simple act of replacing an incandescent bulb with LED can be thwarted by the need to replace a dimmer switch.
There are many such problems in any existing city, and that makes it all too easy for smart systems to evolve independently with a lack of interoperability and leading to a scattering of siloed solutions and technologies. If the emergency services believe it is extremely urgent to develop a smart management system, they will not want to hold up the project for many months while the traffic department makes complex choices. In desperation the emergency services will go ahead on their own, as will other key functions needing rapid results.
Underlining this risk of fragmentation is the unhappy legacy of multiple technologies and platforms each with their own independent standards and interfaces. A fully networked city would involve a huge range of network technologies, from the very local RFID contact systems, the short range technologies such as Bluetooth and ZigBee, then Ethernet, WiFi, Metro Ethernet, 3G, LTE and many others. Missing out any of these elements could reduce the potential inclusiveness of smart thinking, and yet few of these technologies were designed to interoperate.
On top of all these challenges is the fact that, once they have been surmounted and all the systems are go, the sheer quantity and diversity of data that will be available presents a whole new challenge in itself. Serious work is needed to make sure that people, or the system is not blinded by all the input. So called ‘Big Data’ solutions are a hot topic, but bringing together all the elements of a smart city calls for very smart data mining to unearth those golden nuggets of truly relevant and actionable data.
Are we attempting too much?
For any city department that has been minding its own business successfully for decades, the prospect of becoming part of a smart city must seem daunting, if not totally impossible. Many of the hurdles listed above will seem like brand new challenges, never before attempted, and certainly not on this scale. And yet, at a fundamental level, they are really nothing new. They are simply an extension and scaling up of challenges that the networking and communications industry has been facing for many years already.
Consider the challenges faced by a mobile network provider connecting thousands of smartphones as well as webcams and other mobile devices. These already present an enormous attack surface and present a very tempting target for cyber crime. There is also the need to integrate technologies that were not designed to work together: a smartphone does not only connect to 3G and 4G networks it also uses WiFi, Bluetooth, GNSS positioning and several other types of sensor, each with their different standards and interfaces. Cell towers, WiFi hubs and other signal relay installations may not be as numerous as a smart city grid, but they too need to be rugged and reasonably future proof. And the amount of user data fed back from all these devices is already a Big data challenge.
The point is that a company like Spirent already has extensive experience in addressing and managing all these challenges, not only in planning and design but also in testing the resulting networks and platforms under every sort of operating condition and cyber attack. We already have to negotiate between multiple standards bodies, fight for consistent global standards and encourage rival manufacturers to adopt standard open APIs in order to keep the industry from fragmenting.
The scope of potential disasters in a smart city may be larger, but the quality of experience demanded by mobile users is highly critical, and the risk of customer churn is far greater – so from the points of view of interoperability, performance, QoE and testing, smart city challenges are more different in scale than in quality or complexity.
The shortest route to becoming smart is to find good teachers. The good news is that the network industry already has the experience and knowledge that is needed.