5.1 Applications and benefits to citizens
There are a large number of potential applications of the internet of things in smart cities. Some are expected to be deployed early in smart cities and others may not emerge until the future when platforms are in place, smart cities are more mature and as the demands of society evolve. The applications which have been identified for the purposes of this report are listed in Table 6 below and are listed in eight groups. A brief explanation of each application is provided in Appendix A.
Group Applications
Citizen monitoring
CCTV
Citizen tracking
Crime detection
Crowd control
Sentiment measurementCivil emergencies
Communication of critical instructions
Natural disaster response
Road traffic accident reportingEnvironment and energy
Cogeneration
Energy usage monitoring
Local weather forecasting
Noise and pollution monitoring
Stray animal trackingPublic connectivity services
Education
TourismGroup Applications
Public health and social care
Drug detection
Social care monitoring Public information and policy
Information kiosksServices and infrastructure
Connected street furniture
Connected waste management
Smart street lighting
Staff management and trackingTransport management
Car safety
Car sharing
Congestion charging
Connected road furniture
Gritting
Pothole management
Public transportation ticketing
Smart parking
Smart roads
Traffic management & control Table 6 – Smart city applications listed by groupIn general, the benefits of each application are one or more of the following:
Cost savings for public services, leading to a reduced tax burden for individuals and businesses
More efficient use of time, such as time saved in traffic congestion or using public transport
Improved environment, such as reduced pollution
Improved safety and quality of life
Increased wealth through economic growth
Better access to informationThe benefits provided, and who the primary beneficiaries are, have implications for the most appropriate business model, as discussed in section 5.2 below.
5.2 Business model approaches
Smart cities provide a range of benefits to many different individuals and businesses in a city, but also require substantial investment and the close involvement of a number of different stakeholders. Business models therefore have particular importance for smart cities, perhaps more than any other area of IoT.
Business models must provide a return or justification to those providing investment, which is often a different stakeholder to those that receive the benefits. In some cases this may be through creating a revenue stream for a private enterprise, but in other cases there is no clear means of monetising smart
city services, and so it falls to the public sector to provide an investment for the good of the community.
Table 7 below lists the potential beneficiaries and investment sources for smart cities.
Potential beneficiaries
Health and social services
Central government
Service providers, such as postal services, utilities and others
Connectivity or digital service providers
Universities
Public sector Councils
Emergency services
Health and social services
Central government
And others
Individuals Residents
Visitors (unlikely to invest)
Businesses Those based in the city
Service providers, such as postal services, utilities and others
Connectivity or digital service providers
Universities Table 7 – Potential beneficiaries and sources of investmentThe lack of an appropriate business model may in itself inhibit the deployment of smart city services. The co-ordination and collaboration required between a diverse set of stakeholders can be difficult to achieve and complicate the case for investment. Internal department and separate budget-holders within a local authority can further complicate the challenge.
In some cases, the approach taken in one aspect of city development can affect the overall business case for smart cities. For example, some local authorities have contracted the provision and maintenance of lamp posts to private companies on a long term contract. If suitable consideration was not given at the time of contracting to the potential future use of lamp posts as smart city infrastructure, then this can act as a barrier to their use in the future. The budgetary separation within authorities of the provision of one service, in this case street lighting, can impact the ability of the city to make budgetary decisions at a higher level.
A number of distinct business models have been identified for the provision of smart cities. However, in reality a combination of these may be used, for example different stakeholders may collaborate and invest collectively, each using different business models to justify their investment. Separate revenue streams may be generated over time, facilitating the evolution from one business model to another, as the market matures.
5.2.1 Business model: Public sector cost reduction
Local or national government, along with other public sector authorities such as the emergency services or health authorities, may invest in providing smart city infrastructure in order to reduce the costs of delivering existing services. Although there may be some complication in sharing the investment across
different budget holders, the business case is relatively straightforward as a balance between the investment required and the cost savings delivered.
An example of an application which may be provided with this business model is connected litter bins which report when they are nearly full and so enable the costs of routinely visiting and emptying bins to be reduced.
5.2.2 Business model: Public sector investment for economic growth
If the value from smart city services would not be delivered satisfactorily through any other business model, and the economic or quality-of-life benefits justify it, then public sector authorities may be called upon to make the investment on behalf of citizens. This approach depends on the responsibilities at each level of government, and may be more appropriate at a regional or national level. There may be specific high-value applications that drive this investment, such as nation-wide traffic monitoring. There may also be competition with other regions or countries to become leaders in smart city technology which may drive investment.
5.2.3 Business model: Provision by citizens through crowd-sourcing
Local residents can provide infrastructure on a crowd-sourced basis, by each providing an element of infrastructure which works together as a system. Access may be provided to the public for free or by contribution to the community. This approach is being adopted by The Things Network309 which has 28 communities in cities in the UK and communities across 53 other countries. With its informal approach, these networks cannot offer guaranteed coverage or quality of service, but with its low-cost base and decentralised approach may be appropriate for some useful applications within a smart city.
5.2.4 Business model: Private sector investment for revenue
If it is possible to monetise the value delivered from smart city services then a commercially-viable service may be built by private sector businesses. Revenue may come from service users, such as residents or businesses paying for access to data, or from a service fee paid by public sector authorities which recognise the value of the service to the city and wish to subcontract its provision. Revenue may also be generated indirectly, such as through targeted advertising to users or through the value of data collected by the service.
An example of an application which may be provided with this business model is where public transport is provided by a commercial organisation which invests in a service to provide live transport updates to passengers. The benefit of this service is to increase the number of fare-paying passengers, therefore justifying the business case for investment.
5.2.5 Business model: Private sector investment as technology demonstrator
As smart cities remain emergent, there is value to businesses in establishing themselves or the region as a leader in the technology of smart cities. This may justify an investment with no short-term revenues, but which benefits the business in the long term. For example, an emerging business with a candidate technology may set up a city-wide demonstrator in order to establish their technology as the market leader. Alternatively, a group of businesses may have an interest in promoting the city or region as a leader in smart city technologies and may co-operate to provide some infrastructure on a trial basis. This may lead to an evolved solution as more applications are deployed, and in time the business model may need to mature to a different approach.
5.2.6 Business model: Private sector construction investment
Private sector businesses may invest in smart city infrastructure and services as part of a wider
investment or business case. For example, a construction company may develop a large housing estate and as part of the development may install smart city services alongside services such as utilities,
309 See: https://www.thethingsnetwork.org/
communications and transport networks. These smart city services may subsequently be handed over to other organisations to manage. This business model is likely to emerge as smart cities become more mature and services are integrated more closely with construction developments, especially large developments of new towns.
5.2.7 Business model: Academic research
As smart city technology develops, there are aspects which are the focus of academic research and have not yet matured to commercial research and development. Investment cases can be made for some smart city services in order to support academic research of technology and their social implications.
Although it is unlikely that this model will support complete systems, it can form an important part of a collaboration, and many of the smart city initiatives in the UK involve academic partners.
5.2.8 Business model: Collaboration and hybrid business models
Most significant smart city deployments in the UK so far have involved collaboration between a number of partners, usually including public sector, academia and private businesses. For example, Bristol is Open is a joint venture between the University of Bristol and Bristol City Council, and has formed partnerships with many different organisations. In these cases there is often no single clear business model but each partner makes a business case for their involvement based on a different model. As these deployments mature, it may be that they evolve to a different business model, perhaps including transfer of
responsibility to a single organisation at an appropriate time.
5.3 Approaches to data ownership, privacy and security
There are two principal threats to a smart city system: unauthorised access to valuable data and unauthorised control or disabling of a system which causes harm or loss.
Many of the applications of a smart city gather data which is not particularly valuable or sensitive, and in fact may be public as soon as it is gathered, such as traffic congestion or weather data. However, some data may be sensitive, particularly if it permits an individual to be identified or tracked. In these cases, it is important that the data is suitably protected. The data itself may not be sensitive, but it may be processed or combined with other data to provide more valuable insights, such as facial recognition of CCTV
images, or daily occupancy patterns of a building. Some example applications which involve the collection or handling of sensitive data include:
Traffic flow measurement (if individual vehicles identified)
Smart parking (if individual vehicles identified)
Utilities/energy monitoring if at sufficient granularity, e.g. by household
Use of apps or browsers which track user identity
Public transport (if individuals identified such as with an electronic season ticket)
CCTV (where facial recognition algorithms can be applied)
Care of elderly or vulnerable personsAlthough the data is sensitive in each of these cases, it is of a level which is already routinely collected, stored and protected by commercial-grade systems. The risk is increased, however, if data is being collected across applications by the same system, and if suitable partitioning of the system is not in place so that access to one data set grants access to other data sets. Appropriate measures must be taken to protect smart city data because, if personal data is compromised, this may lead to resistance from the public to some smart city applications.
At the current stage of development of smart cities, data is generally collected in order to provide a service, and it is not monetised directly. It is possible that in the future data will be used to generate revenue, such as through its direct sale or indirectly through targeted advertising to consumers. In this case, the attitudes of consumers towards the data being used for this purpose will need to be managed.
This debate is currently playing out with regard to data collected by internet companies and social networks, and the trade-offs necessary are beginning to be understood by the public.
In many cases, the value of the data increases as more data sets are combined and more insight can be generated, but this also increases the risk of data being compromised. Data should be anonymised wherever possible and as early as is practical in the data handling process.
Of greater significance, however, is the potential for a smart city system to be maliciously compromised by a hacker, which may be for criminal reasons or even terrorist or state-sponsored activities. Access of some smart city systems could enable the hacker to have an impact in the real world, such as changing the display on smart signs or influencing traffic control systems. If a connected traffic lights system could be compromised such that all city traffic lights showed green, this could lead to loss of life in traffic accidents and inevitable economic loss through the ensuing gridlock.
The security of systems which could lead to personal injury or economic loss to the city or its citizens if compromised is therefore vitally important. Standard commercial security techniques can be used, such as ensuring these systems are not directly connected to the internet if this is practical. Protection of critical national infrastructure is a stated aim for the creation by the UK Government of the National Cyber Security Centre which was formed in March 2016310.
5.4 Approaches for mission-critical applications
As more aspects of a city become connected and integrated, there will be an increasing level of interdependence between platforms and communications systems. Although each element will have a high level of availability, there will be more potential points of failure. For smart city applications that are mission critical, or which result in significant loss if they fail, a high level of resilience will be essential.
Smart city applications which could be described as mission critical include:
Intelligent traffic management systems and public transport control systems, which could result in gridlock or even cause fatalities in the event of a failure
Applications that provide critical care for vulnerable people, where failure could result in physical harm or a lack of essential care being provided
Systems used by the emergency services, such as to access city information or co-ordinate a response to an incident, where failure could result in loss of life or propertyMission-critical systems must be designed with an appropriate level of redundancy to guarantee that they are highly available. These approaches are already common in other mission-critical infrastructure, and include careful design to remove any single points of failure, and the provision of redundant power supplies and redundant communication systems. If possible, parallel communications systems using different technologies should be implemented, such as using a cellular system as a fall-back to a private network, or a satellite link between sites. These approaches increase the cost, and this needs to be balanced against the probability and impact of a system failing.
Smart connected systems should also be designed to fall-back to their current, non-connected mode of operation. So for example, if a smart traffic light system were to fail then it should revert to its independent timed mode of operation. This may lose the efficiencies of a connected system, but will ensure that some operation continues rather than causing gridlock.
There is a significant reputational risk in the failure of smart systems. Although non-connected systems suffer failures, and human-dependent systems certainly do, the failure of a connected or “smart” system can be a high profile failure which shakes the public’s confidence in technology. An example of this can be seen in autonomous cars, which are statistically safer than their human-driven counterparts, and yet a fatality caused by an autonomous vehicle is seen as evidence that the technology is not safe.
310 See: https://www.gov.uk/government/news/new-national-cyber-security-centre-set-to-bring-uk-expertise-together
5.5 Implications for the future market
There are already numerous pioneering initiatives in UK cities and the level of interest in them is rising.
The most advanced deployments are based around collaborations between city authorities, businesses and academic institutions and are pitched as demonstrators or test beds. There remain significant inhibitors to widespread deployments in urban areas around the UK, and it will take time for the right business and technology approaches to mature and become widespread.
There may be a role for regional or central government to lead, ensuring that deployments move on from initial test beds to established deployments. This may include encouraging collaboration between cities and regions, and providing funds for platforms to overcome the initial investment barrier. Awareness could be raised within local authorities through the sharing of information, best practice and lessons learned from the early adopters.
As the technologies remain in an emergent phase, a liberal approach to spectrum availability and usage will enable flexibility as technologies emerge, evolve and adapt. A high level of fragmentation can be expected, followed by convergence towards a smaller number of technologies that benefit from economies of scale and high interoperability.
International developments can also be expected to have an impact on the UK market. Large cities in emerging economies face significant pressure with rapid growth rates and large urban areas. City
authorities in these conurbations will increasingly use technology to address some of these problems, and will drive some of the adoption of smart city approaches worldwide. Newly-built cities are being
constructed in places such as the Middle East such as King Abdullah Economic City311 in Saudi Arabia, which make wide use of smart technologies and avoid the challenges of deploying into a legacy
environment. Overall, therefore, the direction of smart city technologies will be influenced by deployments outside the UK as well as within the UK.
311 See: http://www.kaec.net/
6 Focus on connected vehicles
The connected vehicle market has seen a large increase in focus over the past two years, with connectivity solutions moving to the mainstream of cellular standardisation and increased autonomy becoming available, in a limited way, in cars available for sale today. This rapidly changing market and technology landscape means that we need to consider additional impacts over those discussed in section 4.1, in the following structure: