Three primary urban problems which can be solved by IoT and AI
Having visited more than 40 countries, 200 cities and lived in six countries in the last 10 years as well as working in the disruptive Internet of Things (IoT) space, the subject of how to make cities smarter and more citizen friendly is of particular interest to me for both professional and personal reasons.
More than half of the world’s population now live in cities - and the figure will rise to more than two thirds by 2050, according to a United Nations forecast. Growing numbers of city residents put pressure on energy and water resources, transport networks, environment, national healthcare budgets as well as many more aspects of the city. In the last few weeks I have been thinking about the most important problems that the most cities around the world may face, but they can be solved or reduced by Internet of Things and artificial intelligence (AI) enabled solutions. By IoT we simply mean when objects are connected to the Internet and exchange data.
With the power of IoT and AI, cities have the ability to understand at a granular level and in real time the biggest air pollution problems
From my everyday professional experience - reading reports, speaking with council representatives, attending smart city conferences, but also from personal exposure to cities as a global citizen and traveller - I identified the following three big problems that many big cities try to deal with. The good news is that the power of technology, especially the IoT and AI, can improve all of them.
Problem 1: Mobility challenges – How to improve citizens’ lives and bring them closer
Urbanisation and growing population in most cities is causing more and more problems for the movement of the citizens in their city. Commuting or driving to work and home has become a hassle;. congestion in the EU is often located in and around urban areas and costs nearly EUR 100 billion, or 1 % of the EU's GDP, annually as estimated by the European Commission.
The mobility challenges are plenty and not limited just to traffic congestion. They are also about efficiently connecting (time, cost, effort) different neighbourhoods with public means of transport, helping citizens and professionals at the last mile journey, giving access to the critical stations (train, airport, buses) with multiple means and from multiple regions, offering a variety of options to the people to move around (including bicycle), offering of parking slots, and many more. It is also about understanding how citizens move every day in order for city officials to plan accordingly the location of stations, bike routes and traffic lights, as well as to optimise the schedule of each city activity without disturbing others.
Today, thanks to the use of IoT and AI-enabled solutions, the cities can be improved and solve - or at least reduce - some of the main urban transportation issues. Here are some examples:
- Optimise availability of public parking slots through real time parking sensors that can show to the drivers where the nearest parking is without going around blindly. Finding parking in less time can reduce both traffic jam and air pollution
- Understand how and when people are moving in the city, from where to where, and their profile. A city authority which can have this knowledge is able to take much better planning decisions based on data and facts. Some ways to achieve this are by analysing the anonymous and aggregated mobile data from consumer phones. If this data is combined with other data generated by connected city furniture, then the insights are priceless. Smart city furniture could be connected lights, smart benches, and connected traffic lights, while other city assets could be connected bikes and buses, connected buses and rubbish bins. The analysis of all this combined data can generate insights and automations that we could never think otherwise.
- Plan maintenance and improvements in the road and public transport network efficiently based on the collected data by the IoT enabled assets. For example, big halls on a street can be identified by the data generated from smart bikes/lights due to the shaking sensors. No need to send employees to check or ask citizens to report it (usually after accidents). At the same time, the schedule of when a local authority is appropriate to send the workers to cover the halls can be planned based on the available data from the sensors around that street, so traffic interruptions can be avoided.
Of course, there are even more IoT applications that can improve the mobility in the city. Saying this, improving mobility can improve also air quality. Based on European Commission statistics, urban mobility accounts for 40% of all CO2 emissions of road transport and up to 70% of other pollutants from transport.
Problem 2: Air pollution – how to do urban planning and reduce air pollution
Urbanisation has enormous environmental consequences too. Despite the efforts of some mayors to handle the level of air pollution in their cities, in most cases the quality of the air that we breathe in the cities is deteriorating due to a variety of reasons; the increasing population in urban places, rising car usage, limitations in parking, as well as factories operations.
Apart from the obvious damaging consequences to our health, there is also significant negative impact on the economy of each country. For example, last year alone the costs of air pollution to the National Health Service (NHS) and social care in England were estimated to be £157 million. The latest findings, published in a report from PHE, warn these costs could reach as much as £18.6 billion by 2035 unless action is taken. The researchers explain that these figures are based on costs related to GP doctor visits, medical prescriptions, hospital treatment and social care due to long-term health conditions, and do not take into account economic impacts due to lost productivity. Unfortunately, the economic cost and health impact is tremendous in every country that suffers from similar problems.
With the power of IoT and AI, the cities have the ability to understand at a granular level and in real time the biggest air pollution problems, the cause, who is affected and what it means for the citizens. With all these real-time insights the city administrators can take informative decisions about how to tackle the problems and how to prioritise their investments. I am sure in the future we will even see real-time decision making and actions in order to improve the air in the polluted neighbourhoods.
Today there are a variety of air quality sensors that can be placed in public means of transport, smart furniture such as smart lights, smart benches or anything else that can be connected, such as rubbish bins, bus stations, or bikes. Some environmental information is publicly available and some can be provided to the local councils in low or no cost on exchange to something else (i.e. license to use city space or add sensors on city furniture). Apparently, if the data from the sensors that measure the air quality is combined with anonymous mobile data from the network of mobile operators, such as of O2, then the insights can be really valuable, as described above. Cities can plan to create new pedestrian streets, new biking routes, electric vehicle chargers or parking spaces based on the air quality levels. Thus, both the combined data from sensors and mobile phones is critical.
In other words, the councils instead of taking decisions based on historic data or opinions, now coupled with expert perspectives they have all the tools to optimise their decisions based on real-time data or even to automate processes based on specific incidents. In addition, now the cities are capable to customise their actions on neighbourhood level and take different measures for each neighbourhood, instead of acting in the same way for big areas of the city or even for the whole city. Each neighbourhood may have different problems and may require different action plans.
Problem 3: Home care for elderly and vulnerable people
We often read reports and articles about the growing ageing population and what it means for the national economy, but also for the life of these people. The increase in life expectancy has coincided with a dramatic rise in the number of elderly people who are “highly dependent”. Expenditure on the care of older people is increasing substantially and quickly; almost 190,000 more people in UK aged 65 years or older will require care by 2035, marking a rise of 86 per cent, according to the paper published in The Lancet.
Nowadays, the cost is paid either by families or by the city councils. The cost though is too high and the way that these services are offered is very impractical and inefficient. For example, a council needs to send a home care employee to visit three times a day a sick or elder person in order to check if he/she took the medicines and if he/she is fine. For obvious reasons, services like this cannot scale without the support of technology.
There are many IoT-enabled products in the market that can help local authorities remotely monitor the conditions of these people, get notified if and when they took their medicines, if they need any help, and more. Today, there should not be the need to pay and send professionals to check if an elder person is fine at home. Thanks to IoT and AI remote checks can take place and alerts can be sent in case of incidents. These professionals can use their time in more added value services which can have more impact to the lives of this vulnerable population. Some of my favourite examples of IoT and AI solutions are:
- Smartwatches specialised for elders that can monitor the location, the health condition, remind taking medicines based on specific schedule, help in collecting and sending medical data These kinds of solutions can also benefit people with Alzheimer’s and dementia, among others.
- Passive devices that can sense movement, temperature, humidity and noise. The device can learn the daily patterns of the person in the house using machine learning algorithms and send notifications to the person, or to the selected stakeholder (family members, city home care service or others) when a daily pattern is disrupted. You can even interact with these devices in order to remind something or to inform others that a task has been completed.
- Smart devices that monitor the water or electricity consumption and through machine learning they are able to identify disruption in the daily patterns of the person. For example, if the user of the flat usually boils water at 10:00 and turns on the TV at 17:00, if one or both of these actions do not take place, it may mean that the person feel unwell or has left the house alone. Then, an alert can be sent to the predefined stakeholder in order to check closer what the issue is.
All of these home care solutions can work passively without the need for intervention from the user or someone else. This is usually possible because the devices are connected with managed cellular connectivity (SIM cards) instead of Wi-Fi. With this type of connectivity there is no requirement for the flats to have Wi-Fi or for someone to configure the device with the Wi-Fi. The device is ready to be used. Apart from this, new communication networks, like LTE-M, NB-IoT and 5G will allow the deployment of even more applications.
It is about smart city partnerships and ecosystems
If we want to see all these solutions at scale then the type of cooperation between public authorities and private companies has to change. In the past, the traditional relationship was: buyer=public authorities and one time supplier=private company. This relationship cannot offer sustainable solutions and partnerships today.
A new approach to the city problems (and not only) need to be followed and this is development of a strong ecosystem of partners, meaning many different suppliers with complementary services and skills that are ready to invest resources in order to innovate together with the city, learn together from the pilots and later to scale. This ecosystem needs to include stakeholders from different backgrounds, such as local authorities, local universities, private or public associations, startups and some key corporates. Needless to say, the citizens, as value receivers, need to be involved and kept updated about the ideas, plans and projects in their city, while offering them the opportunities to share feedback and recommendations.
If we want to see all these solutions at scale, then the type of cooperation between public authorities and private companies has to change
Each stakeholder needs to be able to add incremental value to a specific part of the value chain. One company cannot offer everything and cities shouldn’t trust all the solutions to one supplier. Partnerships and co-innovation are the magic words in order a city to be able to plan, pilot and scale a smart city solution. Some good city ecosystem examples we can see in the UK are in cities such as Bristol, Manchester and Bournemouth.
New business models
Lastly, while IoT changes relationships and build ecosystems, there is a clear need too for new business models so they can fund all these projects and move them beyond pilots. As we know, most of the cities cannot afford expensive CAPEX (upfront) investments for each new solution they want to deploy. Business models that charge per month or per year (OPEX) are preferable, offering everything ‘as a service’. In addition, revenue sharing concepts or result based charge are ideas that are discussed a lot nowadays and I am sure we will see them applied more and more often.
To sum up, cities are just scratching the surface of what can be done with data and the opportunities of positive urban transformation by the use of technology are plenty. Citizen engagement and attention to data and citizen privacy are required though, because otherwise the irresponsible use of technology or use of technology just for the sake of using it can destroy the benefits that we envision for our cities. Innovative partnerships and business models combined with social and environmental responsibility are necessary in order to make the roadmap to smart cities economically, socially and environmentally sustainable in the 21st century.
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