Three major urban problems that iot and AI can solve


liu, tempo Date: 2021-08-05 09:54:57 From:ozmca.com
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According to a United Nations projection, more than half of the world’s population now lives in cities — a number that will increase to more than two-thirds by 2050. More and more city dwellers are putting pressure on energy and water, transport networks, the environment, national health care budgets and other aspects of the city. Over the past few weeks, I’ve been thinking about the most important problems that most cities in the world may face, but that can be solved or reduced through Internet of Things and artificial intelligence (AI) solutions. By the Internet of Things, we simply mean that objects connect to the Internet and exchange data.

 

With the power of the Internet of Things and artificial intelligence, cities have the ability to understand the biggest air pollution problems at a granular level in real time.

 

  • Question 1: Mobility Challenge – How to improve the lives of citizens and bring them closer together

 

Urbanization and population growth in most cities are creating increasing problems for the mobility of urban residents. Commuting or driving to work and home has become a hassle. The Commission estimates that congestion in the EU, which is often located in and around cities, costs close to €100bn a year, or 1% of the BLOC’s gross domestic product.

 

Mobility challenges are many, not just traffic jams. They also will effectively (time, cost, and effort) different communities linked with public transport, help citizens and professionals in the last mile journey, through a variety of ways and multiple access to key site (train, airport, bus) region, provide a variety of options for people (including bicycle), provide parking Spaces, and so on. It’s also about understanding how citizens move on a daily basis so that city officials can plan stations, bike routes and traffic lights accordingly, as well as optimize the schedule of each city event without disturbing others.

 

Today, thanks to the use of IoT and artificial intelligence solutions, cities can improve and solve — or at least reduce — some major urban transportation problems. Here are some examples:

 

The availability of public parking Spaces is optimized with a real-time parking sensor that shows the driver the nearest parking space rather than blindly circling. Finding a parking space in a shorter time can reduce traffic congestion and air pollution.

 

Learn how and when people move around the city, from where to where, and their personal data. Urban authorities with this knowledge are able to make better planning decisions based on data and facts. Some ways to do this are to analyze anonymous and aggregated mobile data from consumer phone calls. These insights are invaluable if combined with other data generated by connected city furniture. Smart city furniture can be connected to lights, smart benches and connected to traffic lights, while other city assets can be connected to bicycles and buses, and connected to buses and garbage cans. The analysis of all this combined data can yield insights and automation we could never have imagined.

 

Effectively plan the maintenance and improvement of roads and public transport networks based on data collected from IoT enabled assets. For example, a hall on a street can be identified by data generated by a smart bike/light due to a shake sensor. There is no need to send staff to check or ask citizens to report (usually after an accident). At the same time, the available data from sensors around the street can be used to plan when it is appropriate for the local authority to send workers to cover the hall’s schedule, thus avoiding traffic disruption.

 

Of course, there are many more iot applications that can improve urban mobility. Speaking of which, improved mobility can improve air quality. According to statistics from the European Commission, urban transport accounts for 40% of all carbon dioxide emissions from road transport and 70% of other traffic pollutants.

 

  • Question 2: Air pollution – How to plan cities and reduce air pollution

 

Urbanization also has huge environmental consequences. While some mayors have struggled to deal with air pollution levels in their cities, for the most part, the quality of the air we breathe in cities is deteriorating for a variety of reasons; The city’s population is growing, car use is increasing, parking restrictions and factories are operating.

 

In addition to the obviously devastating consequences for our health, each country’s economy would also be severely adversely affected. Last year alone, for example, the cost of air pollution to the NATIONAL Health Service and social care in England was estimated at £157m. The latest findings, published in a PHE report, warn that unless action is taken, these costs could be as high as £18.6 billion by 2035. The researchers explained that the figures were based on costs associated with gp visits, medical prescriptions, hospitalisation and social care related to long-term health conditions and did not take into account the economic impact of lost productivity. Unfortunately, the economic costs and health impacts of every country that suffers from similar problems are enormous.

 

With the power of the Internet of Things and artificial intelligence, cities are able to learn in minute and real time about the biggest air pollution problems, why, who is affected and what it means for citizens. With all this real-time insight, city managers can make informative decisions about how to solve problems and how to prioritize investments. I believe in the future we will even see real-time decisions and actions to improve the air in polluted communities.

 

Today, there are all kinds of air quality sensors that can be placed on public transport, smart furniture such as smart lights, smart benches or any other device that can be connected, such as dustbins, bus stops or bicycles. Some environmental information is public, and some can be given to local councils at low cost or for free in exchange for something else (i.e. permission to use urban space or add sensors to city furniture). Obviously, if data from sensors that measure air quality are combined with anonymous mobile data from mobile operator networks (e.g. O2), then insight can be very valuable, as described above. Cities can plan for new pedestrian streets, new bike lanes, electric car chargers or parking Spaces depending on air quality levels.

 

In other words, instead of making decisions based on historical data or opinion, councils now have all the tools to optimize decisions based on real-time data and even automate processes based on specific events, with expert input. In addition, cities are now able to customize their actions at the neighborhood level and take different measures for each community, rather than acting in the same way for large areas of the city or even the entire city. Each community may have different problems and may require a different plan of action.

 

Internet of Things

 

  • Issue 3: Home care for the elderly and vulnerable groups

 

We often read reports and articles about the growing ageing of the population and what it means for the national economy, and the lives of these people. The rise in life expectancy has coincided with a sharp rise in the number of “highly dependent” older people. Spending on caring for the elderly is rising rapidly; Nearly 190,000 people aged 65 or over will need care in Britain by 2035, an increase of 86%, according to the paper published in the lancet.

 

Today, the cost is paid by the family or the city council. While the costs are high, the way these services are delivered is highly impractical and inefficient. For example, the council needs to send a home care employee to visit the patient or elderly person three times a day to check if he/she is taking medication and if he/she is normal. For obvious reasons, such a service cannot scale without technical support.

 

There are many products on the market that support the Internet of Things to help local authorities monitor these people remotely, get informed when they’re taking their medication, need any help, and so on. Today, there should be no need to pay and send professionals to check elderly people at home for fines. Thanks to IoT and AI, remote checks can occur and alerts can be sent in the event of an accident. These professionals can use their time to work on more value-added services that can have a greater impact on the lives of these vulnerable people. Some of my favorite examples of IoT and AI solutions are:

 

Smart watches designed specifically for the elderly that can monitor location, health status, remind people to take medications based on specific schedules, and help collect and send medical data — these types of solutions could also benefit alzheimer’s and Alzheimer’s patients.

 

A passive device that can sense movement, temperature, humidity and noise. The device can use machine learning algorithms to learn the daily patterns of people in the house and send notifications to that person or selected stakeholders (family members, urban home care services, or others) when the daily patterns are interrupted. You can even interact with these devices to alert someone to something or to notify others that a task has completed.

 

Smart devices that monitor water or power consumption, and through machine learning, they can identify disruptions in a person’s daily patterns. For example, if the user of an apartment normally boiled water at 10:00 and turned on the TV at 17:00, if one or both of these operations did not occur, it could mean that the person was unwell or had left alone. You can then send alerts to predefined stakeholders to more closely examine the problem.

 

All of these home care solutions work passively without intervention from the user or anyone else. This is usually possible because the device uses a hosted cellular connection (SIM card) instead of a Wi-Fi connection. With this type of connection, there is no need for the unit to have Wi-Fi or for someone to configure the device using Wi-Fi. The equipment is ready for use. In addition, new communication networks such as LT-M, NB-iot and 5G will allow more applications to be deployed.

 

  • Involves smart city partnerships and ecosystems

 

If we want to see all of these solutions on a large scale, then the type of collaboration between public institutions and private companies has to change. In the past, the traditional relationship was: buyer = public authority and one-time supplier = private company. This relationship does not currently provide sustainable solutions and partnerships.

 

New approaches to urban issues need to be followed (and not just), and this is the development of a strong ecosystem of partners that means many different providers offering complementary services and skills, ready to commit resources in order to innovate with cities, learn together from pilots, and then expand. The ecosystem needs to include stakeholders from different backgrounds, such as local authorities, local universities, private or public associations, start-ups and some key businesses. Needless to say, citizens as value recipients need to be engaged and constantly updated with ideas, plans and projects in their cities, as well as providing them with opportunities to share feedback and suggestions.

 

Each stakeholder needs to be able to add value to a particular part of the value chain. One company can’t provide everything, and cities shouldn’t trust one supplier with all the solutions. Partnership and co-innovation is a magic word so that cities can plan, experiment and scale smart city solutions. We can see some good examples of urban ecosystems in the UK, such as Bristol, Manchester and Bournemouth.

 

  • New business models

 

Finally, while the Internet of Things changes relationships and builds ecosystems, there is also a clear need for new business models so they can fund all these projects and move them out of the pilot. It is well known that most cities cannot provide the expensive CAPEX(upfront) investment for every new solution they want to deploy. A business model (OPEX) with a monthly or annual fee is preferable, providing everything as a service. In addition, the concept of revenue sharing or results-based charging is an idea that is being discussed a lot at the moment, and I believe we will see them used more and more.

 

All in all, cities are just scratching the surface of the data, and the opportunities for positive urban transformation through the use of technology are ample. But civic engagement and a focus on data and citizen privacy are essential, because otherwise, using technology irresponsibly or using technology for its own sake could undermine the benefits we envision for our cities. Innovative partnerships and business models as well as social and environmental responsibility are necessary to provide smart cities with a roadmap for economic, social and environmental sustainability in the 21st century.

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