Data as the content of digital twin cities
Smart technology and innovative solutions are increasingly needed to enable the sustainable and climate-resilient growth of urban conglomerates. The development of data collection systems, cloud computing, the Internet of Things (IoT), 3D modelling, and Artificial Intelligence (AI) paved the way to a new way of managing cities through digital twin cities.
Basically, a digital twin is a virtual digital model that corresponds to the physical object in the real world. When applied to a city, it allows to replicate and correlate a number of factors and systems such as the physical environment, available natural resources, infrastructure and transportation, public services, and more. The idea behind it is to tackle severe issues such as resource depletion, environmental pollution, traffic congestion, or public security, thus promoting more sustainable and livable communities.
Digital twin cities represent a booming market. According to Marketsandmarkets, the global digital twin market will reach $48.2 billion by 2026; China alone is expected to reach $17.3 billion by 2025. Despite the resounding hype, the concept is still in its early stages and many projects are still in the planning phases.
The recently published report "Digital Twin Cities: Key Insights and Recommendations" by the World Economic Forum and China Academy of Information and Communication Technology bring together some ideas and best practices to help optimize the planning, design, development and use of digital twin platforms in cities. The report refers to the SODPA model and discusses the five key elements of digital twin cities: (1) Strategy and talent development, (2) Operation and business, (3) Data and infrastructure, (4) Platform and technology, and (5) Application and scenario.
The report defines data as the ‘content of a digital twin city’, the essential component to have an accurate and granular view of urban systems. Having a reliable network infrastructure with smart sensors to collect and transmit relevant field information is indeed the precondition upon which a digital twin city operates – exactly as the neural network and neurons allow the human body to sense what happens inside and outside it.
Think of urban mobility. Digital twin models aggregate data about environmental conditions, operating transportation systems, road and traffic conditions, etc. and overlap them with geographic information systems (GIS) to create a virtual live map of the city’s transport network. This empowers data-driven decisions on route planning, traffic management, and emergency intervention when and where needed.
The above-mentioned report warns city managers not to imagine digital twin cities as a mere amalgamation of data: they are a dynamic and digital replication of cites, providing a more holistic and actionable view of urban communities.
Digital twin cities bring together the physical and digital worlds to unleash new ways of managing urban areas. They have the potential to transform cities into more intelligent entities, leading to high-quality urban development and sustainable growth.
Photo credit: JC Gellidon on Unsplash
Smart sensors to monitor heat waves
Extreme heat is marking new records. Scientists acknowledged July 4th as the hottest day on Earth in about 125,000 years, and most of the US states are experiencing burning temperatures this days. Nearly a third of Americans - about 113 million people - are currently under heat advisories, and the National Weather Service has urged people not to underestimate the risk to life.
The situation is severe in Europe too, as the continent is warming more swiftly than the global average, say the experts. While heat waves are repeatedly hitting southern Europe, a recently published report attributed 61,000 deaths in Europe to its searing temperatures last summer.
As we know, the scale of changes required to adequately mitigate climate change is wide and calls for extensive investments. At city level, buildings and mobility systems are being scrutinized, while authorities are pressured to extend shelters and health services to poorer and more marginalized people, and to reduce urban heat islands where temperatures are particularly high.
Smart technologies can help a lot and contribute to climate resiliency. Generally speaking, IoT-based systems support a more accurate tracking of power consumption and natural resources use, thus enabling data-driven decisions to save energy, water, and related CO2 emissions.
More specifically, smart environmental sensors can be implemented to efficiently monitor parameters such as temperature, humidity, solar irradiance, air quality, and more. Having hyper-local environmental data allows cities to alert residents in case of upcoming heat waves in Summer, snow or ice storms in Winter, or any other unfortunate condition.
Discover more about our Smart Environmental Sensors and how they can be used for environmental monitoring and taking immediate action to safeguard citizens’ safety: watch our video and register to download our white paper.
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A data-driven approach to environmental action
Dramatic global events and the climate crisis have made cities acutely aware of the need to increase resilience in all areas: energy, health, food, manufacturing and production, supply chains and more. We are constantly and sharply reminded of how much these areas are linked and the knock-on effects they can have on each other.
While it is impossible for a city to control everything, it’s clear that you can’t manage what you don’t measure. That’s why cities are increasingly investing in smart technologies that help them better understand what is going on and how environmental changes impact critical areas such as public health, energy resilience, transportation, and general liveability.
The need to provide accurate data is driving the development of the environmental sensor industry. Research house MarketandMarkets estimates the environmental monitoring market will be worth almost USD 18 billion by 2026, up almost a third from USD 14.5 billion in 2021, mostly due to augmented public awareness and stricter government regulations around air and noise pollution, or the growing need to manage extreme weather events such as rainstorms, flooding, or heat waves.
As effective as these sensors are, though, deploying and connecting them is not enough. Pressure is coming from all sides for cities to not just collect more environmental data, but to correlate and interrogate pieces of information across different areas to identify patterns and trends, and consequently take action.
Are cities mature enough for data-driven environmental action? And how can technology vendors support them? Find more in our paper ‘Building a data-driven approach to environmental action’ (free download upon registration) and watch our webinar to have insights from Jaromir Beranek (City of Prague), Guillermo del Campo (CEDINT-UPM, University of Madrid), and Julia Arneri Borghese (Paradox Engineering).
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Air pollution: you can’t manage what you don’t measure
Air pollution is a major threat. According to the World Health Organization, it affects 99% of the world’s population and represents one of the three main causes of premature morbidity, resulting in nearly 7 million deaths globally in 2022.
Soot (fine particulate matter air pollution, PM 2.5) is among the most hazardous pollutants and many countries around the world have specific regulations in place. In Europe, the Zero Pollution Action Plan set the ambitious goal of having an environment free of harmful pollution by 2050 and cutting the annual limit value for PM 2.5 by more than half by 2030.
The United States has made major progress in reducing air pollution thanks to the Clean Air Act, but about 20.9 million people still live in areas exceeding current legal limits. A few weeks ago, the U.S. Environmental Protection Agency proposed to strengthen the annual soot standard from a level of 12 micrograms to 9-10 micrograms per cubic meter, reflecting the latest scientific evidence to better protect public health.
However, the environmental organization NRDC (Natural Resources Defense Council) found that 118 US counties out of the 190 with average soot levels within current legal limits completely lack soot monitoring systems. “This area is home to more than 8 million people. This lack of local data collection reduces the accuracy of federal air quality forecasting […] and deprives people of crucial information they can use to better understand local air quality and protect their health”, writes the NRDC.
Can you manage air pollution if you don’t measure it? The answer is obviously no.
Governments and cities need real-time, localized, and accurate data about air quality – but also about temperature, urban heat, humidity, noise, and more – to watch changing environmental conditions and their impact on people’s health, while ensuring compliance with sustainability targets and regulations. Being environmental sensors a mature technology, nowadays they can turn from simple monitoring tools into the enablers of decision-making processes for healthier, safer, and more liveable cities.
Eager to learn how air quality and environmental sensors can contribute to citizen-centric, safe, and climate resilient urban communities? Watch our webinar – available on demand – to have insights from Jaromir Beranek (City of Prague), Guillermo del Campo (CEDINT-UPM, University of Madrid), and Julia Arneri Borghese (Paradox Engineering).
Any question? Don’t hesitate to contact us!
Monitoring urban heat islands
More than 60 million people in the US are under an excessive heat warning or heat advisory, and meteorologists say hot temperatures are likely to persist across large sections of the country for the entire Summer. Heat waves are also enveloping Europe - a clear effect of climate change and global warming.
Cities are generally warmer than rural areas, and it is increasingly important for local administrations to map the hottest neighborhoods, monitor key indicators of heat-related health risks, take action and protect vulnerable citizens and communities. However, many cities lack weather station networks that can monitor heat islands comprehensively, so they look for alternative solutions to reliably collect and correlate data about atmospheric and surface urban heat.
Several systems have been used over time for this purpose, including satellite tracking. In the 1990’s, LANDSAT TM satellite data and GIS software were used to map micro urban heat islands in Dallas, Texas, suggesting heat exposure to be significantly higher in low-income, densely populated neighborhoods. More recent research projects had similar findings: the poorest areas tend to be significantly hotter than the richest in 76% of urban US counties.
An alternative monitoring and data collection system was piloted in France by a team of researchers from the University of Toulouse. Supervised by meteorology researcher Eva Marques, their approach leverages temperature sensors in connected cars to map urban heat.
After a first experiment in the city of Toulouse, the team created temperature maps in several western European cities using a database comprising millions of car sensor measurements that manufacturers had collected for insurance purposes from 2016 to 2018. The researchers found they could reliably estimate temperature variations for spaces as small as 200 by 200 meters with fine-grained data collected at 10-second intervals. Their method proved to be effective in assessing urban heat at street level – and highly beneficial even in small cities that lack weather station networks, but nonetheless need to have reliable heat monitoring.
“Crowdsourcing data is a new hope to produce and share maps with these municipalities in the years to come,” said Marques. The challenge is ensuring data consistency and quality while scaling-up pilot projects. A robust architecture for data management and analysis is also crucial, and some cities are now planning to integrate urban heat islands monitoring in new or existing smart IoT infrastructures.