The Internet of Things solves the weaknesses of traditional monitoring systems by generating a continuous stream of accurate data in near real time, enabling planners to make more informed decisions to reduce traffic flow. However, the Internet of Things is still in its infancy, and the full potential of the Internet of Things in air pollution control will not be realized until engineers launch the next generation of wireless sensor networks, city-level LPWAN and 5G cellular infrastructure. These infrastructures need to provide data to AI algorithms, which can then trigger preventive measures in advance.

For people, cities are as attractive as magnets. According to United Nations data, nearly half of the earth’s population lives in cities with a population of more than 500,000. By 2050, this number will rise to more than two-thirds. In addition, the number of megacities with a population of more than 10 million has increased from 10 in 1990 to 28 today, and is expected to increase to 41 by 2030.

But this is not necessarily a bad thing. Well-managed metropolises encourage economic development and can improve residents’ employment prospects, housing, electricity, water, sanitation, transportation, medical care, and education. Moreover, the cost of providing services in cities is much lower than in rural areas, and environmental development is more sustainable.

But as the scale of the city expands, the problem will also multiply. One of the most difficult problems is traffic congestion. Traffic jams block the arteries of cities, hinder economic development, and have a worse impact on human health. Automobiles continuously discharge harmful exhaust gas (including atmospheric particles with a diameter of 2.5 μm or less) into the air. This PM2.5 pollution penetrates into the lungs and is considered to be the most harmful to health.

The traditional approach is to reduce pollution by controlling traffic, such as charging congestion charges or preventing certain vehicles from traveling on specific days. It is troublesome and does not take into account short-term traffic conditions such as weather and road works or accidents.

But now, through the widespread deployment of commercial air quality sensors that are wirelessly connected to the Internet of Things (IoT) with the help of low-power wireless local area networks (LPWAN), it is expected that fine-grained data can be generated to help city planners accumulate (and remove) air pollution Make a more positive response. Some more active related organizations are adopting the just-started Internet of Things to purify the air in cities, but there is still a long way to go to realize a pollution control system suitable for future smart cities.

Congested traffic

Ford Motor Company’s production line in the United States brought the convenience of independent travel to the public, and city planners quickly accepted this cultural revolution. For example, the urban planning of Los Angeles in the 1920s was mainly designed for automobiles. The city has a low population density and remote suburban areas. This is because during the ten-year rapid expansion that began in 1910, people can easily drive around. Today, Los Angeles’ transportation system has become a victim of its past success. Traffic analyst INRIX said that in 2017, the city’s congestion level ranked first in the world for the sixth consecutive year. Some companies say that commuters in Los Angeles are in peak congestion for more than 100 hours a year.

But traffic congestion is not unique to the United States. In China and India, the rapidly expanding middle class spends most of their disposable income on cars, causing serious traffic problems and getting worse. Take Mumbai as an example. The city has a population of approximately 18.5 million and has 2.3 million vehicles, which has increased by 55% in the past 7 years. In 2017, the number of new car registrations was approximately 700 per day. Vehicle congestion in Beijing is equally impressive, with 5.97 million cars in this metropolis of 21.7 million people (Figure 1).

How the Internet of Things will help control urban air pollution
Figure 1: Traffic congestion in Beijing is extremely serious. This metropolis has 5.97 million cars and a population of 21.7 million (Source: Travelerpix/

The source of particulate pollution and its impact

There are many sources of PM2.5 pollution, including coal and oil-fired power stations, household cooking, and even natural sources such as dust and sea salt. However, a study in South Korea’s Gwangju showed that more than one-third of the city’s particulate matter comes from diesel and gasoline-powered vehicles.

The situation in Beijing is similar. In late March 2017, the PM2.5 concentration in Beijing was 238μg/m3, and the city’s annual average concentration was 90μg/m3. The World Health Organization (WHO) guidelines stipulate that the average PM2.5 within 24 hours of 25μg/m3 is considered unhealthy. Residents of this Chinese city are paying a high price for travel convenience. A 2016 report from the School of Environment of Nanjing University stated that 31.8% of deaths in Beijing (and other congested cities in China) may be related to PM2.5.

Although not as bad as Beijing, Mumbai has a huge number of cars, low emission standards, and the city’s air quality is often shocking. According to the Times of India, Mumbai ranks 63rd in pollution among 859 cities in the world, and is the fourth most polluted megacity. In 2016, the city’s average PM2.5 figure was 64μg/m3. Although Beijing and Mumbai are extremely bad, Western cities have no reason to be complacent. The annual average PM2.5 in Los Angeles has reached 18μg/m3. In Europe, Paris reached a peak reading of 55μg/m3 in February 2018.

According to the World Health Organization, air pollution is the main cause of non-communicable diseases. Approximately 24% of adults die from heart disease, 25% die from stroke, 43% die from chronic obstructive pulmonary disease, and 29% die from lung cancer.

Pollution Control Version 1.0

Related agencies in many cities are working hard to control air pollution. Some cities have adopted special methods. According to a report by the British Broadcasting Corporation (BBC), Delhi, India, tried to install jet engines on flat plates and drag them to heavily polluted areas, using the thrust of the engines to push particles into the atmosphere to prevent people from inhaling them. Beijing also recently introduced a permit system that restricts non-local residents from driving into Beijing 12 times a year.

The traditional method of controlling airborne particulate matter includes deploying monitoring equipment in heavily polluted areas across the country, taking months to get a rough understanding of the pollution situation, and then adopting severe measures, such as restricting car travel or raising emission taxes to alleviate traffic congestion, until air quality improves. These measures do not take into account temporary factors such as weather and car accidents, and strict control programs will also make drivers dissatisfied, which is usually difficult to last.

Use conventional techniques to limit particulate pollution

By deploying modern Electronic devices such as sensors and webcams, some cities in the United States are achieving good results. For example, Chicago, Illinois, uses sensors mounted on lamp posts to map pollution over time in large areas of the city, while residents of Pittsburgh, Pennsylvania can use web cameras to zoom in on specific emission sources and record pollution incidents. To determine the pollution situation. Elsewhere, Louisville, Kentucky, collects data on when asthma patients use inhalers to identify heavily polluted areas.

Outside the United States, Oslo allows general vehicles to pass on bus lanes, provides a large number of charging stations and privileged parking lots, and cancels tolls for electric vehicles. Norway is the country with the most electric vehicles per capita in the world. For a country with a population of 5.2 million, there are more than 100,000 electric vehicles. Oslo’s average PM2.5 reading in 2016 was 11μg/m3. Dresden, Germany is trying to filter the particles in the air by implementing a pollution absorption “environmental protection wall” (Figure 2).

How the Internet of Things will help control urban air pollution
Figure 2: German cities such as Dresden are using “environmental protection walls” to absorb particulate pollution. (Source: Green City Solutions)

Network to improve pollution control methods

The move to reduce the number of cars entering the city is bound to have a certain impact on air quality. Fewer exhaust pipes means lower emissions. But this impact is often not as large as expected. For example, London introduced a congestion charging plan in 2003. By 2014, the traffic volume in the toll area had been reduced by nearly a quarter compared to 10 years ago. But the number of buses has increased. Since 2000, the number of taxi and private taxi trips has increased by nearly 30%.

Has the congestion charge in London improved air quality? In 2003, the average PM2.5 in London was 25μg/m3 (increased to 35μg/m3 in the central region), and in 2016, this figure was 15μg/m3 (increased to 18μg/m3 in the central region). This is a significant improvement, but this figure is still much higher than the 10μg/m3 threshold set by the World Health Organization.

The experience of London shows that the control of air pollution is a comprehensive effect of multiple factors, and changing one factor may affect other factors (sometimes this effect is even negative). To respond quickly to pollution peaks and reduce the average pollution level over a period of time requires data-a large amount of timely and accurate data.

The Internet of Things (IoT) can quickly generate, organize, and analyze data from sensors that are compact, inexpensive, and wirelessly connected to the cloud through LPWAN, enabling city planners to use big data to improve air pollution control measures.

Establish an Internet of Things air pollution control system

An air pollution control system based on the Internet of Things will contain four basic elements:

● Wireless air quality sensor for monitoring and reporting pollution levels;
● LPWAN connection to transmit data from the short-range wireless sensor network to the cloud;
● Cloud server, capable of analyzing data from tens of thousands of wireless sensors;
● Predictive algorithms are used to suggest measures that need to be taken to prevent air pollution from reaching dangerous levels.

Compact, inexpensive, battery-powered PM2.5 sensors are being put into commercial use. Data from these sensors can be complementary to data from metal oxide semiconductor (MOS) gas sensors. The MOS gas sensor can be adjusted to focus on detecting nitrogen dioxide (NO2) and carbon monoxide (CO), which are prevalent in exhaust gas, so that users can understand the overall situation of air pollution caused by vehicles. Sensors are usually used in conjunction with radio frequency transceivers that use battery-friendly wireless protocols such as Bluetooth Low Energy (BLE) or Zigbee so that data can be continuously transmitted over the network. Since PM2.5 sensors and gas sensors are cheap and unobtrusive, they can be widely deployed throughout the city to monitor air pollution.

LPWAN establishes a robust and secure remote connection between the local area network (LAN) of short-range wireless sensors and the cloud. Some LPWAN technologies are currently being commercialized, including cellular IoT technologies such as LTE-M and NB-IoT, LoRaWAN, Sigfox and Weightless (Figure 3).

How the Internet of Things will help control urban air pollution
Figure 3: LPWAN establishes a remote connection between the wireless sensor network and the cloud. (Source: metamorworks/

Once the data is uploaded to the cloud via LPWAN, it can be sorted and analyzed, so as to get a detailed understanding of changes in urban air pollution in near real-time. With the establishment of historical databases, algorithms can use past events to accurately predict how the situation will develop in the future, so that relevant agencies can take preventive measures when needed. Armed with this information, more subtle actions than traditional measures can be taken, such as regulating traffic flow, temporarily reducing road tolls for environmentally friendly vehicles, and quickly advising citizens to avoid areas that may quickly become dangerous through cellular networks or the Internet.

Early practitioners


London is using its experience in congestion control to cooperate with the cellular infrastructure provider alliance GSMA to launch a trial based on the Internet of Things in the Royal borough of Greenwich. This project called “Smart London” combines sensors, cellular IoT LPWAN and big data analysis technology. Sensor networks include low-cost static and mobile devices connected to vehicles, bicycles, and pedestrians. The data from the existing Greenwich air quality monitoring station can supplement the data from these sensors.

These data enable relevant agencies to make early decisions. For example, when the pollution level in the user’s area may rise, the air quality detection data can be sent to users who have subscribed to the AirTEXT service through a smart phone. According to the results of data analysis, the district has adopted some measures to reduce pollution, such as banning the use of large transport trucks and hiring contractors who deliver packages by bicycle.

Although the Greenwich experiment is still in its infancy, the level of PM2.5 has dropped moderately (Figure 4).

How the Internet of Things will help control urban air pollution
Figure 4: Greenwich, London, air pollution control systems based on the Internet of Things are having an impact on PM2.5 levels. (Source: Royal District of Greenwich)


The South Korean capital has an air pollution monitoring program based on the Internet of Things, operated by a local telecom operator. As a developed country, South Korea’s air quality is very poor. In late March 2018, Seoul’s PM2.5 peak reached 100μg/m3. The Korean Air Map project collects air quality data through infrastructure across the country, including 4.5 million telephone poles, 330,000 mobile base stations, 60,000 public telephone booths, and 4,000 switching centers in South Korea. In addition to PM2.5 and PM10 levels, the sensor also tracks temperature, noise level and humidity. Sensor data is relayed to the company’s existing 4G and new 5G mobile networks via the cellular Internet of Things LPWAN. After this information is collected, it will be transmitted to the company’s aerial map platform every minute.

So far, Seoul’s air quality control measures have had limited effects. The city government has taken measures to encourage people not to drive, such as waiving public transportation fees during peak hours, closing parking lots, and imposing fines and bans on certain diesel vehicles when pollution peaks, but these measures have only reduced about 2%. Traffic. According to US News & World Report magazine, a South Korean government spokesperson stated that the improvement of PM2.5 in the past five years has stagnated.

Take action based on air quality data

The experience of London and Seoul shows that detecting pollution is one thing, and taking action based on information to make a meaningful impact is another. However, the Internet of Things is still in its infancy. In the medium term, city planners will benefit from a large amount of current and historical data accumulated by extensive monitoring networks and cloud storage.

Improve response measures

How to react to the data generated by the Internet of Things depends largely on the political environment, but technology can ensure that the public obtains accurate information in a timely manner and can play a greater role in the decision-making process. In this way, citizens are more likely to accept measures that make personal actions more costly or even restrictive.

Introduce enhanced sensor technology

Advances in low-power wireless and semiconductor technology have made air quality sensors cheaper, smaller, less maintenance work, more accurate, and cover longer distances. Therefore, future pollution control programs will be able to utilize more sensors and higher detection accuracy.

Extend the sensor mesh network

The widespread deployment of sensors also benefits from technological developments such as Bluetooth® mesh networking and Zigbee®’s inherent mesh network compatibility. The network allows sensors to communicate with each other, reducing the number of LPWAN nodes required because data can be aggregated to a point on a large network and relayed from that point. This arrangement reduces cost and complexity.

Deploy city-level LPWAN

LPWAN plays a key role in the construction of the Internet of Things. Cellular IoT has a first-mover advantage, because most cities have already established 4G (and increasingly 5G) networks, attracting metropolitan cellular IoT service providers in the early stages. LoRaWAN, Sigfox and Weightless are busy building infrastructure in major cities to support their technologies. Once in place, these LPWANs will provide a backbone network to quickly and cheaply deploy wireless sensor networks in any area of ​​the city.

Act ahead with artificial intelligence

Based on the huge data resources and the powerful functions of the server farm, engineers will develop algorithms that intelligently consider the complex interaction of various factors affecting air pollution, make accurate predictions, and propose early (and subtle) action recommendations. To reduce the degree of danger. For example, the air purification plant under construction in South Korea will automatically start when air pollution reaches a critical value, while Chinese drones spray water or chemicals in heavily polluted areas to wash away accumulated PM2.5.


Although cities still have to work with diesel and gasoline vehicles, the PM2.5 emitted from exhaust is a potential hazard to human health. Most cities are aware of the productivity loss and health system burden caused by respiratory diseases, and some cities are already working hard to reduce pollution levels. These pioneering efforts are commendable, but the implementation costs are high, the management is complicated, and the results are limited.

The Internet of Things solves the weaknesses of traditional monitoring systems by generating a continuous stream of accurate data in near real time, enabling planners to make more informed decisions to reduce traffic flow. However, the Internet of Things is still in its infancy, and the full potential of the Internet of Things in air pollution control will not be realized until engineers launch the next generation of wireless sensor networks, city-level LPWAN and 5G cellular infrastructure. These infrastructures need to provide data to AI algorithms, which can then trigger preventive measures in advance.

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