Why Air Quality Data Matters to The Future of Smart Cities

Recently featured in Disruptor Daily as an expert and thought leader in the arena of Smart Cities, BreezoMeter’s CEO and Co-Founder Ran Korber explains how air quality in smart cities will permeate the success of this revolution.

Perhaps it is best to start with a basic but important question: what is a smart city? The truth is, it can mean different things, but generally speaking, it is an urban area using different types of data and sensors to provide information, with the goal of efficiently managing assets and resources.

Ran Korber Interview highlights:

Q: Why are Smart Cities ripe for disruption?

The answer to this is really a combination of two factors. First, cities are now facing severe challenges regarding transportation, waste and pollution. These are the 3 challenges that cities need to prioritize, because the second factor is that population is growing. As population grows, it becomes more and more complicated to solve the challenges above. More people means more congestion, more waste, and more pollution. Big data & machine learning can offer solutions to these challenges if they are manipulated wisely and with strong expertise.

Smart cities are transforming from a traditional model of a silo-based organization to a more collaborative, integrated service-delivery model. Cities will collaborate with each other to drive smart city innovation by entering into partnerships with each other.

Smart cities will emerge as major big data hubs with, among other types of data, environmental data being collected, analyzed and monitored in real-time by a central monitoring hub and commercial companies. This information will be used to make more informed decisions on how to improve citizens’ quality of life, optimize cities’ operations and also encourage open data platforms and crowd sourcing.

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Q: What’s the future of Smart Cities?

#1: Integrating Big Data

The future of smart cities will revolve around the ability to combine data from various sources to make better decisions in more areas of our lives, and to create better efficiencies. Pollution data can, for example, impact the transportation or mobility of people and things, the decisions relating to energy use for traffic lighting, working hours, and more.

Using big data can help to guide urban planning initiatives to help more efficiently reduce exposure to pollution at the most important times and in optimal places. For example, decisions such as where to build a new school or hospital based on source of air pollution, as going to school in a highly polluted area can highly increase the chances that children will have asthma. Similarly, hospitals in polluted areas have reported the likelihood of worse outcomes for patients. Our cities should be built in the most energy and health-efficient ways possible.

A city that wants to improve the health and experience of its citizens by influencing urban planning will need to use not just individual sensor (“field”) data from stations deployed by governments, but also incorporate IoT and big data by looking at ways to connect more elements that impact air quality.

# 2: The Informed Consumer-Citizen

There is no doubt that there has been a rise of the informed consumer, which has resulted in an increased demand for readily available, accessible, real-time, and accurate data in just about every area of life, including personal health and safety. Environmental data is becoming more available and more accessible via reliable sources, which provides the ability to amass large quantities of environmental data.

# 3: More Sensors

This third prediction is tightly tied to #2, the rise in the informed consumer, as well as #1, big data. The need for data might naturally lead to the purchase of more personal, small sensors, since it seems logical that more sensors equal more data. However, sensors measure air quality in a specific location at a specific time, thus requiring a generalization for these measurements to improve spatial coverage. Since air quality fluctuates at a faster rate than the weather during the course of the day, there are hours when air is more polluted, and different areas may be affected differently within a short period of time. Moreover, during the day there are hours and areas where air quality changes dramatically.

Simply adding more sensors will not fully address the issue. Rather, incorporating machine learning and big data can help achieve a more complete picture of what is in the air people breathe. For example, BreezoMeter uses unique (patent pending) spatial interpolation algorithms in conjunction with cutting-edge dispersion algorithms to make 7.1 billion compound calculations per hour in order to calculate the concentrations of 13 different pollutant types, and provide a uniform Air Quality Index (AQI), accurate to within 300 meters. This is the uniqueness of real-time analysis, which citizens of future smart cities will not compromise on.

Q: What are the top 3 technology trends in Smart Cities?

Trend #1: Connected Sensors – Building Another Layer of Data

Smaller and less expensive connected sensors are emerging in the market, although they are still less accurate and less regulated than official air monitoring stations deployed by municipalities/governments. The data collected from these more widely installed (and sometimes mobile) sensors will further support the collection of massive (open) data, but only in conjunction with the more established sensors that exist today. Additionally, it will be important to incorporate their data as an additional data source, rather than a substitute for big data and machine learning models. While small sensors represent a trend and perhaps a big part of the future, it is important to note that a lot of governments are already doing a lot with the existing infrastructure and partners who can mobilize the power of big data.

Trend #2: Electric Vehicles

Electric vehicles and even drones are also trends that will contribute to smart cities becoming more efficient and potentially healthier for their populations, as the efficiencies can be translated into better air quality and therefore better health.

Trend #3: Better Air Monitoring and Quality

Real-time and location-based air quality monitoring will be able to contribute to citizens making better and more informed choices about how they spend their time indoors or outdoors. Lastly, connected devices will be better equipped to help clean the air in people’s immediate environments to help reduce people’s exposure to harmful air pollutants.

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Amalia Helen
Amalia Helen

Content Lead @BreezoMeter. Passionate about environmental issues and the power of IoT, big data and connected technologies to solve the big problems of our day. Drop me a line by email or connect on LinkedIn.