This post is part of our Future of Smart Cities series in which we interview the leading founders and executives who are on the front lines of the industry to get a better understanding of what problems the industry is facing, what trends are taking place, and what the future looks like.
1. What’s the history of BreezoMeter? Where and how did you begin?
RK: BreezoMeter just celebrated its fourth birthday, and has come a long way in that short time. It all started when my wife was pregnant and we were looking for a house to buy. She has asthma, and as an environmental engineer, I knew she was at increased risk of negative health effects caused by air pollution. But we had no way of knowing what the air quality was like in different places. How could we choose a healthy place to live, if we can’t see what is in the air we breathe, but it can still make us sick? Together with Ziv Lautman, also an environmental engineer, and Emil Fisher, a software engineer, we started building spatial algorithms that would help map air pollution data and turn it into actionable advice for businesses, municipalities, and of course, end-users.
2. What specific problem does BreezoMeter solve? How do you solve it?
RK: 92% of the world’s population lives in areas that have unhealthy levels of air pollution, according to the WHO, and air pollution is considered “the silent killer,’ killing 7 million people a year worldwide.
As humans, we find it very difficult to fight a problem that we cannot see, and air pollution is often invisible. While perhaps we can see some pollutants sometimes, there are also pollutants that aren’t visible, that don’t have a smell, but can still be very harmful to our health.
So, the first challenge is to make air pollution visible, and next, we need to offer simple, actionable advice that people can take to improve their health. Oftentimes, people can easily reduce their exposure to harmful air pollutants by simply staying indoors, closing the windows, and activating an air filtration device.
A more technical problem with respect to air pollution data is its availability and relevance. Many governments of the world have monitoring stations, but these stations, with their sensors, are extremely expensive. This results in relatively sparse distribution of sensors, with two results: 1) the stations are often placed only in areas with dense populations – but these are not the only places that people live, and certainly not the only places that face the issue of air pollution – and 2) the limited number of stations contributes to a partial picture of air quality in a given region.
So, how do we provide location-based air quality information to billions of people around the world?
We collect data from governmental stations, integrate it with layers of other relevant data that affect air quality levels, such as local weather, traffic, satellite data, air dispersion models and more, and use algorithms to interpolate and model the air pollution levels.
The result of harnessing big data and using methods of machine learning is that we are able to provide highly accurate, real-time air pollution data in 67 countries (and we’re still adding more!) which is on the resolution of a city block. With this information in hand, presented in a unified, intuitive, visual manner, people and businesses can start making better decisions for their health when it comes to the air they breathe.
3. What’s the future of Smart Cities?
Prediction #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.
Prediction # 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.
Prediction # 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.
4. What are the top 3 technology trends you’re seeing 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.
5. Why are Smart Cities ripe for disruption?
RK: There is a combination of two factors. First, cities are now facing very strong challenges regarding transportation, waste and pollution. These are the 3 challenges that cities need to prioritize. Secondly, population is growing and 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 answer those 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 crowdsourcing.
About Ran Korber
Ran Korber’s ambition is to improve the health and quality of life of billions of people around the globe by providing highly accurate and actionable air quality data. He is co-founder and CEO at BreezoMeter, the leading air quality analytic company, which was voted one of Israel’s top ten promising start-ups in 2015 and was named in the prestigious 2017 Global Cleantech 100, produced by CTG (Cleantech Group). Among numerous other awards and recognition, BreezoMeter was named one of the 2017 Efficient Fifty – companies who are all about being smarter and more efficient – by JMP Securities.
Ran studied at the Technion, the Israeli Institute of Technology, ranked among the world’s top 100 universities. There he received a B.Sc. in environmental engineering, winning first prize in 2011 among the renewable energy projects sponsored by the Israel Sustainable Energy Society. While still studying at the Technion, Ran became the first Chief Environmental Officer of numerous chemical plants owned by Israel Chemicals Ltd (ICL), which represented a multinational manufacturing concern.
Widely travelled, Ran met with the former U.S President Obama at the 2015 Global Entrepreneurship Summit (GES) in Nairobi, Kenya, where he was invited to be a speaker on behalf of BreezoMeter, and also met with other famous entrepreneurs such as Brian Chesky, CEO of Airbnb.