Saturday, March 6, 2021
  • Setup menu at Appearance » Menus and assign menu to Top Bar Navigation
Advertisement
  • AI Development
    • Artificial Intelligence
    • Machine Learning
    • Neural Networks
    • Learn to Code
  • Data
    • Blockchain
    • Big Data
    • Data Science
  • IT Security
    • Internet Privacy
    • Internet Security
  • Marketing
    • Digital Marketing
    • Marketing Technology
  • Technology Companies
  • Crypto News
No Result
View All Result
NikolaNews
  • AI Development
    • Artificial Intelligence
    • Machine Learning
    • Neural Networks
    • Learn to Code
  • Data
    • Blockchain
    • Big Data
    • Data Science
  • IT Security
    • Internet Privacy
    • Internet Security
  • Marketing
    • Digital Marketing
    • Marketing Technology
  • Technology Companies
  • Crypto News
No Result
View All Result
NikolaNews
No Result
View All Result
Home Artificial Intelligence

AI Being Tapped to Help Improve Air Quality 

September 4, 2020
in Artificial Intelligence
AI Being Tapped to Help Improve Air Quality 
585
SHARES
3.3k
VIEWS
Share on FacebookShare on Twitter

Scientists and entrepreneurs are exploring the use of AI to help measure air quality to identify tiny particles, and proactively manage remediation systems if necessary. (Credit: Getty Images)  

By AI Trends Staff 

You might also like

Autonomous Cars And Minecraft Have This In Common  

Three Finalists Selected in $4.5 Million Watson AI XPrize Competition  

How to Meet the Enterprise-Grade Challenge of Scaling AI 

Scientists are exploring the use of AI to improve air quality with systems that can detect infinitesimally small particles in the air.  

A team at Loughborough University in England is focused on detecting ‘PM2.5’ particulates in the air, particles with a diameter of 2.5 micrometres, which is more than 100 times thinner than a human hair. Such fine particles can travel into the respiratory tract, penetrate deep into the lungs, and even enter the bloodstream. 

In 2013, a study involving 312,944 people in nine European countries revealed that there was no safe level of particulates. PM2.5 particulates were found to be particularly deadly, blamed for a 36% increase in lung cancer according to a recent account in Engineering & Technology. Worldwide exposure to PM2.5 contributed to 4.1 million deaths from heart disease and stroke, lung cancer, chronic lung disease, and respiratory infections in 2016. 

The innovation of the system built by the Loughborough researchers is the ability to predict PM2.5 levels in advance, from one to several hours, and one to two days ahead. The system interprets a range of factors and data used for prediction, leading to a better understanding of weather, seasonal and environmental factors that can impact PM2.5 levels in the air. It also has the capability to be used as an air pollution analysis tool for use in a carbon credit trading system. 

The Loughborough team created the system with AI machine learning with training for the algorithms based on public historical data on air pollution in Beijing. China was selected as the focus because 145 of 161 Chinese cities have serious air pollution problems. 

The developed system will now be tested on live data captured by sensors deployed in Shenzhen, China. 

Qinggang Meng, Professor, Loughborough University, England

Project leader Professor Qinggang Meng stated, “Air pollution is a long-term accumulated challenge faced by the whole world, and especially in many developing countries. The project aims to measure and forecast air quality and pollution levels. We also explore the feasibility of linking the real-time information on carbon emission to end-to-end carbon credit trading, thus dedicating to carbon control and greenhouse gas emission reduction.” 

He added, “We hope this research will help lead to cleaner air for the community and improve people’s health in the future.” 

According to a recent report by Greenpeace, 22 of the 30 most polluted cities in the world are in India. The report recommends India have 4,000 air monitoring stations to check air quality, but today India has approximately 160 air monitoring stations, less than 5% of the recommended number, according to a recent account in YourStory, a media platform in India. 

A number of the new monitoring stations have been deployed in Delhi, which has provided a needed source of air pollution data, to which AI can be applied to further track and predict the growth and reduction of air pollution.   

AI can also be helpful in modelling the chemical reactions between pollutions. Algorithms like Atmospheric Transport Modelling System (ATMoS) help scientists understand PM2.5 concentrations. More advanced algorithms that help in understanding and predicting smog, haze, visibility, and observe meteorological interventions to help manage air quality.  

Startup AirVisual Sells Air Quality Management Devices 

Yann Boquillod, founder AirVisual

The startup community is seeing opportunity in the application of AI to the management of air quality. Startup AirVisual was founded in 2015 by French entrepreneur Yann Boquillod, to apply AI and sensor technology to monitor air quality. The company was acquired in 2017 by Swiss air quality company IQAir and is based in Beijing, where it maintains air quality data from around the world. 

In a recent interview with Veolia Institute Review, Boquillod outlined his reasons for founding the company and described where it stands today. He founded the company soon after moving to China. “I wanted to use my understanding of big data and artificial intelligence to address the problem of air quality,” he stated. “With my business partner, we decided to set up AirVisual in China because the local logistics and supply chains provide a real advantage compared to alternative locations. Also, the speed of project development in China allowed us to grow our company very quickly.” 

At the time, systems to monitor air quality were expensive, costing $30,000 to $50,000 for outdoor air; nothing was available to monitor indoor air. AirVisual devised small sensors, first called “Nodes” and now known as AirVisual Pro. The sensors measure fine particles which have health impacts, the concentration of CO2 to assess the ventilation in enclosed space, and temperature and humidity data. 

AirVisual Pro is a portable personal device that uses a laser to count the number of particle-related interruptions in a stream of air directed by a tiny fan. The apparatus measures up to six pollutants present in the air. The data is sent to the cloud for analysis by an AI system, and remediation is a function of the results. Instructions are then sent directly to connected purification and ventilation systems, providing for proactive management of indoor air quality.  

For the outdoors, the company is maintaining AirVisual Earth, an interactive map that cross-references official data from each country’s air quality measurement services, to produce a global image of particle pollution. “Our goal is to equip the planet with an extensive network of sensors to create a real-time global pollution map with as much granularity as possible,” Boquillod stated. 

Where data is hard to access, such as in vast uninhabited regions, and in parts of the world where sensors and public data do not exist, the company uses satellite images and meteorological forecasts to model fine particle concentrations. 

Today the company has over 100,000 AirVisual sensors running worldwide, with indoor sensors in 120 countries and outdoor sensors in 80 countries. The company’s app currently has 10 million users. 

Read the source articles in Engineering & Technology, a report by Greenpeace, an account in YourStory and in Veolia Institute Review. 

Credit: AI Trends By: Allison Proffitt

Previous Post

A Deep Computer Vision, Machine Learning Patent Surfaces Covering the Possible use of Specialty cameras for the iPhone & Wearables

Next Post

Gregg Popovich Should Leave the Spurs, but Not for the Reason You Think

Related Posts

Autonomous Cars And Minecraft Have This In Common  
Artificial Intelligence

Autonomous Cars And Minecraft Have This In Common  

March 5, 2021
Three Finalists Selected in $4.5 Million Watson AI XPrize Competition  
Artificial Intelligence

Three Finalists Selected in $4.5 Million Watson AI XPrize Competition  

March 5, 2021
How to Meet the Enterprise-Grade Challenge of Scaling AI 
Artificial Intelligence

How to Meet the Enterprise-Grade Challenge of Scaling AI 

March 5, 2021
Convergence of AI, 5G and Augmented Reality Poses New Security Risks 
Artificial Intelligence

Convergence of AI, 5G and Augmented Reality Poses New Security Risks 

March 5, 2021
Survey Finds Many Companies Do Little or No Management of Cloud Spending  
Artificial Intelligence

Survey Finds Many Companies Do Little or No Management of Cloud Spending  

March 5, 2021
Next Post
Gregg Popovich Should Leave the Spurs, but Not for the Reason You Think

Gregg Popovich Should Leave the Spurs, but Not for the Reason You Think

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

Recommended

Plasticity in Deep Learning: Dynamic Adaptations for AI Self-Driving Cars

Plasticity in Deep Learning: Dynamic Adaptations for AI Self-Driving Cars

January 6, 2019
Microsoft, Google Use Artificial Intelligence to Fight Hackers

Microsoft, Google Use Artificial Intelligence to Fight Hackers

January 6, 2019

Categories

  • Artificial Intelligence
  • Big Data
  • Blockchain
  • Crypto News
  • Data Science
  • Digital Marketing
  • Internet Privacy
  • Internet Security
  • Learn to Code
  • Machine Learning
  • Marketing Technology
  • Neural Networks
  • Technology Companies

Don't miss it

Microsoft Exchange zero-day vulnerabilities exploited in attacks against US local governments
Internet Security

Microsoft Exchange zero-day vulnerabilities exploited in attacks against US local governments

March 6, 2021
Hands-on Guide to Interpret Machine Learning with SHAP –
Machine Learning

Hands-on Guide to Interpret Machine Learning with SHAP –

March 6, 2021
$100 in crypto for a kilo of gold: Scammer pleads guilty to investor fraud
Internet Security

$100 in crypto for a kilo of gold: Scammer pleads guilty to investor fraud

March 6, 2021
Revolution by Artificial Intelligence, Machine Learning and Deep Learning in the healthcare industry
Machine Learning

Revolution by Artificial Intelligence, Machine Learning and Deep Learning in the healthcare industry

March 6, 2021
Deploy AI models -Part 3 using Flask and Json | by RAVI SHEKHAR TIWARI | Feb, 2021
Neural Networks

Deploy AI models -Part 3 using Flask and Json | by RAVI SHEKHAR TIWARI | Feb, 2021

March 6, 2021
These two unusual versions of ransomware tell us a lot about how attacks are evolving
Internet Security

These two unusual versions of ransomware tell us a lot about how attacks are evolving

March 6, 2021
NikolaNews

NikolaNews.com is an online News Portal which aims to share news about blockchain, AI, Big Data, and Data Privacy and more!

What’s New Here?

  • Microsoft Exchange zero-day vulnerabilities exploited in attacks against US local governments March 6, 2021
  • Hands-on Guide to Interpret Machine Learning with SHAP – March 6, 2021
  • $100 in crypto for a kilo of gold: Scammer pleads guilty to investor fraud March 6, 2021
  • Revolution by Artificial Intelligence, Machine Learning and Deep Learning in the healthcare industry March 6, 2021

Subscribe to get more!

© 2019 NikolaNews.com - Global Tech Updates

No Result
View All Result
  • AI Development
    • Artificial Intelligence
    • Machine Learning
    • Neural Networks
    • Learn to Code
  • Data
    • Blockchain
    • Big Data
    • Data Science
  • IT Security
    • Internet Privacy
    • Internet Security
  • Marketing
    • Digital Marketing
    • Marketing Technology
  • Technology Companies
  • Crypto News

© 2019 NikolaNews.com - Global Tech Updates