The Financial Express

AI for low carbon economy

| Updated: October 12, 2018 21:42:42

-Reuters file photo -Reuters file photo

Production is a direct contributor to carbon emission, causing pollution and climate change. The higher the production, the more the pollution and worsening climate change effect. Such inevitable effect of production has raised both pollution and climate change effect to an alarming level. What could be an alternative to this inescapable reality? Even countries like Bangladesh at very early stage of development are facing call for regulatory measures to reduce carbon emission. To meet our growing consumption, we have no alternative to increasing production. The option that we have is to reduce wastage, increase efficiency, and develop cleaner alternative to production. Although the progression of industrial age is hastening both pollution and climate change, human like intelligent machine technology, commonly known as artificial intelligence (AI), could be a means to lower the negative consequences. As opposed to regulation, artificial intelligence perhaps has the possibility to intensify competition for increasing profit through lowering pollution and climate change effect.

GROWING POLLUTION CONCERN: According to a Reuters report, "pollution caused nine million deaths in 2015 - three times more than AIDS, tuberculosis and malaria combined." Among the worst affected countries, India suffered worst, with 2.5 million people dying early because of pollution, followed by China with 1.8 million deaths. Research finding reported in The Lancet medical journal indicate that one in six of all deaths worldwide are caused by pollution; unfortunately the vast majority of them is occurring in developing countries. Air pollution has already reached an unbearable level in major cities of South Asia. Air pollution has been the cause of yearly death of almost 15,000 people in Delhi. According to different reports, ambient air pollution caused by industries, cars and trucks, among others, caused 4.2 million global deaths in 2016.

WORSENING CLIMATE CHANGE EFFECT: According to the finding of Union of Connected Scientists, higher ozone concentration due to rising temperature is worsening. Ground high ozone concentration exacerbates lung diseases such as asthma and can cause breathing difficulties even in healthy individuals. According to certain estimates, even if all countries keep their Paris climate pledges, by 2100, it is likely that average global temperatures will be 3?C higher than in pre-industrial times. It's being estimated that USA will suffer from an average of $5.4 billion in health impact cost associated with the climate change penalty on ozone in 2020. With growing production, as we keep warming up the planet, climate change impacts are worsening. One of the implications of such deteriorating warming effect is that in 2016, there were 772 weather and disaster events, thee times the number that occurred in 1980.

AI TO REDUCE POLLUTION AND EMISSION: Artificial intelligence is often found synonymous with terms like deep learning, machine learning, big data, Robotics, Industry 4.0, and data analytics. In essence, it's about the machine capability of sensing, perceiving, reasoning and deciding about actions. Basically, artificially intelligent machines upon processing sensor data optimise the action for increasing efficiency and reducing wastage. By adding these capabilities to production machinery, it is possible to reduce pollution and emission and save money. And most importantly, the cost of AI in doing so will perhaps be less than the saving. As a result, as opposed to increasing cost (thereby decreasing profit) to comply with the regulation, the application of AI in production has the possibility of intensifying competition for reducing negative consequences on climate change and pollution for increasing profit. Here are few examples.

AI IN AGRICULTURE: Data from sensor's monitoring of soil moisture, ingredient composition, plant health, and temperature could be fed to smart pump for optimum watering. Such data could also be used to determine the best times to plant, spray and harvest crops. This will likely increase efficiency, enhance yields, and lower use of water, fertilizer and pesticides, resulting in less pollution and emission. According to certain reports, smart irrigation systems can save up to 45 per cent water during the dry season, and around 80 per cent of water in the rainy season when compared to manually operated watering systems.

AI IN TRANSPORTATION: The use of fuel cell or battery to realise the dream of emission-free vehicles turns conventional automobile into an artificially intelligent smart machine.  Diverse sensors feed data and they are processed by software to manage energy, ensure safety and drive the motors. For example, a typical fuel cell stack uses more than a dozen sensors monitoring different parameters including hydrogen concentration, hydrogen in air, carbon monoxide level, ammonia and sulfur compound. Similarly, on board central processing unit of electric vehicle gathers signals from various onboard sensors. In the absence of the growth of AI technology, electric vehicle whether run by battery or fuel cell could not have been the reality.

AI IN ENERGY PRODUCTION AND CONSUMPTION: AI is increasingly being used to manage the intermittency of renewable energy so that more micro sources and storage can be incorporated into the grid to make renewable as substitute to polluting energy. A modern wind turbine is no longer a passive machine. Sensors built in different parts of the turbine continuously feed data for optimum operation. Sensors are at the core of smart grid technology offering the opportunity of micro producers to sell power to the national grid. Machine learning and artificial intelligence are being used to identify vulnerabilities in the grid, and restore power more quickly when failures occur. AI has also the potential to reduce energy wastage. As a matter of fact, energy efficiency is a core component of Industry 4.0. Commercial building and facilities are among the main IoT use for improving the energy efficiency, resulting in energy saving up to 15 per cent. 

AI IN MANUFACTURING: Among all the sectors, manufacturing appears to have the potential to be the largest beneficiary of artificial intelligence in reducing wastage, improving quality, and minimising energy bill. For example, a closed loop intelligent control system of boilers is saving as high as 20 per cent energy. Similarly, AI powered food cutting machine is saving 5 to 7 per cent food, and increasing safety. Similarly, intelligent control is reducing the emission and even supporting profitable recovery of chemicals and other minerals from production byproducts.

The question could be: can developing countries afford AI solution? Some of the AI solution could be quite complex, like modeling of global climate effect. Developing certain AI innovations often also need significant investment. For example, the R&D spending for developing self-driven cars has already reached $80 billion. But many productive activities, which require far less complex AI intervention, could be very much within the reach of industries of developing countries. Often sensors, tiny processors (in the form of, say, smartphones) and actuators could cost just a couple of hundred dollars. Software containing relatively simple AI algorithm could often play meaningful role, such as turning off the pump once water level in the field reaches the desired level, or optimally feeding fish or poultry birds. Moreover, AI solution development for simpler tasks will lead to developing higher-level productive knowledge to apply increasing science into production through software, for achieving greater yield causing less pollution and emission. AI has a large scope for making interventions, starting from understanding the evolving dynamics of pollution and climate change to taking actions in production process for intensifying competition as well as adopting smart regulation and enforcing them to fight pollution and climate change.

M Rokonuzzaman Ph.D is academic, researcher and activist on Technology, Innovation and Policy.

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