India, with a population of over 1.3 billion people, is one of the world’s major garbage producers, creating 63 million tonnes of municipal solid waste (MSW) per year. Plastic trash and e-waste account for 5.6 million tonnes and 15 million tonnes, respectively. Managing and processing this garbage has traditionally been a mostly human process across the world, but several governments have recently begun to use Artificial Intelligence (AI) to do the same.
In 2017, the Indian government established the ‘Task Force on Artificial Intelligence for India’s Economic Transformation’ under the Commerce and Industry Department, with the goal of harnessing AI for economic advantages and developing a legislative framework to speed up the implementation of AI technology. In December 2018, the Union Cabinet formally established the task committee. This aided in the expansion of AI applications in India. However, in India, the use of AI is currently focused on three industries: healthcare, agriculture, and fintech. Given that trash management is around USD 15 billion business in India, AI applications in the waste management industry have strong growth potential.
The waste processing cycle consists of four key steps: trash disposal, waste collection, waste sorting (at waste processing factories), and lastly waste processing/treatment. South Korea, Finland, and Australia have started utilising AI to tackle three of the four phases of waste management. RFID tags measure total waste created and determine suitable waste collection schedules, while autonomous robots function as waste sorters to sort and match rubbish based on specified criteria. One major benefit is that intelligent garbage cans and waste sorters are more efficient than employees, and they can increase their efficiency over time by analysing their own historical data.
Over 10,000 tonnes of plastic garbage is not collected in India, when an estimated 26,000 tonnes of plastic waste is created every day. The five cities of India – Delhi, Mumbai, Bengaluru, Chennai, and Kolkata create half of the country’s plastic garbage. Maharashtra and Delhi are the states that generate the most MSW and plastic trash, respectively where AI technology can be put to good use. Furthermore, employees in India’s MSW labour, particularly in the informal sector, are exposed to untreated waste due to a lack of awareness and insufficient resources. For example, during the current corona pandemic, two independent researchers conducted a telephone poll of 214 sanitation employees in five states and two metro areas and discovered:
E-waste, plastic trash, and MSW also pose major health risks to employees. Inadequate solid waste management has been related to 22 human illnesses in the United States, according to the US Public Health Service.
In such a circumstance, deploying AI can significantly enhance public health by lowering the risk of MSW-related illnesses.
Countries all around the globe have recognized the advantages of AI and are investing heavily in it. The State Council of the People’s Republic of China, as a global leader in AI search, has set a target for itself to become a $150 billion AI global leader by 2030. The United States, which is famed for its tech culture, has committed $10 billion in venture capital financing to AI. In 2017, the UK, which already had 121 AI-enabled businesses, channeled nearly 38% of all venture money into AI, despite the UK government approving $78 million in financing for robotics and AI research. The Canadian government also pledged $125 million to AI research in the same year. Russia invests $12.5 million in AI per year. In fact, Russian President Vladimir Putin has stated that whoever leads AI in the near future will dominate the globe.
Some Indian firms have begun creating AI products such as trash sorters for processing facilities and water purification systems. However, these are only a few droplets in the ocean. Given the large amount of trash produced and India’s growing population, using AI in waste management can have substantial benefits for the entire ecosystem while also reducing the load on the public health system.