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The first synthetic plastic Bakelite was produced on 1907, marking the beginning of the global plastics industry. However, rapid growth in global plastic production was not realized until the 1950s.  Over the next 65 years, annual production of plastics increased nearly 200-fold to 381 million tons in 2015. For context, this is roughly equivalent to the mass of two thirds of the world population. Clearly plastic waste has become a menace and almost 80% of the plastic waste ends up in rivers and eventually in oceans.

Data mining is an emerging field which will help us deal with plastic waste management. Data mining is the process of obtaining useful information from raw data by identifying patterns and establishing relationships within the data so that we can use the insights for problem solving. There a number of ways that data mining will enable us to deal with the plastic waste management such as collection and management of waste, classification of waste, tracking and decision making.

Collection and management of plastic waste.

The collection of data requires the use of Internet of Things (IoT) which collects data right from when disposal is done in households to where it ends up. The combination of data mining and IoT can greatly improve accurate collection and management of waste. This could be possible when smart bins, fitted with sensors, are created in every household. Waste management industry can access the data from the smart bins.

Classification of Waste.

Data mining can be used for classifying different types of waste in terms of sorting and type of degeneration. This is important for the recycling industry because it provides the vital information of the type of plastic that needs to be recycled. There are very many  different types of plastics, some are easier to recycle while other are extremely difficult to recycle and costly as well, therefore it’s important to classify them accordingly for easier recycling process and proper legislation put in place on which type of plastic should be banned or repurposed.


Tracking of plastic waste is very useful to enable us to understand the mobility of plastic in the environment and how it affect the ecosystem. With data mining in place especially the movement of plastics in the drainage systems such as rivers will help in reducing the amounts of plastic waste that ends up in the oceans. The collection of visual data along rivers which can then be analyzed and provide important information on river plastics.

Decision Making.

In plastic waste management, decision making involves making the policy decision regarding waste management easily with predictive patterns from the analyzed data using visualization tools such as trend lines, graphs and pie charts over a certain period of time.

Waste collection systems not only help to cut costs, however they also help to reduce the business environmental impacts as well. Proper and dedicated application of data mining process helps the plastic waste management industry to carry out their processes systematically which will leave a positive and sustainable impact to the environment.

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