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Our planet is drowning in plastic pollution, especially single-use plastic. One million plastic drinking bottles are purchased every minute, while up to 5 trillion single use plastic are used worldwide every year.

Half of all plastic produced is designed to be used only once and then thrown away. Almost 80% of these plastic end up in our drainage systems such as rivers. Rivers carrying these plastics end up in oceans. There is a huge growing problem here, isn’t it?

The single-use plastic products are everywhere. For many of us, they have become integral to our daily lives. There are types of plastics in production today. I will discuss each one of them and their uses and use statistical data to propose on ways of which data can help to deal with this plastic problem.


Polyethylene terephthalate (PET) which is used in making water bottles, dispensing containers, biscuit trays

High-density polyethylene (HDPE) used to make shampoo bottles, milk bottles, freezer bags

Low density polyethylene (LDPE) used to make paperbags, trays, containers food packagings

Polystyrene (PS) used to make cutlery plates and cups


Expanded polystyrene (EPS) used to make protective packaging and hot drink cups.

We need to curb the flow of plastic at its source, mostly from households, but we also need to have a paradigm shift in how to dispose waste, most importantly plastic waste. Rivers are the highest ‘consumers’ of these plastics.

Only 9% of all plastic waste ever produced has been recycled. About 12% has been incinerated while the rest 79% has accumulated in landfills, dumps most of it in rivers.

Rivers carry plastic waste from deep inland to the sea, making them major contributors to ocean pollution. A staggering 8 million tons of plastic end up in the world’s oceans every year. This is a huge amount of plastic flowing in the ocean at the writing of this script. How do we make use of data to deal with this problem?

Computer vision

Computer vision involves the use of image data collected and manipulating it to enable classification of the images, identifying them and making decisions on them.

Image data can be collected along rivers real-time or different points in time. The images taken of the debris flowing in the river, through computer vision, can help in identifying the type of plastic. This is an important information that will help in understanding the types of plastic flowing in rivers.

Weight Data of Plastic Waste.

Methods of trapping waste that flows in rivers are being developed. Chemolex Limited, a company based in Nairobi Kenya, is among many companies worldwide that are developing plastic capture devices to be used to trap waste in rivers. It is important to weigh the amount of waste trapped by these devices, to know the efficiency of these devices. This captured debris contains plastics which must be weighed and segregated into different types of plastic. This weight data will help in developing the recycling strategy for the sorted plastic. This will as well help in the developments policy documents by government agencies involved in protecting the environment.

Source plastic data.

Most of plastic waste originates from households and industries. Over 50% ends up in drainage systems such as rivers and streams which eventually ends up in oceans and lakes. The data of the households will help in formulating strategies of creating behavioral changes in how the plastic waste is managed at source.

Hydrological Data.

Hydrological data is vital in understanding the course of the river and how much plastic waste can be transported by the river course. This information can assist is deciding which location will be ideal for setting up of plastic capture devices. This type of data includes river depth, average rainfall in the area, river width which is very vital in understanding the amount of plastic the river carries.

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