Page 63 - Plastics News Issue October 2025

TECHNOLOGY NEWS
ADVANCED SORTING TECHNOLOGIES IN PLASTIC RECYCLING:
A DEEP DIVE INTO THE FUTURE OF WASTE MANAGEMENT
he issue of plastic waste is one of the most
current problems of the current epoch.
TPlastics have infiltrated our entire lives,
encompassing names of packaging material and
consumer products, and have left mountains of
waste that are straining our ecosystem. This is
not only an act of a decrease in consumption
but also in the way we recycle. The innovative
sorting technologies of recycling plastics lie at
the very heart of this change, which are trans-
forming the principles of efficiency, precision,
and sustainability.
Why Advanced Sorting Matters in Plastic Re-
cycling
One common challenge that has been experi-
enced since the inception of recycling has al-
ways been the lack of a proper system to sepa-
rate mixed plastics into separate streams that
October 2025
are reusable. Poor separation results in pollution
of produce, and this makes the recycled mate-
rials not useful in high-value applications. The
industries that consume high-purity recycled
plastics, like packaging, the automobile industry,
and consumer goods, have never required them
more than they do currently. This has compelled
technology developers, researchers, and recy-
clers to invest in something that transcends me-
chanical sorting very much.
Nowadays, AI-based waste sorting, optical sort-
ing during plastic recycling, and the introduction
of near-infrared (NIR) sensors to plastics allow
plants to reach the accuracy levels that were
unimaginable ten years ago. The outcome is a
world where discarded bottles, films, and con-
tainers can be repurposed into new raw materi-
als in an efficient way, and this brings the vision
of a circular economy of plastic recycling closer
to reality.
AI-Powered Waste Sorting: A Digital Brain in
Recycling Plants
So, what will happen when artificial intelligence
is introduced to waste management? The solu-
tion would be AI-based waste sorting that would
directly introduce the power of machine learning
and automation to recycling plants. Compared
to the manual separation that requires a lot of
labor, is prone to error, and slow, AI-powered
systems can analyze vast quantities of waste
at light speed. Pattern-recognition algorithms,
cameras, and sensors monitor even tiny varia-
tions between plastics that appear to be identi-
cal to the human eye.
The use of deep learning in the identification of
PLASTICS NEWS 63