India, June 5,
2025: Yandex
B2B Tech, Yandex School of Data Analysis, and the Far Eastern Federal
University (FEFU), have developed and open-sourced a neural network designed to
streamline coastal waste cleanup in hard-to-reach regions. Deployed
successfully in the remote areas of South Kamchatka Federal Nature Reserve, the
technology is now being tested in the Arctic and beyond.
Aligned with World
Environment Day 2025’s focus on ending plastic pollution, this open-sourced
solution can help environmental agencies and volunteers accelerate solid waste
removal, including plastics, in ecologically sensitive zones worldwide.
India’s plastic
pollution crisis
India is the world’s
largest plastic polluter, with 9.3 million tonnes of plastic waste annually, of
which 126,513 metric tonnes reach oceans via rivers. This
kind of pollution poisons ecosystems, disrupts food chains, and threatens
marine biodiversity and human health. For instance, The Gulf of Mannar, home to
over 4,200 species, faces coral reef threats as plastic waste suffocates and
blocks sunlight, endangering over 8% of reefs. The Sundarbans, the world’s
largest mangrove forest, receives 40,000 tonnes of plastic annually, disrupting
breeding grounds and reducing local fish, shrimp, and crab catches by up to
15%, directly harming local livelihoods.
A significant part of
the plastic waste accumulates along India’s 11,098-kilometer coastline,
with reports revealing that 90% of waste found on the
country’s beaches is plastic, including bottles, caps, and polystyrene
products. Managing this waste is often challenging due to the remoteness of
polluted areas and difficulties in estimating the number of volunteers and
equipment needed for cleanup.
With machine learning
automating waste detection and analysis, the neural network developed by Yandex
and FEFU researchers now streamlines pollution assessment, offering a faster,
cost-effective alternative to outdated methods — a critical step in combating
the marine crisis globally.
Proven impact and
opportunities for global adoption
During expeditions in
Kamchatka’s nature reserves, the neural network revealed that 33–39% of coastal
waste was plastic containers and packaging, while 27–29% derived from
industrial fishing. By deploying the tool, volunteer teams cleared 5 tons of
waste four times faster than traditional methods, mobilizing
an optimal number of volunteers and determining the pieces of equipment needed
for the cleanup.
Further project
development in 2025 includes deployments across Far Eastern and Arctic national
parks, where challenging terrain complicates waste management.
Addressing the
pressing issue of pollution, this solution can be further developed and
implemented by local volunteer teams and government agencies in India and other
countries with coastal areas, riverbanks, and similar environments, enabling
more effective solid waste monitoring and cleanup. Additionally, having an open
codebase, it can be customized to detect new types of waste, monitor endangered
species, and support other environmental efforts.
How the AI solution
works
The AI solution
development leveraged computer vision, specifically semantic image
segmentation, to automate solid waste detection. This method divides images
into pixel groups, assigning each to a specific waste type: fishing nets, iron,
rubber, large pieces of plastic, concrete, and wood, achieving over 80%
accuracy.
The neural network
then maps waste locations, estimates volume and weight, and calculates the
required workforce and equipment (for instance, dump trucks, all-terrain
vehicles). This data-driven approach optimizes logistics, reducing cleanup time
and costs.
The neural network can
be integrated with various mapping tools, such as the open-source QGIS.
The neural network
codebase is fully open-sourced and available on GitHub. Environmental agencies and volunteer
organizations around the world can use the model for free and modify it for
their own pollution management tasks.
About Yandex
Yandex is a global
technology company that builds intelligent products and services powered by
machine learning. The company aims to help consumers and businesses better
navigate the online and offline world. Since 1997, Yandex has been delivering
world-class, locally relevant search and information services and has also
developed market-leading on-demand transportation services, navigation
products, and other mobile applications for millions of consumers across the
globe.
