New Technologies Towards Better Waste Management: AI and Machine Vision


Waste production is an unavoidable phenomenon in an ecosystem and any society. Human society generates billions of tons of waste every year, with the production rate increasing at an alarming rate. From a simple rural household producing municipal waste to online services where  paper writer  work 24/7on power-consuming electronic devices, waste and by-product generation is everywhere.

According to a report by the World Bank, global annual waste production is expected to rise to more by more than 70 percent to 3.4 billion metric tons. The consequences are alarming, ranging from devastating amounts of environmental pollution, climate change, health hazards and the like.

Fortunately, rapid advancements in technology have brought forth new ways to manage and reprocess artificial waste. Techniques in Machine Learning and Computer Vision are now being implemented in new waste management technologies. 

This article dives deep into this groundbreaking waste reprocessing tech and takes a look at the innovative start-ups implementing them for the sake of our future.

The Necessity of Reusing And Recycling

Hazardous wastes, biodegradable & non-biodegradable wastes, e-wastes, agricultural runoffs, urban & rural wastes– different kinds of waste products affect the environment &, subsequently, the human society differently. 

  • A US Government Environmental Protection Agency article puts forth some alarming figures about the man-made waste generation scenarios in the country.  The United States remains the leading waste producer globally, followed by numerous high-income nations such as Australia, Canada, France, Germany, etc.
  • Waste reusing & recycling is one of the most effective and economical waste management methods in practice that ensures reduction and utilization of waste products.  
  • Existing waste recycling & waste controlling measures struggle to cope with humongous amounts of waste produced each year. 

With an exponential increase in the waste generation estimated in the following years, systems will be near their breaking points. Moreover, environmental damage due to improper management is already a verifiable reality, as evident from climate change, loss of ecosystems and endangerment &extinction of different plant & animal species each year.

The situation is much worse in countries across Africa, South America, South and South-East Asia.

Effective waste management is the need of the hour, supported by the latest innovative technologies that supplement existing endeavors. Technology companies, including many start-ups, are adopting AI and machine vision to tackle wastage problems. 

Let’s take a closer look at these new processes.

AI Waste Management Using Machine Vision

The fundamentals of recycling involve collecting, sorting, manual or automatic processing and delivering recycled materials to their appropriate destination.

Manual sorting and processing are highly inefficient and unfeasible on a larger scale, and hazardous for the people involved. 

Machine learning enhanced computer vision, coupled with robotic process automation, are some rising techs that can boost the capabilities of recycling plants.

  • Machine Learning is a branch of artificial intelligence that uses predictive data analytics to train and automate machine operations. ML is revolutionizing different industries and is augmenting existing techs like image processing & computer vision to a massive extent.

Innovators, experts, and policymakers are realizing and taking initiatives to adopt these groundbreaking techs into existing waste management strategies. For example, the Global Waste Management Conference in Malaysia gathered some of the best minds across industries to discuss the implementation of Fourth Industrial Revolution technologies such as Big Data, AI, Automation and the Internet of Things for intelligent waste management. 

  • Machine vision is machine learning-powered computer vision that allows computers to process, identify, classify, categorize, segregate and separate objects from a collection or a pile. 

Computer and machine vision are being now implemented to see and classify different kinds of human waste. AI and computer vision can sort, audit and recover waste for recycling. From smart waste bins to automated recycling plants, there is massive scope for Smart Recycling in the waste processing industry.

Research paper writers in AI cite advanced methods such as Multilayer-Hybrid Deep Learning Method for Waste Classification and Recycling and Artificial Neural Networks as effective ways to discern & sort different waste products.

AI-Assisted Waste Recycling and Waste Management

  • Machine vision is used in various plastic recycling facilities to improve recycling efficiency and achieve greater profitability. For example, many private and even public facilities employ hyperspectral and multispectral vision systems to categorize black-coloured plastics. 

The speed and accuracy of AI-enhanced vision systems are increasing by leaps and bounds. As a result, greater quality and efficiency is now possible in the plastic recycling industry due to these up and coming technologies. 

AI-Assisted Machine Vision For Identification And Segregation

  • Robotic recycling systems employ AI vision systems and computer systems to guide robotic arms over conveyor belts and pick & place objects. These technologies are now assisting humans in identifying and sorting objects of different colors, shapes, sizes, textures, etc. In addition, they are faster and, with proper training, can become more efficient than human beings. 
  • Certain limitations to AI-assisted innovative recycling do exist, however. Chief amongst them are: 
  1. The necessity of Human Supervision:  Waste product piles and heaps are complex environments. AI models in machine vision systems require proper training to identify and sot various waste materials. 
  • Maintenance of Databases: Segmented databases of labeled images of waste products must be maintained for effective operations.
  • Data Processing and Power Requirements:  Powerful processing units are necessary for the high computing requirements of Deep Learning and ML vision systems. Simultaneously, reliable and constant power sources are a must.
  • Supply and Demand: AI waste management systems do not come cheap, and the profit-making aspect of robotic recycling & processing is another cause of concern. 

Despite the limitations involved, governments, tech companies, and numerous entrepreneurship have begun implementing smart recycling and AI waste management technologies. 

Recent Initiatives 

Here are some major businesses that are using AI waste management to make the world a better place.

 The company is using AI and RPA to improve recycling quality and efficiency.

This Indian start-up is using robotics, computer vision and IoT to tackle India’s waste generation problems. 

An AI tech company from Spain, Sadako Technologies, has manufactured robotic waste sorter and flow monitoring systems for effective management & further processing.

And that rounds up this article on new technologies that are trying to solve an age-old waste problem. 

The onus falls upon our society, too, to produce less waste and live in an environmentally sustainable manner. REDUCE-REUSE-RECYCLE- we must remember these three Rs if we want to ensure the continued survival of our future generations.

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