University of Kentucky Introduces AI-Enabled Waste Sorting Recycling Technology

17 Apr 2023


On March 20th, 2023, the University of Kentucky (UK) announced the integration of AI-enabled recycling innovation in their campuses.

The AI-enabled recycling system, the Oscar Sort, provides real-time feedback to users on the recyclability of items.

Artificial intelligence (AI) is a rapidly developing technology and has been increasingly applied across a wide range of industries, including waste management and recycling. 

With the help of AI-enabled recycling systems such as Oscar Sort, waste management companies can now automate various processes involved in waste collection, sorting, and recycling, leading to improved efficiency and accuracy.

Read the complete story to know about the functionality and significance of this innovative AI-enabled waste sorting technology.

Oscar Sort: Transforming Campus Recycling with AI

Oscar Sort is an AI-powered smart recycling assistant installed across various university campuses, which was developed by a Canadian startup, Intuitive AI.

This new AI-enabled technology is the latest step in the University of Kentucky’s drive toward being a zero-waste campus.

Oscar Sort has been designed to improve the recycling process by reducing contamination and ensuring that items are sorted and disposed of correctly.

By utilizing advanced computer vision and machine learning algorithms, Oscar Sort can accurately identify the materials in an item and determine whether it should be recycled, partially recycled, or disposed of. 

For instance, Oscar Sort can identify a cup in a student’s hand and inform the student that the cup can be recycled; however, the straw must be thrown in the trash.
Furthermore, it can also identify liquid residues in bottles, organic waste within food boxes, and separate coffee cup lids and sleeves.

Hassan Murad, CEO, and co-founder of Intuitive AI, said, “Oscar knows hundreds of classes of waste items, and each class has 15-20 subclasses. Like a new employee, Oscar Sort [they] has a good foundation but need to learn the ins and outs of the new environment.”

He further added,” The more waste Oscar sees across the University of Kentucky, the faster and better accuracy will become over time."

Oscar Sort integrates centralized zero-touch zero-waste stations, making it an ideal solution for public spaces like campuses, parks, and shopping centers.

Moreover, AI-enabled waste sorting systems, such as Oscar, include interactive displays, games, and challenges that reward people for recycling or reducing their waste. 

This not only makes recycling more fun and engaging, but it also helps to boost diversion rates, which is the percentage of waste that is diverted from the landfill and recycled.

The underlying principle of Oscar Sort is based on a powerful behavioral change concept known as a "Nudge." This concept is incorporated throughout the user interface, referred to as the Oscar Experience.

When a user approaches the Oscar Sort system, the Oscar discovery mode welcomes them and provides instructions on how to sort waste in a simple, intuitive, and visually appealing way. The system can also incentivize users by rewarding them for correct sorting practices or reprimanding them for incorrect ones.

Advanced recycling technologies such as Oscar sort can help reduce contamination in the recycling process, leading to higher-quality recycled materials, which leads to an increase in recycling rates, reduced labor costs, and improved efficiency.

Moreover, Oscar Sort conducts automated waste auditing by analyzing waste patterns and trends. It offers a range of features, including pickup optimization, environmental, social, and governance (ESG) reporting, and operational benefits.

Ryan Lark, a recycling, and waste reduction specialist senior at UK, said,” Our goal as a university is to be a zero-waste campus by 2030.”

According to Lark, this entails diverting 90% of all waste generated on campus to various avenues such as recycling, composting, and organic waste through different channels instead of sending it to landfills. 

He believes that people's inadequate recycling behavior can be attributed to two factors, namely, the absence of convenience and inadequate education. However, Oscar technology will address both issues by providing immediate feedback.

Lark further explained that "By offering instant feedback and informing individuals that they can recycle a certain item on the spot without wasting 20 minutes trying to figure it out, the likelihood of people recycling will significantly increase."

Moreover, a case study conducted on Merck San Francisco revealed that Intuitive AI's Oscar technology contributed to a 65% increase in diversion rate, which was sustained through data-driven insights gained via waste analytics. The University of Kentucky is optimistic about achieving similar outcomes.

With such success rates, other advanced recycling technologies are set to embrace AI and machine learning in their processes, which is expected to drive growth in the market.

According to data insights from BIS Research, the global advanced recycling technologies market is projected to reach $9,339.7 million by 2031 from $270.5 million in 2022, growing at a CAGR of 48.22% during the forecast period 2022-2031.


Conclusion

AI-based recycling technology has the potential to provide real-time feedback and data analysis to enhance waste reduction and recycling efforts. 

With the rapid advancement of technology, AI-powered recycling systems such as Oscar Sort will likely become more sophisticated and prevalent. 

This will help businesses and organizations to identify opportunities for improvement, streamline operations, and reduce waste generation. 

Moreover, it could help to improve the quality of recycled materials and reduce contamination, making them more valuable in the recycling market.

Interested to know more about the advancing technologies in your industry vertical? Get the latest market studies and insights from BIS Research. Connect with us at [email protected] to learn and understand more.

 
 
 
 

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