Access to timely and accurate waste volume and composition data has long been the
recycling and waste management sector’s Achilles heel. Traditional composition analysis
methods, such as manual sampling and visual inspection, are often unreliable,
time-consuming, and cannot provide representative data.
As a result, these methods are struggling to keep up with compliance reporting that
requires accurate and up-to-date data, and more of it. Operationally, real-time process
adjustments require data that can be gathered quickly and easily to spot contamination in
product outputs and increase recovery.
Artificial Intelligence (AI) and computer vision systems have emerged in recent years and
are now being deployed within the recycling and waste management sector to address
these data challenges and drive process improvement.
Our expert panel will discuss the importance of waste data within an emerging regulatory
context and will share real world examples of the results of AI applications to scale
composition analysis.