We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
Design and Fabrication of Material Separation Machine for Sustainable Development
Summary
This paper is not relevant to microplastics research — it describes the design and fabrication of a robotic material separation machine intended to sort recyclable waste more efficiently using AI-inspired engineering principles.
In this research article, design and fabrication of material separation machine is discussed with the objective to decrease the time, money, and labor required to separate waste materials from one location to another, the design and manufacture of material separation machines are explored in this study. The fundamental concept was inspired by the development and application of artificial intelligence as well as the motion of robotic arms. The Material Separation machine's design places an emphasis on separating recyclable and usable waste from the accessible trash while using less energy and scientific approaches to separate the valuable material. The device is helpful for the efficient use of time and human labor, as well as for areas where a lack of manpower is a concern. Compared to other existing Material Separation machines, our machine utilizes cheap, readily available materials in the best way possible to produce an effective outcome in a predetermined amount of time.
Sign in to start a discussion.
More Papers Like This
A Machine Arm to Assist in Trash Sorting using machine Learning and Object Detection
Not relevant to microplastics — this paper describes a robotic arm system that uses machine learning and computer vision to sort recyclable waste materials, focused on automation of waste sorting processes.
Application of AI-Enabled Computer Vision Technology for Segregation of Industrial Plastic Wastes
Researchers developed an AI-powered computer vision system to segregate mixed industrial plastic wastes by polymer type, addressing a key barrier to effective plastic recycling. The system achieved high classification accuracy across common plastic categories, demonstrating that machine vision can improve sorting efficiency and recycled plastic quality.
Design and Development of Smart Beach Debris Collection and Segregation System
Researchers designed and built a smart automated system for collecting and segregating beach debris, using sensors and robotics to identify and sort plastic waste from natural material on shorelines. The system demonstrated effective separation of plastic debris in field tests.
Artificial Intelligence-Based Robotic Technique for Reusable Waste Materials
This paper describes an AI-based robotic arm system that uses a customized deep learning model to classify and sort waste materials including plastics and cartons by material type for automated recycling. The integrated system combines gripping, motion control, and AI-driven material classification into a full-automation architecture for waste recovery.
Enhancing Waste Management with a Deep Learning-based Automatic Garbage Classifier
This paper is not about microplastics; it presents a deep learning convolutional neural network system for automatically classifying garbage by material type to improve waste sorting efficiency and reduce the labor burden of manual waste management.