Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Khan, Fazal; Priya, Sharon Roji C.; Burhanuddin, Ibrahim; Kurian, Joshua P.K. Title A name given to the resource Automated Waste Segregation using Raspberry Pi and Deep Learning Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived 16th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2025;Volume;2;pp.8620-8625 Identifier An unambiguous reference to the resource within a given context <a href="https://www.scopus.com/pages/publications/105034833401?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105034833401?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Khan F., Department of Computer Science and Engineering, Christ University, Bangalore, India; Priya S.R.C., Department of Computer Science and Engineering, Christ University, Bangalore, India; Burhanuddin I., Department of Computer Science and Engineering, Christ University, Bangalore, India; Kurian J.P.K., Department of Computer Science and Engineering, Christ University, Bangalore, India Description An account of the resource With rapid urbanization and increasing waste generation, efficient waste segregation has become a critical challenge for sustainable waste management. Traditional waste disposal methods rely heavily on manual sorting, which is inefficient, labor-intensive, and prone to errors, leading to improper recycling and environmental hazards. To address these problems, a clever waste segregation method is presented in this research. It automatically sorts waste into four categoriesglass, metal, plastic, and paper/cardboardusing computer vision and machine learning. A 720p webcam is used to collect images in real time, and the system is powered by a Raspberry Pi 4B with 4GB of RAM. A Convolutional Neural Network (CNN) model that was developed using the TrashNet dataset forms its basis. The model can correctly identify the waste in the photos due to an optimized training method that incorporates data augmentation, regularization strategies, and early stopping to prevent overfitting. An SG90 servo motor controls the lid, ensuring the garbage is placed in the appropriate compartment, while an MG996R servo motor swings the bin into place after the waste has been classified. The bin and lid go back to their initial places once the garbage has been dumped, preparing the system for usage again. Here, we are able to combine automated mobility, automated categorization, and real-time waste detection with embedded technologies, machine learning, and automation to separate waste with the least amount of human intervention. Furthermore, the system's scalability and adaptability make it appropriate for smart city initiatives, urban trash management, and wider industrial application. Consequently, this technology helps to tackle intelligent waste management problems, which facilitates the emergence of a sustainable and eco-friendly future. The system achieved a testing accuracy of 88.1%, showcasing its effectiveness and reliability. Grenze Scientific Society, 2025. Subject The topic of the resource automation; computer vision; Convolutional Neural Network (CNN); environmental sustainability; machine learning; Real-time waste detection; smart waste management; TrashNet dataset; Waste segregation Publisher An entity responsible for making the resource available Grenze Scientific Society Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online