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MAESTRO – sMArt rEcycle bin uSing auTomatic gaRbage recOgnition

MAESTRO – sMArt rEcycle bin uSing auTomatic gaRbage recOgnition

MAESTRO is a garbage collector able to distinguish different types of garbage. It is composed of a multisensory system for recognizing the waste and a manipulator with two degrees of freedom for sorting in recycling bins. The user deposits the object to be trashed in a special drawer. The system, by exploiting artificial intelligence, decides the proper recyling path.
The MAESTRO trash-bin is able to memorize the different materials used by the owner in order to promote virtuous behavior in the disposal of waste through smart billing.
Italy


MAESTRO – sMArt rEcycle bin uSing auTomatic gaRbage recOgnition

Il progetto è stato realizzato nel corso di Cyber-Physical Systems, gli autori sono: Federica Pascucci, Sara Acquaviva, Elena Bernardini, Matteo Castellani, Gianmarco Frangini, Filippo Magri, Giulia Perri, Jie Tan.

Federica Pascucci received the M.S. degree in computer science and automation engineering from the University of Roma Tre in 2000 and the Ph.D. degree in system engineering from the University of Rome La Sapienza in 2004. Since 2005, she has been an Assistant Professor with the Department of Engineering, University of Roma Tre. Her current research interests include wireless sensor networks, indoor localization, cyber-physical systems, industrial control systems, and critical infrastructure protection. As professor of the course on Cyber Physical Systems, she coordinates the MAESTRO project.

Sara Acquaviva received the BD degree in computer engineering from the University of Roma Tre in 2016 and she is currently student of the MS in Management and Automation at the University of Roma Tre. She defined the functional requirements and designed the information system for the MAESTRO project.

Elena Bernardini received the BD degree in Computer Engineering from the University of Roma Tre in 2017 and she is currently student of the MS in Management and Automation at the University of Roma Tre. She designed the physical structure of the bin and interfaces sensors and actuators to Arduino for the MAESTRO project.

Matteo Castellani received the BD degree in Computer Engineering from the University of Roma Tre in 2016 and he is currently student of the MS in Management and Automation at the University of Roma Tre. He designed and developed the Arduino software for the MAESTRO project.

Gianmarco Frangini received the BD degree in computer engineering from the University of Roma Tre in 2016 and he is currently student of the MS in Computer Engineering at the University of Roma Tre. He designed and developed computer vision algorithms based on Machine Learning for the MAESTRO project.

Filippo Magri received the BD degree in computer engineering from the University of Roma Tre in 2016 and he is currently student of the MS in Management and Automation at the University of Roma Tre. He designed the system to identify different material and the control algorithms for the actuators for the MAESTRO project.

Giulia Perri received the BD degree in computer engineering from the University of Roma Tre in 2017 and she is currently student of the MS in Management and Automation at the University of Roma Tre. She designed the physical structure of the bin and interfaces sensors and actuators to Arduino for the MAESTRO project.

Jie Tan is currently student of the MS in Management and Automation at the University of Roma Tre. She defined the functional requirements for the MAESTRO project.


Stand D34 (pav. 7) - Università degli Studi Roma Tre


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Data updated on 2019-10-20 - 5.32.19 pm