Logo do repositório
 
Publicação

Multi-sensor pattern recognition and real-time data processing for autonomous smart waste management

2025Comunicação em conferência Acesso aberto
Ver registo simples
datacite.subject.fosEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
dc.contributor.authorJvarsheishvili, Mariam
dc.contributor.authorIbrahim, Ahmad
dc.contributor.authorAhmadi, Mahdia
dc.contributor.authorIgrejas, Getúlio
dc.contributor.authorSoares, Caio
dc.contributor.authorIzidorio, Felipe
dc.contributor.authorLopes, Rui Pedro
dc.contributor.authorRodrigues, Pedro João
dc.date.accessioned2026-03-25T12:33:39Z
dc.date.available2026-03-25T12:33:39Z
dc.date.issued2025
dc.description.abstractUrban waste management systems require intelligent monitoring solutions that can process multi-modal sensor data in real-time while operating autonomously. This paper presents RAICYCLE, a comprehensive smart waste management system that integrates advanced pattern recognition techniques with real-time operating systems for autonomous urban deployment. The system employs eight BME688 environmental sensors with distinct heater profiles (50°C to 350°C) for volatile organic compound (VOC) pattern classification, combined with VL53L0X Time-of-Flight sensors and GPS tracking. The embedded architecture utilizes FreeRTOS dual-core task scheduling on ESP32 microcontrollers, enabling concurrent sensor data processing, LoRaWAN communication, and system monitoring. Data serialization through Protocol Buffers achieves 70% payload reduction compared to JSON formats, while kinetic energy harvesting from container lid movements enables autonomous operation. The system demonstrates effective real-time processing of 32 dimensional feature vectors for waste classification and environmental monitoring in urban deployments.eng
dc.identifier.citationJvarsheishvili, Mariam; Ibrahim, Ahmad; Ahmadi, Mahdia; Igrejas, Getúlio; Soares, Caio; Izidorio, Felipe; Lopes, Rui Pedro; Rodrigues, Pedro João (2025). Multi-sensor pattern recognition and real-time data processing for autonomous smart waste management. In RECPAD 2025 - 31st Portuguese Conference on Pattern Recognition. Aveiro, Portugal
dc.identifier.urihttp://hdl.handle.net/10198/36270
dc.language.isoeng
dc.peerreviewedyes
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.titleMulti-sensor pattern recognition and real-time data processing for autonomous smart waste managementpor
dc.typeconference paper
dspace.entity.typePublication
oaire.citation.conferencePlaceAveiro, Portugal
oaire.citation.titleRECPAD 2025 - 31st Portuguese Conference on Pattern Recognition
oaire.versionhttp://purl.org/coar/version/c_ab4af688f83e57aa
person.familyNameIgrejas
person.familyNameLopes
person.familyNameRodrigues
person.givenNameGetúlio
person.givenNameRui Pedro
person.givenNamePedro João
person.identifier.ciencia-id8E14-54E4-4DB5
person.identifier.ciencia-id1316-21BB-9015
person.identifier.orcid0000-0002-6820-8858
person.identifier.orcid0000-0002-9170-5078
person.identifier.orcid0000-0002-0555-2029
person.identifier.ridM-8571-2013
person.identifier.scopus-author-id47761255900
relation.isAuthorOfPublicationab4092ec-d1b1-4fe0-b65a-efba1310fd5a
relation.isAuthorOfPublicatione1e64423-0ec8-46ee-be96-33205c7c98a9
relation.isAuthorOfPublication6c5911a6-b62b-4876-9def-60096b52383a
relation.isAuthorOfPublication.latestForDiscoveryab4092ec-d1b1-4fe0-b65a-efba1310fd5a

Ficheiros

Principais
A mostrar 1 - 1 de 1
Miniatura
Nome:
Multi_Sensor_Pattern_Recognition_and_Real_Time_Data_Processing_for_Autonomous_Smart_Waste_Man.pdf
Tamanho:
90.32 KB
Formato:
Adobe Portable Document Format
Ver/Abrir
Licença
A mostrar 1 - 1 de 1
Miniatura indisponível
Nome:
license.txt
Tamanho:
1.75 KB
Formato:
Item-specific license agreed upon to submission
Descrição:
Ver/Abrir

Coleções

ESTiG - Artigos em Proceedings Não Indexados à WoS/Scopus