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Identificação

Identificação pessoal

Nome completo
Emanuel Ribeiro Lima

Nomes de citação

  • Lima, Emanuel

Identificadores de autor

Ciência ID
DA13-576A-BB7C
ORCID iD
0000-0002-8134-3915
Formação
Grau Classificação
2015/10/01 - 2024/06/20
Concluído
 MAP-Tele (Doutoramento)
Especialização em Engenharia das Telecomunicações
Universidade do Porto Faculdade de Engenharia, Portugal
2014/12/19
Concluído
 Redes e Serviços de Comunicações (Mestrado)
Especialização em Não Aplicável
Universidade do Minho, Portugal
Percurso profissional

Docência no Ensino Superior

Categoria Profissional
Instituição de acolhimento 		Empregador
2018 - 2023 Assistente Convidado (Docente Universitário) Universidade do Minho, Portugal
Produções

Publicações

Artigo em revista
  1. Lima, Emanuel Ribeiro; Aguiar, Ana; Carvalho, Paulo; Viana, Aline Carneiro. "Human mobility support for personalized data offloading". (2022): https://hdl.handle.net/1822/89945.
    10.1109/tnsm.2022.3153804
  2. Rodrigues, Daniel; Carvalho, Paulo; Rito Lima, Solange; Lima, Emanuel; Lopes, Nuno Vasco. "An IoT platform for production monitoring in the aerospace manufacturing industry". (2022): https://hdl.handle.net/1822/89943.
    10.1016/j.jclepro.2022.133264
Tese / Dissertação
  1. Abdah, Hadeel Mohamad-Ali. "Selective reprogramming of WSNs: energetic study and functionality optimization". Mestrado, 2016. http://hdl.handle.net/1822/47320.
  2. Lima, Emanuel Ribeiro. "Uma extensão protocolar para a reprogramação seletiva de RSSFs". Mestrado, 2014. http://hdl.handle.net/1822/37275.

Outros

Outra produção
  1. Monitoring IoT platform for the aerospace manufacturing industry. The maturation of IoT and CPS technologies has attracted the attention of many governments and companies worldwide due to their potential to optimize industrial processes in multiple ways. In this context, enhancing monitoring and controlling of production lines is of particular interest as a fundamental step towards smart manufacturing and product delivery. This work is focused on developing a so. 2021. Rodrigues, Daniel Souto; Carvalho, Paulo; Rito Lima, Solange; Lima, Emanuel Ribeiro; Lopes, Nuno Vasco. https://hdl.handle.net/1822/89947.
    10.23919/SpliTech52315.2021.9566453
  2. Impacts of human mobility in mobile data offloading. Due to the limited coverage of WiFi APs, users’ mobility has a severe impact on the performance of mobile offloading systems. The present study is a contribution in this context as offloading zones are identified and characterized from individual GPS trajectories when small offloading time windows are considered. The results show that (i) attending to users mobility, ten seconds is the minimum off. 2018. Lima, Emanuel Ribeiro; Aguiar, Ana Cristina Costa; Carvalho, Paulo; Viana, Aline Carneiro. http://hdl.handle.net/1822/71556.
    10.1145/3264844.3264849
  3. Offloading surrogates characterization via mobile crowdsensing. This paper uses data mining of a mobile crowdsensed dataset of passive WiFi scans to define attributes that can characterize a chaotic WiFi deployment with respect to offloading opportunities. Besides indicators of signal quality, we define indicators of contact windows and contact opportunities with an Access Point (AP). We apply k-means clustering to identify classes of APs, and observe that int. 2017. Lima, Emanuel; Aguiar, Ana; Carvalho, Paulo. http://hdl.handle.net/1822/52706.
    10.1145/3139243.3139253
  4. Improving energy-awareness in selective reprogramming of WSNs. Saving energy is considered one of the main challenges in wireless sensor networks (WSNs), being radio activities such as message transmission/reception and idle listening the main factors of energy consumption in the nodes. These activities increase with the increase of reliability level required, which is usually achieved through flooding strategies. Procedures such as remote WSNs reprogramming. 2016. Abdah, Hadeel Mohamad-Ali; Lima, Emanuel; Carvalho, Paulo. http://hdl.handle.net/1822/52707.
    10.1007/978-3-319-46301-8_20
  5. A protocol extension for selective reprogramming of WSNs. Wireless sensor networks (WSNs) are expected to operate for long time periods, often in places of difficult access. Thus, the ability to reprogram remotely and selectively sensor nodes becomes crucial in the maintenance and management of these networks. From the operating systems mostly used in WSNs, only TinyOS supports natively a reprogramming protocol (Deluge). The epidemic nature of Deluge, wi. 2015. Lima, Emanuel; Carvalho, Paulo; Gama, Óscar Sílvio Marques Almeida. http://hdl.handle.net/1822/52710.
    10.1109/SOFTCOM.2015.7314064