14th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services

Research Article

A Mobile Crowdsensing Framework for Integrating Smartphone and IoT Devices to Cloud Computing Services

  • @INPROCEEDINGS{10.4108/eai.7-11-2017.2274134,
        author={Waskitho Wibisono and M Divi Nuryanto and Royyana Ijtihadie and Tohari Ahmad and Radityo Anggoro},
        title={A Mobile Crowdsensing Framework for Integrating Smartphone and IoT Devices to Cloud Computing Services },
        proceedings={14th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services},
        publisher={ACM},
        proceedings_a={MOBIQUITOUS},
        year={2018},
        month={4},
        keywords={mobile crowdsensing cloud computing},
        doi={10.4108/eai.7-11-2017.2274134}
    }
    
  • Waskitho Wibisono
    M Divi Nuryanto
    Royyana Ijtihadie
    Tohari Ahmad
    Radityo Anggoro
    Year: 2018
    A Mobile Crowdsensing Framework for Integrating Smartphone and IoT Devices to Cloud Computing Services
    MOBIQUITOUS
    ACM
    DOI: 10.4108/eai.7-11-2017.2274134
Waskitho Wibisono1,*, M Divi Nuryanto2, Royyana Ijtihadie2, Tohari Ahmad2, Radityo Anggoro2
  • 1: Department of Informatics, Institut Teknologi Sepuluh Nopember, Indonesia
  • 2: Department of Informatics Institut Teknologi Sepuluh Nopember, Indonesia
*Contact email: waswib@if.its.ac.id

Abstract

The proliferations of mobile crowdsensing (MCS) services using smartphones with various embedded sensors have enabled people to involve in public sensing activities for various applications. Nevertheless for more complex applications such as smart cities, traffic monitoring, disaster prevention more variety of sensors are required. Hence combination of smartphone and Internet of Things (IoT) devices to form crowdsensing cluster will give great advantages. This paper proposes design and implementation of mobile crowdsensing framework to support integration of smartphones and IoT devices as a mobile crowdsensing cluster. The prototype of the proposed framework has been successfully implemented and tested using real devices and infrastructure with promising results.