Monitoring nyiragongo volcano using a federated cloud-based wireless sensor network
Cloud computing; Sensor-clouds; Volcano monitoring; Wireless sensor network
Current Nyiragongo Volcano observatory systems yield poor monitoring quality due to unpredictable dynamics of volcanic activities and limited sensing capability of existing sensors (seismometers, acoustic microphones, GPS, tilt-meter, optical thermal, and gas flux). The sensor node has limited processing capacity and memory. So if some tasks from the sensor nodes can be uploaded to the server of cloud computing then the battery life of the sensor nodes can be extended. The cloud computing can be used both for processing of aggregate query and storage of data. The two principal merits of this paper are the clear demonstration that the Cloud Computing model is a good fit with the dynamic computational requirements of Nyiragongo volcano monitoring and the novel optimization algorithm for seismic data routing. The proposed new model has been evaluated using Arduino-Atmega328 as hardware platform, Eucalyptus/Open Stack with Orchestra-Juju for Private Sensor Cloud connected to some famous public clouds such as Amazon EC2, ThingSpeak, SensorCloud and Pachube. 2017 IEEE.
Proceedings - 2017 4th International Conference on Information Science and Control Engineering, ICISCE 2017, pp. 1545-1550.
Institute of Electrical and Electronics Engineers Inc.
https://doi.org/10.1109/ICISCE.2017.322 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85040541541&doi=10.1109%2fICISCE.2017.322&partnerID=40&md5=936588446f8aebf2fd8180909f649fd8
Rutakemwa M.M., Embedded Systems: Computer Engineering, Christ University Bangalore, Bangalore, Karnataka, India; Iven J., Electronics and Communications, Christ University Bangalore, Bangalore, Karnataka, India; Georges T.M., Goma Volcano Observatory, China