Framework to monitor pregnant women with a high risk of premature labour using sensor networks

Hisham Allahem; Srinivas Sampalli

doi:10.23919/INM.2017.7987458

Framework to monitor pregnant women with a high risk of premature labour using sensor networks

Hisham Allahem, Srinivas Sampalli

Physics and Astronomy

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

12 Citations (Scopus)

Original language	English
Title of host publication	Proceedings of the IM 2017 - 2017 IFIP/IEEE International Symposium on Integrated Network and Service Management
Editors	Prosper Chemouil, Paulo Simoes, Edmundo Madeira, Stefano Secci, Edmundo Monteiro, Luciano Paschoal Gaspary, Carlos Raniery P. dos Santos, Marinos Charalambides
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1178-1181
Number of pages	4
ISBN (Electronic)	9783901882890
DOIs	https://doi.org/10.23919/INM.2017.7987458
Publication status	Published - Jul 20 2017
Event	15th IFIP/IEEE International Symposium on Integrated Network and Service Management, IM 2017 - Lisbon, Portugal Duration: May 8 2017 → May 12 2017

Publication series

Name	Proceedings of the IM 2017 - 2017 IFIP/IEEE International Symposium on Integrated Network and Service Management

Conference

Conference	15th IFIP/IEEE International Symposium on Integrated Network and Service Management, IM 2017
Country/Territory	Portugal
City	Lisbon
Period	5/8/17 → 5/12/17

ASJC Scopus Subject Areas

Computer Networks and Communications
Hardware and Architecture
Information Systems and Management

Access to Document

10.23919/INM.2017.7987458

Cite this

Allahem, H., & Sampalli, S. (2017). Framework to monitor pregnant women with a high risk of premature labour using sensor networks. In P. Chemouil, P. Simoes, E. Madeira, S. Secci, E. Monteiro, L. P. Gaspary, C. R. P. dos Santos, & M. Charalambides (Eds.), Proceedings of the IM 2017 - 2017 IFIP/IEEE International Symposium on Integrated Network and Service Management (pp. 1178-1181). Article 7987458 (Proceedings of the IM 2017 - 2017 IFIP/IEEE International Symposium on Integrated Network and Service Management). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/INM.2017.7987458

Framework to monitor pregnant women with a high risk of premature labour using sensor networks. / Allahem, Hisham; Sampalli, Srinivas.
Proceedings of the IM 2017 - 2017 IFIP/IEEE International Symposium on Integrated Network and Service Management. ed. / Prosper Chemouil; Paulo Simoes; Edmundo Madeira; Stefano Secci; Edmundo Monteiro; Luciano Paschoal Gaspary; Carlos Raniery P. dos Santos; Marinos Charalambides. Institute of Electrical and Electronics Engineers Inc., 2017. p. 1178-1181 7987458 (Proceedings of the IM 2017 - 2017 IFIP/IEEE International Symposium on Integrated Network and Service Management).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Allahem, H & Sampalli, S 2017, Framework to monitor pregnant women with a high risk of premature labour using sensor networks. in P Chemouil, P Simoes, E Madeira, S Secci, E Monteiro, LP Gaspary, CRP dos Santos & M Charalambides (eds), Proceedings of the IM 2017 - 2017 IFIP/IEEE International Symposium on Integrated Network and Service Management., 7987458, Proceedings of the IM 2017 - 2017 IFIP/IEEE International Symposium on Integrated Network and Service Management, Institute of Electrical and Electronics Engineers Inc., pp. 1178-1181, 15th IFIP/IEEE International Symposium on Integrated Network and Service Management, IM 2017, Lisbon, Portugal, 5/8/17. https://doi.org/10.23919/INM.2017.7987458

Allahem H, Sampalli S. Framework to monitor pregnant women with a high risk of premature labour using sensor networks. In Chemouil P, Simoes P, Madeira E, Secci S, Monteiro E, Gaspary LP, dos Santos CRP, Charalambides M, editors, Proceedings of the IM 2017 - 2017 IFIP/IEEE International Symposium on Integrated Network and Service Management. Institute of Electrical and Electronics Engineers Inc. 2017. p. 1178-1181. 7987458. (Proceedings of the IM 2017 - 2017 IFIP/IEEE International Symposium on Integrated Network and Service Management). doi: 10.23919/INM.2017.7987458

Allahem, Hisham ; Sampalli, Srinivas. / Framework to monitor pregnant women with a high risk of premature labour using sensor networks. Proceedings of the IM 2017 - 2017 IFIP/IEEE International Symposium on Integrated Network and Service Management. editor / Prosper Chemouil ; Paulo Simoes ; Edmundo Madeira ; Stefano Secci ; Edmundo Monteiro ; Luciano Paschoal Gaspary ; Carlos Raniery P. dos Santos ; Marinos Charalambides. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 1178-1181 (Proceedings of the IM 2017 - 2017 IFIP/IEEE International Symposium on Integrated Network and Service Management).

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Framework to monitor pregnant women with a high risk of premature labour using sensor networks

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