Wireless Sensor Network to Help Low Incomes Farmers to Face Drought Impacts
This research presents the main ideas to implement an
intelligent system composed by communicating wireless sensors
measuring environmental data linked to drought indicators (such as
air temperature, soil moisture , etc...). On the other hand, the setting
up of a spatio temporal database communicating with a Web mapping
application for a monitoring in real time in activity 24:00 /day, 7
days/week is proposed to allow the screening of the drought
parameters time evolution and their extraction. Thus this system
helps detecting surfaces touched by the phenomenon of drought.
Spatio-temporal conceptual models seek to answer the users who
need to manage soil water content for irrigating or fertilizing or other
activities pursuing crop yield augmentation. Effectively, spatiotemporal
conceptual models enable users to obtain a diagram of
readable and easy data to apprehend. Based on socio-economic
information, it helps identifying people impacted by the phenomena
with the corresponding severity especially that this information is
accessible by farmers and stakeholders themselves. The study will be
applied in Siliana watershed Northern Tunisia.
[1] Rengers, N., Soeters, R. and Westen, C.J. Van (1992) Remote sensing
and GIS applied to mountain hazard mapping. Episodes, Vol.15, No.1,
March 1992, pp.36-45.
[2] Johnston C. A, Groffman P, Breshears DD, et al. 2004. Carbon Cycling
in Soil. Front Ecol Environ 2: 522–28.
[3] Díaz S. E., Pérez J. C., Mateos A. C., Marinescu M.C., B. B., Guerra,
2011. A Novel Methodology for the Monitoring of the Agricultural
Production Process Based on Wireless Sensor Networks. Computers and
Electronics in Agriculture, vol. 76, no. 2, pages 252–265, 2011.
[4] Garcia-Sanchez A. J., Garcia-Sanchez F., J. Garcia-Haro, 2011. Wireless
Sensor Network Deployment for Integrating Video Surveillance and
Data-Monitoring in Precision Agriculture over Distributed Crops.
Computers and Electronics in Agriculture, vol. 75, no. 2, pages 288 –
303, 2011.
[5] López Riquelme J.A., F. Soto, J. Suardíaz, P. Sánchez, A. Iborra and
J.A. Vera, 2009. Wireless Sensor Networks for Precision Horticulture in
Southern Spain. Computers and Electronics in Agriculture, vol. 68, no.
1, pages 25 – 35, 2009.
[6] Wark T., P. Corke, P. Sikka, L. Klingbeil, Ying Guo, C. Crossman, P.
Valencia, D. Swain and G. Bishop-Hurley, 2007. Transforming
Agriculture through Pervasive Wireless Sensor Networks. Pervasive
Computing, IEEE, vol. 6, no. 2, pages 50–57, 2007.
[7] Eagleson, P.S. (1994) the Evolution of Modern Hydrology (from
Watershed to Continent in 30 years), Advances in Water Resources 17
(1994), 3-18.
[8] Parent C., Spaccapietra S., Zimányi E., Donni P., Plazanet C., Vangenot
C., Rognon N., Rausaz P. MADS, Modèle Conceptuel Spatio-Temporel.
Revue Internationale de Géomatique, 1997, Vol. 7, n°3-4, pp. 317-351.
[9] Bédard Y., 1999. Visual Modelling of Spatial Databases: Towards
Spatial PVL and UML, Géomatica, 53(2), pp.169-186.
[10] Spaccapietra S., Parent C., Zimányi E., 1998. Modeling Time from a
Conceptual Perspective, In: Int. Conf. on Information and Knowledge
Management (CIKM 1998).
[11] Parent C., Spaccapietra S., Zimányi E., 1999. Spatio-Temporal
Conceptual Models: Data Structures + Space + Time, Proceedings of the
7th ACM international symposium on Advances in geographic
information systems. GIS’99.Kansas City, Missouri, USA.
[12] Laplanche F., 2002, Conception de Projet Sig Avec UML. Bulletin de
La Société Géographique de Liège, 42, pp.19-25.
[13] Brodeur J., Bédard Y. et Proulx M.-J., 2000. Modelling Geospatial
Application Databases Using UML Based Repositories Aligned with
International Standards in Geomatics, ACMGIS 2000, November 10-11,
Washington DC, USA.
[14] Gutiérrez C., Servigne S., Laurini R., 2007. Towards Real-time
Metadata for Network-Based Geographic Databases, In: ISSDQ 2007 –
5th International Symposium, Spatial Data Quality 2007. p. 8. ITC,
Enschede, the Netherlands, pp.13-15.
[15] Fantazi W., Ezzedine T, 2012. International Conference on Information
Processing and Wireless Systems March 16-18, 2012 Sousse, Tunisia.
IP-WIS « Architecture of Real-Time Spatio-Temporal Metadata for
Wireless Sensor ».
[16] Fantazi W., Ezzedine T., Z. Bargaoui, 2014. Implementing a Sensor
Network for Monitoring of Drought Indicators. In International
Scientific Symposium of Water Management and Desertification 26-
28th November 2014 Istanbul/ Turkey.
[17] Pankaj Sharma. 2013, Socio-Economic Implications of Wireless Sensor
Networks with Special Reference to its Application in Agriculture, in
African Journal of Computing & ICT, Vol 6. No. 2, June 2013, pp.31-
40.
[1] Rengers, N., Soeters, R. and Westen, C.J. Van (1992) Remote sensing
and GIS applied to mountain hazard mapping. Episodes, Vol.15, No.1,
March 1992, pp.36-45.
[2] Johnston C. A, Groffman P, Breshears DD, et al. 2004. Carbon Cycling
in Soil. Front Ecol Environ 2: 522–28.
[3] Díaz S. E., Pérez J. C., Mateos A. C., Marinescu M.C., B. B., Guerra,
2011. A Novel Methodology for the Monitoring of the Agricultural
Production Process Based on Wireless Sensor Networks. Computers and
Electronics in Agriculture, vol. 76, no. 2, pages 252–265, 2011.
[4] Garcia-Sanchez A. J., Garcia-Sanchez F., J. Garcia-Haro, 2011. Wireless
Sensor Network Deployment for Integrating Video Surveillance and
Data-Monitoring in Precision Agriculture over Distributed Crops.
Computers and Electronics in Agriculture, vol. 75, no. 2, pages 288 –
303, 2011.
[5] López Riquelme J.A., F. Soto, J. Suardíaz, P. Sánchez, A. Iborra and
J.A. Vera, 2009. Wireless Sensor Networks for Precision Horticulture in
Southern Spain. Computers and Electronics in Agriculture, vol. 68, no.
1, pages 25 – 35, 2009.
[6] Wark T., P. Corke, P. Sikka, L. Klingbeil, Ying Guo, C. Crossman, P.
Valencia, D. Swain and G. Bishop-Hurley, 2007. Transforming
Agriculture through Pervasive Wireless Sensor Networks. Pervasive
Computing, IEEE, vol. 6, no. 2, pages 50–57, 2007.
[7] Eagleson, P.S. (1994) the Evolution of Modern Hydrology (from
Watershed to Continent in 30 years), Advances in Water Resources 17
(1994), 3-18.
[8] Parent C., Spaccapietra S., Zimányi E., Donni P., Plazanet C., Vangenot
C., Rognon N., Rausaz P. MADS, Modèle Conceptuel Spatio-Temporel.
Revue Internationale de Géomatique, 1997, Vol. 7, n°3-4, pp. 317-351.
[9] Bédard Y., 1999. Visual Modelling of Spatial Databases: Towards
Spatial PVL and UML, Géomatica, 53(2), pp.169-186.
[10] Spaccapietra S., Parent C., Zimányi E., 1998. Modeling Time from a
Conceptual Perspective, In: Int. Conf. on Information and Knowledge
Management (CIKM 1998).
[11] Parent C., Spaccapietra S., Zimányi E., 1999. Spatio-Temporal
Conceptual Models: Data Structures + Space + Time, Proceedings of the
7th ACM international symposium on Advances in geographic
information systems. GIS’99.Kansas City, Missouri, USA.
[12] Laplanche F., 2002, Conception de Projet Sig Avec UML. Bulletin de
La Société Géographique de Liège, 42, pp.19-25.
[13] Brodeur J., Bédard Y. et Proulx M.-J., 2000. Modelling Geospatial
Application Databases Using UML Based Repositories Aligned with
International Standards in Geomatics, ACMGIS 2000, November 10-11,
Washington DC, USA.
[14] Gutiérrez C., Servigne S., Laurini R., 2007. Towards Real-time
Metadata for Network-Based Geographic Databases, In: ISSDQ 2007 –
5th International Symposium, Spatial Data Quality 2007. p. 8. ITC,
Enschede, the Netherlands, pp.13-15.
[15] Fantazi W., Ezzedine T, 2012. International Conference on Information
Processing and Wireless Systems March 16-18, 2012 Sousse, Tunisia.
IP-WIS « Architecture of Real-Time Spatio-Temporal Metadata for
Wireless Sensor ».
[16] Fantazi W., Ezzedine T., Z. Bargaoui, 2014. Implementing a Sensor
Network for Monitoring of Drought Indicators. In International
Scientific Symposium of Water Management and Desertification 26-
28th November 2014 Istanbul/ Turkey.
[17] Pankaj Sharma. 2013, Socio-Economic Implications of Wireless Sensor
Networks with Special Reference to its Application in Agriculture, in
African Journal of Computing & ICT, Vol 6. No. 2, June 2013, pp.31-
40.
@article{"International Journal of Information, Control and Computer Sciences:70726", author = "Fantazi Walid and Ezzedine Tahar and Bargaoui Zoubeida", title = "Wireless Sensor Network to Help Low Incomes Farmers to Face Drought Impacts", abstract = "This research presents the main ideas to implement an
intelligent system composed by communicating wireless sensors
measuring environmental data linked to drought indicators (such as
air temperature, soil moisture , etc...). On the other hand, the setting
up of a spatio temporal database communicating with a Web mapping
application for a monitoring in real time in activity 24:00 /day, 7
days/week is proposed to allow the screening of the drought
parameters time evolution and their extraction. Thus this system
helps detecting surfaces touched by the phenomenon of drought.
Spatio-temporal conceptual models seek to answer the users who
need to manage soil water content for irrigating or fertilizing or other
activities pursuing crop yield augmentation. Effectively, spatiotemporal
conceptual models enable users to obtain a diagram of
readable and easy data to apprehend. Based on socio-economic
information, it helps identifying people impacted by the phenomena
with the corresponding severity especially that this information is
accessible by farmers and stakeholders themselves. The study will be
applied in Siliana watershed Northern Tunisia.", keywords = "WSN, database spatio-temporal, GIS, web-mapping,
indicator of drought.", volume = "9", number = "8", pages = "1935-5", }
