2007
DOI: 10.1162/itid.2007.4.1.51
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COMMONSense Net: A Wireless Sensor Network for Resource-Poor Agriculture in the Semiarid Areas of Developing Countries

Abstract: COMMONSense Net (CSN) is an ongoing research project that focuses on the design and implementation of a sensor network for agricultural management in developing countries, with a special emphasis on the resource-poor farmers of semiarid regions. Throughout the year 2004, we carried out a survey on the information needs of the population living in a cluster of villages in Southern Karnataka, India. The results highlighted the potential that environment-related information has for the improvement of farming stra… Show more

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Cited by 71 publications
(27 citation statements)
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“…En los proyectos documentados en [16][17][18][19][20] se ejecutaron despliegues de WSN en campos de cultivo con diferentes productos agrícolas. Del análisis de estos trabajos se define el modelo de red para MOR4WSN como sigue.…”
Section: A Modelo De Redunclassified
“…En los proyectos documentados en [16][17][18][19][20] se ejecutaron despliegues de WSN en campos de cultivo con diferentes productos agrícolas. Del análisis de estos trabajos se define el modelo de red para MOR4WSN como sigue.…”
Section: A Modelo De Redunclassified
“…However, this routing protocol does not guarantee to eliminate sensing holes. COMMONSense Net (CNS) [2] is another WSN-based agriculture monitoring project developed for semiarid regions in developing countries. The routing protocol of CNS uses tree structure which is not reliable since a link failure or sensor node failure can make other nodes unreachable to BS.…”
Section: Literature Reviewmentioning
confidence: 99%
“…In this article, we focus on routing and topology control challenges. Many of the existing routing protocols [1][2][3] use energy-inefficient tree structure and dynamic flooding. These protocols use the number of hops as the length of data transmission path.…”
Section: Introductionmentioning
confidence: 99%
“…Examples include debris flow monitoring systems [1], [2], agriculture systems [3], and flood warning systems [4]. All these applications rely on collecting enough samples to reconstruct the monitored signal.…”
Section: Introductionmentioning
confidence: 99%