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InWaterSense: An Intelligent Wireless Sensor Network for Monitoring Surface Water Quality to a River in Kosovo
University of Prishtina, Serbia.
University of Prishtina, Serbia.
Tyndall National Institute, Ireland;University College Cork, Ireland.
Linnéuniversitetet, Fakulteten för teknik (FTK), Institutionen för datavetenskap och medieteknik (DM).ORCID-id: 0000-0003-0512-6350
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2018 (Engelska)Ingår i: International Journal of Agricultural and Environmental Information Systems, ISSN 1947-3192, Vol. 9, nr 1, s. 39-61Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

A shift in water monitoring approach from traditional grab sampling to novel wireless sensors is gaining in popularity not only among researchers but also in the market. These latest technologies readily enable numerous advantageous monitoring arrangements like remote, continuous, real-time, and spatially-dense and broad in coverage measurements, and identification of long-term trends of parameters of interest. Thus, a WSN system is implemented in a river in Kosovo as part of the InWaterSense project to monitor its water quality parameters. It is one of the first state of the art technology demonstration systems of its kind in the domain of water monitoring in developing countries like Kosovo. Water quality datasets are transmitted at pre-programmed intervals from sensing stations deployed in the river to the server at university via the GPRS network. Data is then made available through a portal to different target groups (policy-makers, water experts, and citizens). Moreover, the InWaterSense system behaves intelligently like staying in line with water quality regulatory standards.

Ort, förlag, år, upplaga, sidor
IGI Global, 2018. Vol. 9, nr 1, s. 39-61
Nationell ämneskategori
Övrig annan teknik
Forskningsämne
Data- och informationsvetenskap, Datavetenskap
Identifikatorer
URN: urn:nbn:se:lnu:diva-68718DOI: 10.4018/IJAEIS.2018010103ISI: 000429506200003OAI: oai:DiVA.org:lnu-68718DiVA, id: diva2:1156275
Konferens
Hershey, PA, USA
Projekt
InWaterSenseTillgänglig från: 2017-11-11 Skapad: 2017-11-11 Senast uppdaterad: 2019-05-29Bibliografiskt granskad

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