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Authors = Hanna Huitu

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HANNA (102) , HUITU (2)

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Open AccessReview Geosensors to Support Crop Production: Current Applications and User Requirements
Sensors 2011, 11(7), 6656-6684; doi:10.3390/s110706656
Received: 16 May 2011 / Revised: 16 June 2011 / Accepted: 22 June 2011 / Published: 27 June 2011
Cited by 11 | Viewed by 6129 | PDF Full-text (342 KB) | HTML Full-text | XML Full-text
Abstract
Sensor technology, which benefits from high temporal measuring resolution, real-time data transfer and high spatial resolution of sensor data that shows in-field variations, has the potential to provide added value for crop production. The present paper explores how sensors and sensor networks have
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Sensor technology, which benefits from high temporal measuring resolution, real-time data transfer and high spatial resolution of sensor data that shows in-field variations, has the potential to provide added value for crop production. The present paper explores how sensors and sensor networks have been utilised in the crop production process and what their added-value and the main bottlenecks are from the perspective of users. The focus is on sensor based applications and on requirements that users pose for them. Literature and two use cases were reviewed and applications were classified according to the crop production process: sensing of growth conditions, fertilising, irrigation, plant protection, harvesting and fleet control. The potential of sensor technology was widely acknowledged along the crop production chain. Users of the sensors require easy-to-use and reliable applications that are actionable in crop production at reasonable costs. The challenges are to develop sensor technology, data interoperability and management tools as well as data and measurement services in a way that requirements can be met, and potential benefits and added value can be realized in the farms in terms of higher yields, improved quality of yields, decreased input costs and production risks, and less work time and load. Full article
(This article belongs to the Special Issue Sensors in Agriculture and Forestry)
Open AccessArticle Wireless in-situ Sensor Network for Agriculture and Water Monitoring on a River Basin Scale in Southern Finland: Evaluation from a Data User’s Perspective
Sensors 2009, 9(4), 2862-2883; doi:10.3390/s90402862
Received: 4 March 2009 / Revised: 20 April 2009 / Accepted: 21 April 2009 / Published: 21 April 2009
Cited by 27 | Viewed by 9577 | PDF Full-text (369 KB) | HTML Full-text | XML Full-text
Abstract
Sensor networks are increasingly being implemented for environmental monitoring and agriculture to provide spatially accurate and continuous environmental information and (near) real-time applications. These networks provide a large amount of data which poses challenges for ensuring data quality and extracting relevant information. In
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Sensor networks are increasingly being implemented for environmental monitoring and agriculture to provide spatially accurate and continuous environmental information and (near) real-time applications. These networks provide a large amount of data which poses challenges for ensuring data quality and extracting relevant information. In the present paper we describe a river basin scale wireless sensor network for agriculture and water monitoring. The network, called SoilWeather, is unique and the first of this type in Finland. The performance of the network is assessed from the user and maintainer perspectives, concentrating on data quality, network maintenance and applications. The results showed that the SoilWeather network has been functioning in a relatively reliable way, but also that the maintenance and data quality assurance by automatic algorithms and calibration samples requires a lot of effort, especially in continuous water monitoring over large areas. We see great benefits on sensor networks enabling continuous, real-time monitoring, while data quality control and maintenance efforts highlight the need for tight collaboration between sensor and sensor network owners to decrease costs and increase the quality of the sensor data in large scale applications. Full article
(This article belongs to the Special Issue Workshop Sensing A Changing World)

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