A system for the rapid design and implementation of Personalized Agricultural Key Performance Indicators issued from sensor data

Bimonte, Sandro; Naoufal, Echcherki; Gineste, L.

doi:10.1016/j.compag.2016.09.010

Cited by 5 publications

(4 citation statements)

References 30 publications

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“…O que se apresenta em [Bimonte et al 2016] trata de um Sistema de Informac ¸ão de Gestão Agrícola, chamado VBoxReporting, voltado a análise de consumo energético em implementos agrícolas para apoio a tomada de decisão. O sistema é capaz de coletar dados de localizac ¸ão e nível de combustível por meio dos sensores de baixo custo dos equipamentos.…”

Section: Trabalhos Relacionadosunclassified

Implementação de Sorvedouro de de Dados de Aplicação IoT Irrigação Automática

Silva,

Araújo,

Rodrigues

et al. 2023

Anais Da XXIII Escola Regional De Computação Bahia, Alagoas E Sergipe (ERBASE 2023)

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Section: Trabalhos Relacionadosunclassified

Implementação de Sorvedouro de de Dados de Aplicação IoT Irrigação Automática

Silva,

Araújo,

Rodrigues

et al. 2023

Anais Da XXIII Escola Regional De Computação Bahia, Alagoas E Sergipe (ERBASE 2023)

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“…Visualisations in viticulture enable a better vineyard monitoring, reducing costs and at the same time, generating a more transparent representation of the existent variability in the vineyard, which is valuable for the optimisation • AgroDSS [31] • AquaGIS [32] • • ATLAS [33] • • Blauth et al [34] • Byishimo et al [35] • CAMDT [36] • CropGIS [37] • • CropSAT [38] • • DIDAS [39] • DyNoFlo [40] • • Galindo et al [41] • GeoVisage [42] • Geovit [43] • GramyaVikas [44] • HydroQual [45] • Li et al [46] • LMTool [47] • • Luvisi et al [48] • mDSS [49] • SmartScape [50] • • VBoxReporting [51] Vite.net [52] • • • visualizeR [8] • ViPER [53] • Ochola et al [54] • Falcao et al [55] • LandCaRe DSS [56] • ValorE [57] • Agroland [58] • Gandhi et al [59] • • CaNaSTA [60] • eFarmer [61] • FARMERS [62] • PlanteInfo [63] • CropScape [64] • SIMAGRI [65] • FDSSFIS [66] • MOTIFS [67] • CarrotAge [68] • AgriSensor [69] • • • CognitiveInputs [70] • • Ruß et al [71] Tan et al…”

Section: Viticulturementioning

confidence: 99%

“…AgMine [28] • AgriAG [29] • • • AgriSuit [30] • AgroDSS [31] • AquaGIS [32] • Blauth et al [34] • Byishimo et al [35] • CAMDT [36] • • • CropGIS [37] • CropSAT [38] • DIDAS [39] • DyNoFlo Dairy [40] • Galindo et al [41] • • GeoVisage [42] • Geovit [43] • GramyaVikas [44] HydroQual [45] Li et al [46] • LMTool [47] • SmartScape [50] • VBoxReporting [51] • Vite.net [52] • ViPER [53] • Ochola et al [54] • • LandCaRe [56] • ValorE [57] • • Gandhi et al [59] • • • eFarmer [61] • FARMERS [62] •…”

Section: End-usersmentioning

confidence: 99%

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A review of visualisations in agricultural decision support systems: An HCI perspective

Gutiérrez

Htun

Schlenz³

et al. 2019

Computers and Electronics in Agriculture

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Decision Support Systems (DSSs) are used in precision agriculture to provide feedback to a variety of stakeholders, including farmers, advisers, researchers and policymakers. However, increments in the amount of data might lead to data quality issues, and as these applications scale into big, real-time monitoring systems the problem gets even more challenging. Visualisation is a powerful technique used in these systems that provides an indispensable step in assisting end-users to understand and interpret the data. In this paper, we present a systematic review to synthesise literature related to the use of visualisation techniques in the domain of agriculture. The search identified 61 eligible articles, from which we established end-users, visualisation techniques and data collection methods across different application domains. We found visualisation techniques used in various areas of agriculture, including viticulture, dairy farming, wheat production and irrigation management. Our results show that the majority of DSSs utilise maps, together with satellite imagery, as the central visualisation. Also, we observed that there is an excellent opportunity for dashboards to enable end-users with better interaction support to understand the uncertainty of data. Based on this analysis, we provide design guidelines towards the implementation of more interactive and visual DSSs.

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