An SNN Ontology Based Environment Monitoring Method for Intelligent Irrigation System

Li, Shuoming; Chen, Lei; Chen, Shihong

doi:10.1007/s12204-018-1959-0

Cited by 5 publications

(3 citation statements)

References 11 publications

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“…Ecological carrying capacity is an important standard to measure ecosystem health. Figure 1 describes the relationship between ecosystem health and ecological carrying capacity ( 34 – 37 ). For any relatively independent ecosystem, a certain level of ecological carrying capacity and the level of social and economic pressure bear correspond to a certain level of ecosystem health.…”

Section: Methodsmentioning

confidence: 99%

Health diagnosis of coastal zone ecosystem: China's case

Zhang

Wang²

2023

Front. Public Health

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With its unique geographical location, the coastal zone has concentrated great advantages in resources, population and economy. However, with the deepening of marine resources development activities, a series of problems have emerged in the coastal zone, such as the gradual shortage of resources, the decline of environmental quality and the increase of ecological risks. The coastal zone ecosystem has shown a certain degradation trend. Maintaining the health of the coastal zone ecosystem has become the primary task of the sustainable development of the marine economy. Monitoring the coastal ecosystem carrying capacity, diagnosing the health status of the coastal ecosystem, effectively planning and managing the development and utilization of natural resources in the coastal zone, and controlling human activities related to the sea within the ecological carrying capacity and health limits of the coastal zone are of great significance to the sustainable development of society and economy in the coastal zone. In this study, the ecosystem health model, state space model and ecological health early warning principle were comprehensively applied to construct the coastal ecosystem health diagnosis framework of “Carrying type →Early warning degree →Health level;” The evaluation index system of coastal ecosystem carrying capacity was established; Taking Shandong Province as the empirical research object, the health status of the coastal ecosystem in Shandong Province was diagnosed by using the relevant data from 2007 to 2019. The empirical results show that: (1) From 2007 to 2013, the carrying capacity of the coastal ecosystem in Shandong Province was relatively good, in the state of “loadable” or “critical overload,” while from 2014 to 2019, the carrying capacity was poor, in the state of “overload;” (2) From 2007 to 2013, the early warning degree of coastal ecosystem health in Shandong Province was in the state of “no alarm,” “light alarm,” and “medium alarm,” and the health level was in the state of “very healthy,” “healthy,” and “sub-health;” from 2014 to 2019, the health warning level of the coastal ecosystem in Shandong Province was in the state of “serious alarm” and “extremely serious alarm,” and the health level was in the state of “unhealthy” and “Morbid,” and the health status was worrying; (3) The key influencing factors affecting the carrying capacity of the coastal ecosystem mainly included the output of marine mining, marine GDP, per capita marine production, total amount of main pollutants directly discharged into the sea, domestic tourist arrivals in coastal cities, area of marine nature reserves, proportion of class IV and inferior class IV seawater, average density of beach garbage in the monitoring area, number of medical and health institutions; Finally, some policy suggestions were put forward to improve the health of coastal ecosystem in Shandong Province. In the “discussion” part of this study, the consistency between the research results of this paper and the actual situation of the marine ecosystem in Shandong Province and the existing research results of the same kind is compared, and the applicability and limitations of the research methods in this paper are put forward, indicating that the research methods in this paper are more applicable to the comparative analysis under the same ideal value determination criteria.

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Section: Methodsmentioning

confidence: 99%

Health diagnosis of coastal zone ecosystem: China's case

Zhang

Wang²

2023

Front. Public Health

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“…Interoperabilidade semântica no âmbito de soluções de IoT tem sido foco de vários trabalhos [Honti andAbonyi, 2019] [Drury et al, 2019]. Tais soluções, em geral, fazem uso de inúmeros sensores, formando uma rede de dispositivos que apresentam capacidades complementares e especificações distintas, requerendo abordagens de integração no nível semântico para alinhar a troca de dados entre eles [Li et al, 2018] Nesse contexto, a interoperabilidade semântica se coloca como um dos grandes desafios em soluções IoT, na medida em que o enriquecimento semântico de dados sensoriados brutos (raw sensory data) é crucial para suportar integração de informação, que levará à produção de conhecimento e à inovação [Honti and Abonyi, 2019].…”

Section: Referencial Teóricounclassified

“…Ontologias têm sido reconhecidas como um importante artefato para enriquecer os dados sensoriados e promover interoperabilidade semântica [Honti and Abonyi, 2019]. Assim, SSN tem sido aplicada em diferentes cenários aqueles relacionados à Agricultura de Precisão [W3C, 2017] [Li et al, 2018.…”

Section: Introductionunclassified

Semantic Sensor Network Ontology como modelo de referência em soluções de monitoramento agrícola

Nardi

Alves

Júnior

et al. 2021

Anais Do XIII Congresso Brasileiro De Agroinformática (SBIAGRO 2021)

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Soluções de Internet das Coisas na Agricultura lidam com dispositivos e aplicações de software que não compartilham um mesmo modelo de informação. Isso limita a interoperabilidade semântica entre eles. Este trabalho apresenta e discute o uso da ontologia SSN (W3C) em duas iniciativas relacionadas ao monitoramento de variáveis ambientais. Como resultado, busca-se promover integração de dados de dispositivos e desenvolvimento de aplicações de software mais interoperáveis, na medida em que se utiliza um modelo conceitual de referência.

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Agricultural Irrigation Recommendation and Alert (AIRA) system using optimization and machine learning in Hadoop for sustainable agriculture

Veerachamy

Ramalakshmi

2021

Environ Sci Pollut Res

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An SNN Ontology Based Environment Monitoring Method for Intelligent Irrigation System

Cited by 5 publications

References 11 publications

Health diagnosis of coastal zone ecosystem: China's case

Health diagnosis of coastal zone ecosystem: China's case

Semantic Sensor Network Ontology como modelo de referência em soluções de monitoramento agrícola

Agricultural Irrigation Recommendation and Alert (AIRA) system using optimization and machine learning in Hadoop for sustainable agriculture

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