Application of ISFET Microsensors with Mobile Network to Build IoT for Water Environment Monitoring

Cao, Feifei; Jiang, Feng; Liu, Ziqinq; Chen, Bang; Yang, Zhu

doi:10.1109/ie.2014.38

Cited by 6 publications

(3 citation statements)

References 11 publications

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“…Research of the utilization of the Internet of Things (IoT) is being grown, particularly compared to its capacity to help people in the entirety of their exercises, one of which is with regards to the climate. Exploration led by [12] fostered the plan and execution of the Wireless Sensor Network (WSN) just as examination led by [13]. Examination identified with the utilization of WSN for mushroom development was done by [6] [7][8], where the exploration utilized the IoT/WSN way to deal with naturally screen the dampness and temperature of the kumbung.…”

Section: Related Workmentioning

confidence: 99%

RETRACTED: Adaptive Temperature And Humidity Control System on Kumbung Mushroom using Fuzzy Neural Network Algorithm

Hartadi

Agustianto

Destarianto

et al. 2022

IOP Conf. Ser.: Earth Environ. Sci.

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National mushroom production in 2018, 2017, 2016, and 2015 were: 31052, 3702, 40915 and 33485 tons. Mushroom cultivation, especially oyster mushrooms, has the potential to be developed more widely in Indonesia because it has economic value and is environmentally friendly. However, the cultivation of oyster mushrooms has challenges. The challenge that arises in the cultivation of oyster mushrooms is to grow well at a temperature of 16 – 30 °C and a relative humidity of 80 – 95%. Environmental conditioning carried out by farmers on average through spraying water in mushroom kumbung manually. The use of manual methods requires high human resources, besides that it is not effective and efficient. This study aims to develop an Adaptive Temperature and Humidity Control System on Kumbung using Backpropagation Neural Network, where to determine the temperature and humidity the system will evaluate the readings of several sensors at once. The system developed is an adaptive system with an accuracy of 97%, so it is can be used to increase the precision of mushroom cultivation, so that production efficiency and increase in mushroom production can be achieved.

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Section: Related Workmentioning

confidence: 99%

RETRACTED: Adaptive Temperature And Humidity Control System on Kumbung Mushroom using Fuzzy Neural Network Algorithm

Hartadi

Agustianto

Destarianto

et al. 2022

IOP Conf. Ser.: Earth Environ. Sci.

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“…Research of the utilization of IoT has been grown, particularly compared to its capacity to help people in the entirety of their exercises, one of which is with regards to the climate. An examination led by [5][6] [7][8] [9]. Notwithstanding, the execution of WQM explicitly for the primary hydroponics of Vename Shrimp is as yet inadequate with regards to, this is shown by the connected examination found in IEEE [10][11].…”

Section: Introductionmentioning

confidence: 99%

RETRACTED: Surface Modeling Vehicle for Shrimp Ponds using Artificial Neural Network

Destarianto

Agustianto

Rosdiana

et al. 2022

IOP Conf. Ser.: Earth Environ. Sci.

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The worldwide frozen shrimp trade market in 2018 was recorded at the US $ 17.2 billion or around Rp.232.2 trillion. Indonesia is one of the principal exporters of frozen shrimp in the worldwide market. In light of this information, shrimp cultivating is a promising area, yet shrimp cultivating is particularly controlled by water quality. Water quality in shrimp cultivating consistently changes. Many variables impact changes in water quality (shrimp biomass, PH, and temperature). These components in the water should be inside the standard limit rank. Thusly, to accomplish the creation effectiveness of the shrimp business, it is important to robotize water quality control. This study aims to develop Surface Modeling Vehicles (SMV) for Shrimp Ponds utilizing an Artificial Neural Network. The test outcomes show an exactness pace of 94%, the expectation is that the instruments created by the exploration will want to acknowledge exact Vename Shrimp cultivating, so creation proficiency and expanded shrimp creation can be accomplished.

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“…Los sensores que miden parámetros críticos del agua se instalan en lugares estratégicos con el fin de garantizar una alta calidad de suministro. Esto evita la contaminación accidental de los drenajes de aguas pluviales, agua potable y eliminación de aguas residuales [187]. La misma red se puede ampliar para controlar riego en tierras agrícolas.…”

Section: Dominios De Aplicaciónunclassified

Aplicaciones de SWE en entornos industriales

Salazar¹

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This thesis has been created within the framework of the interoperability of the networks of sensors in industrial environments, using standard SWE (Sensor Web Enablement). It has developed from the participation in different research projects, within the research group SATRD (Distributed Real Time Systems and Applications) of the Communications Department of the UPV.Has gone a long time since the appearance of the first sensors that were only able to respond to a stimulus, to the concept of sensor web, where sensors can be remotely configured, perform actions and process and integrate data from other sensors. Nowadays, the use of networks of sensors or WSN (Wireless Sensor Networks) is widespread in several fields, to gather information, which can then be used by other applications.

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Application of ISFET Microsensors with Mobile Network to Build IoT for Water Environment Monitoring

Cited by 6 publications

References 11 publications

RETRACTED: Adaptive Temperature And Humidity Control System on Kumbung Mushroom using Fuzzy Neural Network Algorithm

RETRACTED: Adaptive Temperature And Humidity Control System on Kumbung Mushroom using Fuzzy Neural Network Algorithm

RETRACTED: Surface Modeling Vehicle for Shrimp Ponds using Artificial Neural Network

Aplicaciones de SWE en entornos industriales

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