IoT for Aquaculture 4.0 Smart and easy-to-deploy real-time water monitoring with IoT

Dupont, Charlotte; Cousin, Philippe; DuPont, Samuel J.

doi:10.1109/giots.2018.8534581

Cited by 55 publications

(31 citation statements)

References 3 publications

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“…AI innovation was overwhelmingly supported by gender, environment, and age. Cutting edge IoT combined with AI encounters increasing demand, approach to integrated multi-trophic, and produces environment-friendly (Dupont et al, 2018). Unfortunately, the view an integrated marine framework aims at energy diversi cation by ICZM linking Big Data, AI, IoT for economic development and environmental protection but lacks administrative coordination, speci c legal mechanisms at offering environmental protection against impacts from energy diversi cation is consistent with the previous study (Salvador et al, 2019).…”

Section: Iczm Linking Big Data Iot Ai Innovation For Sccdsupporting

confidence: 83%

Energy Replenishment Diversification Under Marine Spatial Planning Connects Big Data, Artificial Intelligence, Internet of Things for Coastal Community Sustainability

Liao¹

2020

Preprint

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Background Controversial coal power plant restart and non-nuke policy were rejected by referendum in Taiwan on 24 Nov 2018. Outcomes affecting energy replenishment and undermining economic stability are criticized politicization because coal energy is detrimental but no nuke beneficial for the environment. These policies could be contradictory. Problem No autonomous energy puts the country into extreme risk and is controlled by foreigners. Developing energy faces a traditional tradeoff between economic development and environmental protection. Purpose The assumption an innovative energy diversification linking Big Data, artificial intelligence (AI), and the Internet of Things (IoT) is encouraged. The paper investigates upgrading liquified petroleum gas (LPG) to liquified natural gas (LNG) under marine spatial planning (MSP) for energy replenishment and creating an energy diversification framework through integrated coastal zone management (ICZM) linking Big Data, IoT, AI whether are supported. Results Online sampling investigation results, enhancing LPG to LNG at the ecologically biologically significant area (EBSA) under MSP was less encouraged but linking Big Data, IoT, AI innovation through ICZM was overwhelmingly supported and consistent with goalkeepers interview. Research finding gender, the environment, age revealed no significant difference from LNG through MSP and AI under ICZM. Males more support LNG energy replenishment and energy diversification. Energy deficiency, environmental protection, and economic development were interrelated. Conclusion The results LPG to LNG revealed less encouraging and implicates many coastal communities in favor of tangible stable electricity without blackout is important than the intangible slogan EBSA protection, or perhaps renewable energy is an alternative approach. An autonomous energy diversification framework through ICZM links Big Data, IoT, AI for sustainable coastal community development (SCCD) indicating no significant difference from gender, environment, age, and is consistent with the goalkeepers' interview results supporting energy diversification. The finding males more support LNG and energy diversification. Finally, the study suggests that legislative enforcement establishment designate expertise teamwork to coordinate administration, integrate programs of energy replenishment, creating an autonomous energy diversification framework for monitoring energy demand, supplies, replenishment, and connect Big Data, IoT, AI innovation for SCCD.

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Section: Iczm Linking Big Data Iot Ai Innovation For Sccdsupporting

confidence: 83%

Energy Replenishment Diversification Under Marine Spatial Planning Connects Big Data, Artificial Intelligence, Internet of Things for Coastal Community Sustainability

Liao¹

2020

Preprint

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“…However, some accessories have been included in several official and unofficial bundles. The organization behind the Raspberry Pi [1] consists of two arms. The first two models were developed by the Raspberry Pi Foundation.…”

Section: Working a Raspberry Pimentioning

confidence: 99%

“…The pH around 7 is the natural source water. The water becomes less acidic as the concentration of hydrogen ion decreases for ten-fold for the increases in the number of pH [1] [2] . A reference electrode & a measuring electrode are enclosed in the pH sensor.…”

Section: ) Ph Sensing Modulementioning

confidence: 99%

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Monitoring and Maintenance of Aquaculture Water Quality

Nivedha¹

2019

IJRASET

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Technological significance has been a great support for settling on choice in various fields especially in aquaculture. The advancement of aquaculture has been under development for past many years because of the absence of knowledge in aquaculture learning and natural changes by the fish farmers. Here, it generally concentrates on the upgrading of rural aquaculture development through advanced information and communication processes. It extends the aquaculture organization's ability to meet the needs of fish farmers. This study gives the preferred data at any moment of time from any part of the world and screening their concern instantly at any part of the location. In existing system, the monitoring process of the water level and temperature is done. This will just monitoring the level than controlling it. So, it will miss the checking of water quality. This will create hazardous effect on our usage of water. In the technique we can measure the quality of water using hardware and software. In hardware part it consists of Raspberry Pi version 3, Water Level Sensor, Temperature Sensor, pH Sensor, Pump Motor for controlling water level and pH level and in software in consist of python and HTML. Using both of these operations we can find the quality of water and can improve the aquaculture maintenance process. Keywords used: aquaculture [1][2][3][4] , raspberry pi [1] , water level sensor [1][2][3][4], threshold value 600mV, temperature sensor [2][3][7] , pH sensor threshold value 12mV, python, HTML.

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“…Device integration and management systems [4]- [6] abstract over low-level protocols and are essential to allow both novice and advanced users to benefit from the increasing availability of IoT hardware. Several IoT solutions have been used to implement smart applications for a range of domains including home automation [7], agriculture [8], aquarium management [9], smart campuses [10], entertainment [11], art [12], and more. While the IoT approaches in [7]- [12] allow complicated applications to be developed, they provide limited guarantees on application correctness.…”

Section: Introductionmentioning

confidence: 99%

BigraphTalk: Verified Design of IoT Applications

Archibald

Shieh

et al. 2020

IEEE Internet Things J.

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Graphical IoT device management platforms, such as IoTtalk, make it easy to describe interactions between IoT devices. Applications are defined by dragging-and-dropping devices and specifying how they are connected, e.g. a door sensor controlling a light. While this allows simple and rapid development, it remains possible to specify unwanted device configurations -such as using the same device to drive a motor up and down simultaneously, risking damaging the motor.We propose BigraphTalk, a verification framework for IoTtalk that utilizes formal techniques, based on bigraphs, to statically guarantee that unwanted configurations do not arise. In particular, we check for invalid connections between devices, as well as type errors, e.g. passing a float to a boolean switch. To the best of our knowledge, BigraphTalk is the first platform to support the graphical specification of correct-by-design IoT applications.BigraphTalk provides fully automated verification and feedback without end-users ever needing to specify a bigraph. This means any application, specifiable in IoTtalk, is guaranteed, so long as verification succeeds, not to violate the given configuration constraints when deployed; with no extra cost to the user.

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IoT for Aquaculture 4.0 Smart and easy-to-deploy real-time water monitoring with IoT

Cited by 55 publications

References 3 publications

Energy Replenishment Diversification Under Marine Spatial Planning Connects Big Data, Artificial Intelligence, Internet of Things for Coastal Community Sustainability

Energy Replenishment Diversification Under Marine Spatial Planning Connects Big Data, Artificial Intelligence, Internet of Things for Coastal Community Sustainability

Monitoring and Maintenance of Aquaculture Water Quality

BigraphTalk: Verified Design of IoT Applications

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