CPS/IoT Ecosystem: Indoor Vertical Farming System

Isakovic, Haris; Fasching, Alexander; Punzenberger, Lukas; Grosu, Radu

doi:10.1109/isce.2019.8900974

Cited by 22 publications

(10 citation statements)

References 9 publications

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“…Accordingly, an interesting direction for future research is to investigate the practicality of designing digital twins in accordance with the human ability to generate accurate inferences from very few sensory inputs [ 130 ]. Such research can draw upon the latest findings from neuroscience and from machine learning, both of which indicate that simple models have the potential to be as accurate as complex models [ 42 , 118 ]. An example of this is model reduction in which redundant model parameters are removed to prevent model over-fitting and promote selection of the most parsimonious model that can successfully account for previous observations [ 42 ].…”

Section: Discussionmentioning

confidence: 99%

“…Also, vertical farming can be scaled out through modular kits. Physical disorder and information uncertainty in vertical farming can be reduced by situating inside buildings [ 118 ]. Furthermore, physical disorder, information uncertainty, and unproductive energy consumption of urban allotments can be reduced through initial energy expenditure in careful planning of, for example, plant types and irrigation methods [ 119 ].…”

Section: Federated Digital Twins For Synchronous Generative Developmentmentioning

confidence: 99%

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Synchronous Generative Development amidst Situated Entropy

Fox

2022

Entropy

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The Sustainable Development Goals have been criticized for not providing sufficient balance between human well-being and environmental well-being. By contrast, joint agent-environment systems theory is focused on reciprocal synchronous generative development. The purpose of this paper is to extend this theory towards practical application in sustainable development projects. This purpose is fulfilled through three interrelated contributions. First, a practitioner description of the theory is provided. Then, the theory is extended through reference to research concerned with multilevel pragmatics, competing signals, commitment processes, technological mediation, and psychomotor functioning. In addition, the theory is related to human-driven biosocial-technical innovation through the example of digital twins for agroecological urban farming. Digital twins being digital models that mirror physical processes; that are connected to physical processes through, for example, sensors and actuators; and which carry out analyses of physical processes in order to improve their performance. Together, these contributions extend extant theory towards application for synchronous generative development that balances human well-being and environmental well-being. However, the practical examples in the paper indicate that counterproductive complexity can arise from situated entropy amidst biosocial-technical innovations: even when those innovations are compatible with synchronous generative development.

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Section: Discussionmentioning

confidence: 99%

Section: Federated Digital Twins For Synchronous Generative Developmentmentioning

confidence: 99%

Synchronous Generative Development amidst Situated Entropy

Fox

2022

Entropy

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“…The sensed information by the sensor is transmitted towards the cloud server by using IoT protocol. The detected data is stored within the database and the control actions are performed for maintaining the optimal situation in the environment [47].…”

Section: Figure 10 Conceptual Design Of Greenhouse Farmingmentioning

confidence: 99%

Internet of Things in Greenhouse Agriculture: A Survey on Enabling Technologies, Applications, and Protocols

Farooq

Riaz

Helou³

et al. 2022

IEEE Access

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The greenhouse is one of the sustainable forms of smart agricultural farming. It is considered as an alternate method to overcome the food crisis which is generated due to high population growth, climate change, and environmental pollution. Although this method supports off-the-season crops within the enclosed area even in severe climatic zones. It has required to efficiently control and manage the crop parameters at greenhouse in a more precise and secure way. The advancement of the Internet of Things (IoT) has introduced smart solutions to automate the greenhouse farming parameters such as plant monitoring, internal atmosphere control, and irrigation control. The survey presents a hierarchy on the major components of IoT-based greenhouse farming. A rigorous discussion on greenhouse farming techniques, IoT-based greenhouse categories, network technologies (cloud/edge computing, IoT protocols, data analytics, sensors) has been presented. Furthermore, a detailed discussion on mobile-based greenhouse applications and IoT applications has been presented to manage the greenhouse farm. Moreover, the success stories and statistical analysis of some agricultural countries have been presented to standardize the IoT-based greenhouse farming. Lastly, the open issues and research challenges related to IoT-enabled greenhouse farming has been presented with state-of-the-art future research directions.

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“…It takes up 3-D space for farming with controlled water, nutrients, minimal pesticides, and artificial lighting sources. The practical limitation of vertical farming system is generation of artificial light sources for plant growth and the large costs involved [57].…”

Section: Urban Farmingmentioning

confidence: 99%

Everything You wanted to Know about Smart Agriculture

Mitra¹,

Vangipuram²,

Bapatla³

et al. 2022

Preprint

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The world population is anticipated to increase by close to 2 billion by 2050 causing a rapid escalation of food demand. A recent projection shows that the world is lagging behind accomplishing the "Zero Hunger" goal, in spite of some advancements. Socio-economic and well being fallout will affect the food security. Vulnerable groups of people will suffer malnutrition. To cater to the needs of the increasing population, the agricultural industry needs to be modernized, become smart, and automated. Traditional agriculture can be remade to efficient, sustainable, eco-friendly smart agriculture by adopting existing technologies. In this survey paper the authors present the applications, technological trends, available datasets, networking options, and challenges in smart agriculture. How Agro Cyber Physical Systems are built upon the Internet-of-Agro-Things is discussed through various application fields. Agriculture 4.0 is also discussed as a whole. We focus on the technologies, such as Artificial Intelligence (AI) and Machine Learning (ML) which support the automation, along with the Distributed Ledger Technology (DLT) which provides data integrity and security. After an in-depth study of different architectures, we also present a smart agriculture framework which relies on the location of data processing. We have divided open research problems of smart agriculture as future research work in two groups -from a technological perspective and from a networking perspective. AI, ML, the blockchain as a DLT, and Physical Unclonable Functions (PUF) based hardware security fall under the technology group, whereas any network related attacks, fake data injection and similar threats fall under the network research problem group.

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CPS/IoT Ecosystem: Indoor Vertical Farming System

Cited by 22 publications

References 9 publications

Synchronous Generative Development amidst Situated Entropy

Synchronous Generative Development amidst Situated Entropy

Internet of Things in Greenhouse Agriculture: A Survey on Enabling Technologies, Applications, and Protocols

Everything You wanted to Know about Smart Agriculture

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