Data communication mechanism for greenhouse environment monitoring and control: An agent-based IoT system

Wang, Jizhang; Chen, Meizheng; Zhou, Jinsheng; Li, Pingping

doi:10.1016/j.inpa.2019.11.002

Cited by 26 publications

(16 citation statements)

References 11 publications

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“…Using computers in the future is able to dominate human work and defeat human computing capabilities such as controlling electronic equipment remotely using internet media, IoT allows users to manage and optimize electronics and electrical equipment that uses the internet. We can utilize the IoT system for monitoring and control of the greenhouse environment [5], [7]- [10]. This speculates that in the near future communication between computers and electronic equipment is able to exchange information between them thereby reducing human interaction.…”

Section: Research Methods 21 Internet Of Thingsmentioning

confidence: 99%

Applying fuzzy proportional integral derivative on Internet of things for figs greenhouse

Riansyah

Mulyono

Roichani

2021

IJ-AI

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Indonesia is an agrarian country where most of population work as farmers. Various planting media have been developed in Indonesia such as using greenhouses. Greenhouse is one of very promising planting media for plant cultivators, because it can be a solution to challenges of extreme climate change. In a greenhouse, the state of the room can be easily controlled using technologies such as automatic watering systems, air temperature control, air humidity and soil moisture. This research focuses on figs by applying fuzzy proportional integral derivative (FPID) as artificial intelligence on the Internet of things (IoT) for greenhouses. It uses Tsukamoto method serves to monitor air conditions and soil conditions and then it is coupled with proportional integral derivative (PID) control to control air temperature, air humidity, and soil moisture so that it is always in the ideal condition of figs in greenhouse. By implementing FPID on IoT for greenhouse, the development of figs in greenhouse can be optimized because air and soil conditions can be maintained in ideal conditions.

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Section: Research Methods 21 Internet Of Thingsmentioning

confidence: 99%

Applying fuzzy proportional integral derivative on Internet of things for figs greenhouse

Riansyah

Mulyono

Roichani

2021

IJ-AI

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“…Despite mature IoT techniques, data loss during the transfer process ("Process" might imply as (1) the data are not received by the target recipient, (2) the data are not being sent from the sender or (3) the data are being received but the recipient's processor trims the data, and the recipient chooses not to store all the received data) is still a problem due to various reasons such as software incompatibility and data fading (the gradual degradation of the bits on storage media that are not in constant use). The current simulation methodologies for the built environment are generally not correlated with the real-time environmental data (ur Rehman et al, 2019;Wang et al, 2020). Not only does the next generation of DT allows real-time visualization and prediction to aid decision-making, but it also provides autonomous feedback and management of the built environment (Deng et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

An investigation for integration of deep learning and digital twins towards Construction 4.0

Kor

Yitmen

Alizadehsalehi

2022

SASBE

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PurposeThe purpose of this paper is to investigate the potential integration of deep learning (DL) and digital twins (DT), referred to as (DDT), to facilitate Construction 4.0 through an exploratory analysis.Design/methodology/approachA mixed approach involving qualitative and quantitative analysis was applied to collect data from global industry experts via interviews, focus groups and a questionnaire survey, with an emphasis on the practicality and interoperability of DDT with decision-support capabilities for process optimization.FindingsBased on the analysis of results, a conceptual model of the framework has been developed. The research findings validate that DL integrated DT model facilitating Construction 4.0 will incorporate cognitive abilities to detect complex and unpredictable actions and reasoning about dynamic process optimization strategies to support decision-making.Practical implicationsThe DL integrated DT model will establish an interoperable functionality and develop typologies of models described for autonomous real-time interpretation and decision-making support of complex building systems development based on cognitive capabilities of DT.Originality/valueThe research explores how the technologies work collaboratively to integrate data from different environments in real-time through the interplay of the optimization and simulation during planning and construction. The framework model is a step for the next level of DT involving process automation and control towards Construction 4.0 to be implemented for different phases of the project lifecycle (design–planning–construction).

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“…Besides, Singh’s model ignored the management and automation of the present greenhouse. Wang et al [ 32 ] designed a data encapsulation method that could be feasibly applied to achieve data communication and data interoperability in a distributed greenhouse IoT system. Wang’s research tested the data communication mechanism for real-time and cumulative data synchronization between the gateway and the server.…”

Section: Introductionmentioning

confidence: 99%

A Cloud-Based IoT Platform for Precision Control of Soilless Greenhouse Cultivation

Sagheer

Mohammed

Riad

et al. 2020

Sensors

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Food security has become an increasingly important challenge for all countries globally, particularly as the world population continues to grow and arable lands are diminishing due to urbanization. Water scarcity and lack of labor add extra negative influence on traditional agriculture and food production. The problem is getting worse in countries with arid lands and harsh climate, which exacerbates the food gap in these countries. Therefore, smart and practical solutions to promote cultivation and combat food production challenges are highly needed. As a controllable environment, greenhouses are the perfect environment to improve crops’ production and quality in harsh climate regions. Monitoring and controlling greenhouse microclimate is a real problem where growers have to deal with various parameters to ensure the optimal growth of crops. This paper shows our research in which we established a multi-tier cloud-based Internet of Things (IoT) platform to enhance the greenhouse microclimate. As a case study, we applied the IoT platform on cucumber cultivation in a soilless medium inside a commercial-sized greenhouse. The established platform connected all sensors, controllers, and actuators placed in the greenhouse to provide long-distance communication to monitor, control, and manage the greenhouse. The implemented platform increased the cucumber yield and enhanced its quality. Moreover, the platform improved water use efficiency and decreased consumption of electrical energy. Based on the positive impact on water use efficiency and enhancement on cucumber fruit yield and quality, the established platform seems quite suitable for the soilless greenhouse cultivation in arid regions.

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Data communication mechanism for greenhouse environment monitoring and control: An agent-based IoT system

Cited by 26 publications

References 11 publications

Applying fuzzy proportional integral derivative on Internet of things for figs greenhouse

Applying fuzzy proportional integral derivative on Internet of things for figs greenhouse

An investigation for integration of deep learning and digital twins towards Construction 4.0

A Cloud-Based IoT Platform for Precision Control of Soilless Greenhouse Cultivation

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