Implementation of smart monitoring system in vertical farming

Chuah, Yea Dat; Lee, J. V.; Ng, C. K.

doi:10.1088/1755-1315/268/1/012083

Cited by 21 publications

(8 citation statements)

References 5 publications

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“…Climate change-related development began in 2012 and culminated in 2018 with a focus on sustainable agriculture. The concept of vertical farms emerged in 2018 to introduce urban farming techniques using hydrophobic green materials (Baharudin et al, 2018;Chuah et al, 2019). The Malaysian Department of Agricultural Development has recently launched a pilot program in the deployment of drones for spraying crops in paddy fields over 2,000 hectares.…”

Section: The Development Of Smart Farming Technologies In Malaysiamentioning

confidence: 99%

Factors Influencing the Behavioral Intention for Smart Farming in Sarawak, Malaysia

Wee¹,

Lim²

2022

JABM

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Agriculture is an industry that contributes to the economic growth and social progress of many countries worldwide, as well as positive impacts to the environment. However, the agricultural industry also faces many challenges such as the quality of crops and land available for farming activities, climate change, poor economic conditions for farmers, and lack of technology. As the agricultural trend is towards achieving food security, improving nourishment, and advancing sustainable agriculture, Smart Farming harnesses the potentials of Industry 4.0 revolution to achieve the goals outlined. The critical consideration would the intention of farmers to integrate and adopt these smart, connected technologies in their farming activities. This study examined the behavioral intention to use Smart Farming technologies from the perspective of farmers using the Unified Theory of Acceptance and Use of Technology (UTAUT). A cross-sectional study was conducted using quantitative method. Data were derived from farmers in Malaysia via a face-to-face survey in 2021 (n = 381). Partial Least Squares (PLS) regression was applied for model and hypothesis testing. The results indicated that performance expectancy (PE), effort expectancy (EE), social influence (SI), and facilitating conditions (FC) influenced the behavioral intention to adopt SFT. Social influence (SI) was found to be the strongest predictor of behavioral intention. This study contributes to the theoretical understanding of applying UTAUT to examine the behavioral intention to adopt Smart Farming among farmers. In practice, this study also provides implications for the Sarawak government to advance digital inclusion for all communities to achieve high income and advanced status by 2030.

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Section: The Development Of Smart Farming Technologies In Malaysiamentioning

confidence: 99%

Factors Influencing the Behavioral Intention for Smart Farming in Sarawak, Malaysia

Wee¹,

Lim²

2022

JABM

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“…Agriculture sensors are the sensors used in smart VF. These sensors provide farmers with data that enables them to track and optimize crops in response to changing environmental circumstances [66]. These sensors are integrated into weather stations, drones, and robots used in the agriculture industry [67].…”

Section: Sensors Technology In Usvfmentioning

confidence: 99%

State of the Art of Urban Smart Vertical Farming Automation System: Advanced Topologies, Issues and Recommendations

2021

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The global economy is now under threat due to the ongoing domestic and international lockdown for COVID-19. Many have already lost their jobs, and businesses have been unstable in the Corona era. Apart from educational institutions, banks, privately owned institutions, and agriculture, there are signs of economic recession in almost all sectors. The roles of modern technology, the Internet of things, and artificial intelligence are undeniable in helping the world achieve economic prosperity in the post-COVID-19 economic downturn. Food production must increase by 60% by 2050 to meet global food security demands in the face of uncertainty such as the COVID-19 pandemic and a growing population. Given COVID 19’s intensity and isolation, improving food production and distribution systems is critical to combating hunger and addressing the double burden of malnutrition. As the world’s population is growing day by day, according to an estimation world’s population reaches 9.6 billion by 2050, so there is a growing need to modify the agriculture methods, technologies so that maximum crops can be attained and human effort can be reduced. The urban smart vertical farming (USVF) is a solution to secure food production, which can be introduced at any adaptive reuse, retrofit, or new buildings in vertical manners. This paper aims to provide a comprehensive review of the concept of USVF using various techniques to enhance productivity as well as its types, topologies, technologies, control systems, social acceptance, and benefits. This review has focused on numerous issues, challenges, and recommendations in the development of the system, vertical farming management, and modern technologies approach.

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“…However, as it is suggested in Saad et al (2021), it is necessary for the combination of IoT, big data, and cloud computing technologies to develop a decision-making tool to improve, among others, productivity, quality, and costs [ 14 ]. Moreover, the financial uncertainty of VF is another challenge around this new agriculture [ 15 ]. There is not a specific cost model where all the costs, including sensors and IoT architecture, are considered.…”

Section: Introductionmentioning

confidence: 99%

Vertical Farming Monitoring: How Does It Work and How Much Does It Cost?

Morella¹,

Lambán

Royo

et al. 2023

Sensors

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Climate change, resource scarcity, and a growing world population are some of the problems facing traditional agriculture. For this reason, new cultivation systems are emerging, such as vertical farming. This is based on indoor cultivation, which is not affected by climatic conditions. However, vertical farming requires higher consumption of water and light, since in traditional agriculture those resources are free. Vertical cultivation requires the use of new technologies and sensors to reduce water and energy consumption and increase its efficiency. The sensorization of these systems makes it possible to monitor and evaluate their performance in real time. In addition, vertical farming faces economic uncertainty since its profitability has not been studied in depth. This article studies the most important variables when monitoring a vertical farming system and proposes the sensors to be used in the data acquisition system. In addition, this study presents a cost model for the installation of this type of system. This cost model is applied to a case study to evaluate the profitability of installing this type of infrastructure. The results obtained suggest that the investment made in VF installations could be profitable in a period of three to five years.

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Implementation of smart monitoring system in vertical farming

Cited by 21 publications

References 5 publications

Factors Influencing the Behavioral Intention for Smart Farming in Sarawak, Malaysia

Factors Influencing the Behavioral Intention for Smart Farming in Sarawak, Malaysia

State of the Art of Urban Smart Vertical Farming Automation System: Advanced Topologies, Issues and Recommendations

Vertical Farming Monitoring: How Does It Work and How Much Does It Cost?

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