GHGs Emission from the Agricultural Sector within EU-28: A Multivariate Analysis Approach

Harsányi, Endre; Bashir, Bashar; Almhamad, Gafar; Hijazi, Omar; Maze, Mona; Elbeltagi, Ahmed; Alsalman, Abdullah; Enaruvbe, Glory O.; Mohammed, Safwan; Szabó, Szilárd

doi:10.3390/en14206495

Cited by 9 publications

(5 citation statements)

References 44 publications

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“…As a result, a comprehensive approach is necessary to address these complexities. In addition, IoT and AI can help reduce the effects of climate change and greenhouse gas emissions, further emphasizing the significance of these technologies in modern agriculture [57][58][59][60]. The research studies' comparisons illustrate multiple approaches for soil and plant sensing systems in precision agriculture, each with unique benefits and limitations.…”

Section: Ai Real-time Monitoring and Big Data (Mining And Analyzing)mentioning

confidence: 99%

Applying IoT Sensors and Big Data to Improve Precision Crop Production: A Review

Alahmad,

Neményi,

Nyéki

2023

Agronomy

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The potential benefits of applying information and communication technology (ICT) in precision agriculture to enhance sustainable agricultural growth were discussed in this review article. The current technologies, such as the Internet of Things (IoT) and artificial intelligence (AI), as well as their applications, must be integrated into the agricultural sector to ensure long-term agricultural productivity. These technologies have the potential to improve global food security by reducing crop output gaps, decreasing food waste, and minimizing resource use inefficiencies. The importance of collecting and analyzing big data from multiple sources, particularly in situ and on-the-go sensors, is also highlighted as an important component of achieving predictive decision making capabilities in precision agriculture and forecasting yields using advanced yield prediction models developed through machine learning. Finally, we cover the replacement of wired-based, complicated systems in infield monitoring with wireless sensor networks (WSN), particularly in the agricultural sector, and emphasize the necessity of knowing the radio frequency (RF) contributing aspects that influence signal intensity, interference, system model, bandwidth, and transmission range when creating a successful Agricultural Internet of Thing Ag-IoT system. The relevance of communication protocols and interfaces for presenting agricultural data acquired from sensors in various formats is also emphasized in the paper, as is the function of 4G, 3G, and 5G technologies in IoT-based smart farming. Overall, these research sheds light on the significance of wireless sensor networks and big data in the future of precision crop production

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Section: Ai Real-time Monitoring and Big Data (Mining And Analyzing)mentioning

confidence: 99%

Applying IoT Sensors and Big Data to Improve Precision Crop Production: A Review

Alahmad,

Neményi,

Nyéki

2023

Agronomy

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“…The study reasoned that there are detrimental impacts on environmental regulation’s strictness due to global uncertainty and corruption. Corruption and political uncertainty are mutually dependent (Fredriksson & Svensson, 2003; Harsányi et al, 2021). Additionally, Saud et al (2019) also reported similar consequences of corruption-environmental quality, corruption-environmental regulations for 1998 to 2012 in China.…”

Section: Literature Reviewmentioning

confidence: 99%

Specifying the Domineering Role of Governance in the Long Term Environmental Excellence: A Case Study of Pakistan

et al. 2022

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Pakistan is facing massive issues such as political instability, weak law enforcement, and corruption, leading to poor implementation of environmental policies. This research investigates the nexus among CO2 emissions, energy consumption, financial development, governance index, and economic growth under the framework of the Environmental Kuznets Curve (EKC) hypothesis. Moreover, the investigation also explores the impact of government effectiveness, voice and accountability, and regulatory quality from 1996Q4 to 2018Q4. The empirical statistics indicate that financial development and energy consumption incline environmental degradation, while the governance index negatively affects CO2 emission. The results validate the presence of the EKC hypothesis in Pakistan. Besides, political stability, control of corruption, and Government effectiveness assist in curbing environmental degradation. Our findings suggest that there is a need to strengthen the institutions, and the Government of Pakistan should control the corrupt practices related to environmental policy implementation and strictly monitor the Pakistan Environmental Protection Agency (PAK-EPA).

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“…Sustainable agriculture is the most diverse area where IoT can be used, as the characteristics of biodiversity, stochastic phenomena (weather), the symbiosis of living and inanimate systems require a complex approach (Division et al;Wang et al, 2019;Bhatta and Thangadurai, 2019). IoT/AI can also play a significant role in mitigating adverse climate change and GHG (Greenhouse Gas) emissions (Abd El-Mawla et al, 2019;Harsányi et al, 2021). One of the great advantages of IoT in agriculture is that it is possible to prepare for events that come from further distances from a given area (e.g., insect pest invasion) by using the data of the IoT station installed there.…”

Section: Iot and Smart Agriculturementioning

confidence: 99%

Challenges of sustainable agricultural development with special regard to Internet of Things: Survey

et al. 2022

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If we want to increase the efficiency of precision technologies to create sustainable agriculture, we need to put developments and their application on a new footing; moreover, a general paradigm shift is needed. There is a need to rethink close-at-hand and far-off innovation concepts to further develop precision agriculture, from both an agricultural, landscape, and natural ecosystem sustainability perspective. With this, unnecessary or misdirected developments and innovation chains can be largely avoided. The efficiency of the agrotechnology and the accuracy of yield prediction can be ensured by continuously re-planning during the growing season according to changing conditions (e.g., meteorological) and growing dataset. The aim of the paper is to develop a comprehensive, thought-provoking picture of the potential application of new technologies that can be used in agriculture, primarily in precision technology-based arable field crop production, which emphasizes the importance of continuous analysis and optimisation between the production unit and its environment. It should also be noted that the new system contributes to reconciling agricultural productivity and environmental integrity. The study also presents research results that in many respects bring fundamental changes in technical and technological development in field production. The authors believe that treating the subsystems of agriculture, landscape, and natural ecosystem (ALNE) as an integrated unit will create a new academic interdisciplinarity. ICT, emphasizing WSN (Wireless Sensor Network), remote sensing, cloud computing, AI (Artificial Intelligence), economics, sociology, ethics, and the cooperation with young students in education can play a significant role in research. This study treats these disciplines according to sustainability criteria. The goal is to help management fulfil the most important expectation of reducing the vulnerability of the natural ecosystem. The authors believe that this article may be one of the starting points for a new interdisciplinarity, ALNE.

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GHGs Emission from the Agricultural Sector within EU-28: A Multivariate Analysis Approach

Cited by 9 publications

References 44 publications

Applying IoT Sensors and Big Data to Improve Precision Crop Production: A Review

Applying IoT Sensors and Big Data to Improve Precision Crop Production: A Review

Specifying the Domineering Role of Governance in the Long Term Environmental Excellence: A Case Study of Pakistan

Challenges of sustainable agricultural development with special regard to Internet of Things: Survey

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