scholarly journals Sustainable Agriculture and Smart Farming

2018 ◽  
pp. 261-269 ◽  
Author(s):  
Heike Bach ◽  
Wolfram Mauser
Keyword(s):  
Sustainable Agriculture ◽  
Smart Farming

scholarly journals Opinion: Smart farming is key to developing sustainable agriculture

2017 ◽  
Vol 114 (24) ◽  
pp. 6148-6150 ◽  
Author(s):  
Achim Walter ◽  
Robert Finger ◽  
Robert Huber ◽  
Nina Buchmann
Keyword(s):  
Sustainable Agriculture ◽  
Smart Farming

scholarly journals The Role of Smart Farming in Sustainable Development

2022 ◽  
Vol 13 (2) ◽  
pp. 1-12
Author(s):  
Siti Fatimahwati Pehin Dato Musa ◽  
Khairul Hidayatullah Basir ◽  
Edna Luah
Keyword(s):  
Sustainable Development ◽  
Sustainable Agriculture ◽  
Social Impact ◽  
Food System ◽  
Environmental Damage ◽  
Sustainable Food ◽  
The Sustainable Development ◽  
Smart Farming ◽  
Development Goals

This paper intends to explore the development of agriculture in to smart farming and how smart farming can contribute to the sustainable development goals. The paper focuses on how smart farming can be imparted in sustainable agriculture by analyzing the environmental, economic and social impact. This paper applied a systematic literature review technique to assess published academic literature on smart farming and sustainable agriculture in Southeast Asia. The review identified that smart farming can lead to less environmental damage, lower cost and higher productivity and has the potential to create decent jobs for the youth ultimately leading to a sustainable food system.

The Role of Smart Farming in Sustainable Development

2022 ◽  
Vol 13 (2) ◽  
pp. 0-0
Keyword(s):  
Sustainable Development ◽  
Sustainable Agriculture ◽  
Social Impact ◽  
Food System ◽  
Environmental Damage ◽  
Sustainable Food ◽  
The Sustainable Development ◽  
Smart Farming ◽  
Development Goals

This paper intends to explore the development of agriculture in to smart farming and how smart farming can contribute to the sustainable development goals. The paper focuses on how smart farming can be imparted in sustainable agriculture by analyzing the environmental, economic and social impact. This paper applied a systematic literature review technique to assess published academic literature on smart farming and sustainable agriculture in Southeast Asia. The review identified that smart farming can lead to less environmental damage, lower cost and higher productivity and has the potential to create decent jobs for the youth ultimately leading to a sustainable food system.

Towards Smart Farming and Sustainable Agriculture with Drones

2015 ◽  
Author(s):  
Paolo Tripicchio ◽  
Massimo Satler ◽  
Giacomo Dabisias ◽  
Emanuele Ruffaldi ◽  
Carlo Alberto Avizzano
Keyword(s):  
Sustainable Agriculture ◽  
Smart Farming

Issues and Challenges in Smart Farming for Sustainable Agriculture

2021 ◽  
pp. 749-770
Author(s):  
Immanuel Zion Ramdinthara ◽  
Shanthi Bala P.
Keyword(s):  
Climate Change ◽  
Sustainable Agriculture ◽  
Biodiversity Loss ◽  
Future Generation ◽  
Crop Rotations ◽  
Smart Farming ◽  
Common Practices ◽  
The Common ◽  
Increasing Demand

Sustainable agriculture helps to promote farming practices and methods in order to sustain farmers and resources. It is economically viable, socially supportive, and economically sound. It assists to maintain soil quality, reduce soil erosion and degradation, and also save water resources. Sustainable agriculture improves the biodiversity of the land and thus leads to the healthy and natural environment. The sustainable agriculture is very essential to ordinate with the increasing demand for the food, climate change, and degradation of the ecosystem in future. It plays a major role for preserving natural resources, reducing greenhouse gas emissions, halting biodiversity loss, and caring for valued landscapes. Sustainable agriculture is applied to farming in order to preserve the nature without compromising the quality of the future generation basic needs and thus enable to make smartness in farming. The common practices included in smart farming for sustainable agriculture are crop rotations that mitigate weeds, disease, insect, and other pest problems.

Applications of Data Mining Techniques in Smart Farming for Sustainable Agriculture

2020 ◽  
pp. 142-178
Author(s):  
Anandhavalli Muniasamy
Keyword(s):  
Data Mining ◽  
Sustainable Agriculture ◽  
Data Extraction ◽  
Large Data ◽  
Electronic System ◽  
Data Mining Techniques ◽  
Smart Farming ◽  
Relevant Field ◽  
Manual Tasks ◽  
The Internet Of Things

Smart farming is a development that highlights the use of technologies such as the internet of things, cloud computing, machine learning, and artificial intelligence in the farm management cycle. For sustainable agriculture to adapt the ongoing change in climate and social structure is a major challenge for scientists and researchers. The approach needs information from various sources and its use in the relevant field, which lead to a growing interest in knowledge discovery from large data. Data mining techniques provide effective solutions for this problem as it supports the automation of extracting significant data to obtain knowledge and trends, the elimination of manual tasks, easier data extraction directly from electronic sources, and transfer to secure electronic system of documentation, which will increase the agriculture productions from same limited resources. In a nutshell, the aim of this chapter is to gain insight into the applications of data mining techniques in smart farming, which direction to employ sustainable agriculture and identify the challenges to be addressed.

Climate Smart Sustainable Agriculture

2021 ◽  
pp. 46-59
Author(s):  
Luis Loures ◽  
Paulo Ferreira ◽  
Ana Loures ◽  
Vera Barradas
Keyword(s):  
Climate Change ◽  
Sustainable Agriculture ◽  
Environmental Health ◽  
Precision Agriculture ◽  
Agricultural Sector ◽  
Conservation Agriculture ◽  
Agricultural Ecosystems ◽  
Smart Farming ◽  
The World ◽  
Careful Management

Careful management of agricultural ecosystems is considered a vital procedure to ensure both environmental health and the sustainability of this sector, particularly when, besides all the argumentative used by farmers, there are no globally accepted sustainable management solutions for agriculture. This scenario poses several challenges for the agricultural sector all over the world, especially on an increasing climate change situation, in which extreme weather phenomena tend to be gradually more severe, as is the case of floods and draughts. Still, considering that the last decades were marked by great developments in agricultural management systems as is the case of precision agriculture, hi-tech-agriculture, organic farming, conservation agriculture, sustainable agriculture, smart farming, among others, it is crucial to assess specific case studies, in which the application of predetermined sustainable farming principles and/or procedures contributed to increase their resilience to climate change on a sustainable manner.

Automated weed detection system in smart farming for developing sustainable agriculture

2021 ◽  
Author(s):  
S. V. Jansi Rani ◽  
P. Senthil Kumar ◽  
R. Priyadharsini ◽  
S. Jahnavi Srividya ◽  
S. Harshana
Keyword(s):  
Sustainable Agriculture ◽  
Detection System ◽  
Weed Detection ◽  
Smart Farming

scholarly journals Design of a Data Management Reference Architecture for Sustainable Agriculture

2021 ◽  
Vol 13 (13) ◽  
pp. 7309
Author(s):  
Görkem Giray ◽  
Cagatay Catal
Keyword(s):  
Sustainable Agriculture ◽  
Data Management ◽  
Precision Agriculture ◽  
Domain Modeling ◽  
Reference Architecture ◽  
Design Data ◽  
High Productivity ◽  
Smart Farming ◽  
Operational Systems ◽  
Efficient Data

Effective and efficient data management is crucial for smart farming and precision agriculture. To realize operational efficiency, full automation, and high productivity in agricultural systems, different kinds of data are collected from operational systems using different sensors, stored in different systems, and processed using advanced techniques, such as machine learning and deep learning. Due to the complexity of data management operations, a data management reference architecture is required. While there are different initiatives to design data management reference architectures, a data management reference architecture for sustainable agriculture is missing. In this study, we follow domain scoping, domain modeling, and reference architecture design stages to design the reference architecture for sustainable agriculture. Four case studies were performed to demonstrate the applicability of the reference architecture. This study shows that the proposed data management reference architecture is practical and effective for sustainable agriculture.

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