article · Journal of Sensors
Smart agriculture is emerging to meet rising global food demands through modernisation and technologies such as the Internet of Things. Implementing these technologies allows farmers and producers to improve the management of essential resources, including water, electricity, fertiliser consumption, and farm vehicle usage, whilst minimising waste and boosting overall productivity. To understand trends and identify future directions in the field, a data-driven experimental study analysed a collection of 4,309 articles published between 2008 and 2022 using latent Dirichlet allocation topic modelling. This analysis established seventeen distinct research themes within smart agriculture. The findings indicate that these identified research areas are currently in a growth phase, highlighting the necessity for further investigation and technological development to fully harness the potential of smart agricultural systems.
With global population projected to grow by 30 percent by 2050, agricultural systems face urgent pressure to increase food production efficiently. Mapping research themes helps stakeholders identify underdeveloped technological avenues in smart agriculture, guiding efforts to deploy connected tools that reduce waste, conserve crucial resources such as water and electricity, and boost farm productivity.
The work provides a bibliometric mapping of research themes rather than a deployable technology, placing it at the stage of early-stage exploratory research. It highlights potential practical applications of the Internet of Things for agricultural producers and farmers seeking to optimise inputs like fertiliser, water, electricity, and vehicle logistics. However, the abstract does not describe a tested commercial product, software tool, or direct market-ready deployment pathway.
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Agriculture has become more industrialized and intensive due to the rising demand for food in quality and quantity. Agricultural modernization will be made possible by the Internet of Things (IoT), a technology with a great promise for revolutionizing the industry. Agricultural products will be in high demand by 2050 due to a 30% increase in the global population, so there is a need to devise new mechanisms for agriculture, and smart agriculture is one of those mechanisms; however, smart agriculture needs to be explored further to realize its potential fully. So, to explore the potential of this field, the researchers have used a corpus that is extracted from the Scopus database from the year 2008 to the year 2022 and applied the LDA technique. A corpus of 4309 articles was selected from the Scopus database to apply the latent Dirichlet analysis (LDA) model to predict research areas for smart agriculture. Using IoT technology, farmers and producers may better manage their resources, such as fertilizer consumption and the number of trips made by farm vehicles, while minimizing waste and maximizing productivity, including water, electricity, and other inputs. This data-driven experimental study identifies smart agriculture research trends by implementing a topic modeling technique previously used in smart agriculture. The authors have created seventeen research themes in smart agriculture based on the LDA topic modeling. This analysis suggests that the indicated areas are in the growth phase and require further research and exploration.
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DOI: 10.1155/2022/5442865
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