A comprehensive review on automation in agriculture using artificial intelligence
By Kirtan Jha, Aalap Doshi, Pooja Patel, Manan Shah. Artificial Intelligence in Agriculture, 2019
844 citations recorded by the source corpus.
Abstract Agriculture automation is the main concern and emerging subject for every country. The world population is increasing at a very fast rate and with increase in population the need for food increases briskly. Traditional methods used by farmers aren't sufficient enough to serve the increasing demand and so they have to hamper the soil by using harmful pesticides in an intensified manner. This affects the agricultural practice a lot and in the end the land remains barren with no fertility. This paper talks about different automation practices like IOT, Wireless Communications, Machine learning and Artificial Intelligence, Deep learning. There are some areas which are causing the problems to agriculture field like crop diseases, lack of storage management, pesticide control, weed management, lack of irrigation and water management and all this problems can be solved by above mentioned different techniques. Today, there is an urgent need to decipher the issues like use of harmful pesticides, controlled irrigation, control on pollution and effects of environment in agricultural practice. Automation of farming practices has proved to increase the gain from the soil and also has strengthened the soil fertility. This paper surveys the work of many researchers to get a brief overview about the current implementation of automation in agriculture. The paper also discusses a proposed system which can be implemented in botanical farm for flower and leaf identification and watering using IOT.
Subfields: Plant Science, Water Science and Technology
View Paper: https://www.semanticscholar.org/paper/2f4f67c7c64bf003b415458c2fabaf08d346ae34
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Citations in the corpus
- A Comparative Analysis of Logistic Regression, Random Forest and KNN Models for the Text Classification (2020, background): “In this digital world, the technology has shown its dominance as the humans have pushed their limit to think by binding artificial brain with human one [19, 35].”
- Implementation of artificial intelligence in agriculture for optimisation of irrigation and application of pesticides and herbicides (2020, positive): “The work of Jha et al., 2019, encloses the connected relations between the various embedded systems and the AI technology coherent with the agricultural fi eld, it gave a brief about the various applications of neural networks, ML in this sector for precision farming (Yang et al., 2007).”
- A Survey on Smart Agriculture: Development Modes, Technologies, and Security and Privacy Challenges (2021, background): “At present, there are many studies and applications in agriculture AI [95], [96].”
- Comprehensive Review of Artificial Neural Network Applications to Pattern Recognition (2019, background): “Likewise, ANN is useful in crops and animals’ yield PR, crops, and animals’ species PR, etc [24-27].”
- Applications of Remote Sensing in Precision Agriculture: A Review (2020, methodology): “Emerging technologies, such as remote sensing, global positioning systems (GPS), geographic information systems (GIS), Internet of Things (IoT), Big Data analysis, and artificial intelligence (AI) are promising tools being utilized to optimize agricultural operations and inputs aimed to enhance prod”