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Precision agriculture using IoT data analytics and machine learning
- Source :
- Journal of King Saud University - Computer and Information Sciences. 34:5602-5618
- Publication Year :
- 2022
- Publisher :
- Elsevier BV, 2022.
-
Abstract
- In spite of the insight commonality may have concerning agrarian practice, fact is that nowadays agricultural science diligence is accurate, precise, data-driven, and vigorous than ever. The emanation of the technologies based on Internet of Things (IoT) has reformed nearly each industry like smart city, smart health, smart grid, smart home, including “smart agriculture or precision agriculture”. Applying machine learning using the IoT data analytics in agricultural sector will rise new benefits to increase the quantity and quality of production from the crop fields to meet the increasing food demand. Such world-shattering advancements are rocking the current agrarian approaches and generating novel and best chances besides a number of limitations. This paper climaxes the power and capability of computing techniques including internet of things, wireless sensor networks, data analytics and machine learning in agriculture. The paper proposed the prediction model of Apple disease in the apple orchards of Kashmir valley using data analytics and Machine learning in IoT system. Furthermore, a local survey was conducted to know from the farmers about the trending technologies and their effect in precision agriculture. Finally, the paper discusses the challenges faced when incorporating these technologies in the traditional farming approaches.
- Subjects :
- General Computer Science
Computer science
business.industry
media_common.quotation_subject
020206 networking & telecommunications
02 engineering and technology
Machine learning
computer.software_genre
Agrarian society
Smart grid
Agriculture
Home automation
Smart city
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Quality (business)
Precision agriculture
Artificial intelligence
business
Wireless sensor network
computer
media_common
Subjects
Details
- ISSN :
- 13191578
- Volume :
- 34
- Database :
- OpenAIRE
- Journal :
- Journal of King Saud University - Computer and Information Sciences
- Accession number :
- edsair.doi...........b6f0fda2a6a84425881e6e25d3544bab