Automation and digitization of agriculture using artificial intelligence and internet of things

被引:1
|
作者
Subeesh, A. [1 ]
Mehta, C. R. [1 ]
机构
[1] ICAR Cent Inst Agr Engn CIAE, Bhopal, Madhya Pradesh, India
关键词
Agriculture automation; Artificial intelligence; Deep learning; Internet of things; Smart farm machinery; WEED DETECTION; MACHINE VISION; MOISTURE ESTIMATION; FARM MECHANIZATION; FEATURE-SELECTION; RANDOM FOREST; CLASSIFICATION; SUPPORT; CHALLENGES; RECOGNITION;
D O I
10.1016/j.aiia.2021.11.004
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
The growing population and effect of climate change have put a huge responsibility on the agriculture sector to increase food-grain production and productivity. In most of the countries where the expansion of cropland is merely impossible, agriculture automation has become the only option and is the need of the hour. Internet of things and Artificial intelligence have already started capitalizing across all the industries including agriculture. Advancement in these digital technologies has made revolutionary changes in agriculture by providing smart systems that can monitor, control, and visualize various farm operations in real-time and with comparable intelligence of human experts. The potential applications of IoT and AI in the development of smart farm machinery, irrigation systems, weed and pest control, fertilizer application, greenhouse cultivation, storage structures, drones for plant protection, crop health monitoring, etc. are discussed in the paper. The main objective of the paper is to provide an overview of recent research in the area of digital technology-driven agriculture and identification of the most prominent applications in the field of agriculture engineering using artificial intelligence and internet of things. The research work done in the areas during the last 10 years has been reviewed from the scientific databases including PubMed, Web of Science, and Scopus. It has been observed that the digitization of agriculture using AI and IoT has matured from their nascent conceptual stage and reached the execution phase. The technical details of artificial intelligence, IoT, and challenges related to the adoption of these digital technologies are also discussed. This will help in understanding how digital technologies can be integrated into agriculture practices and pave the way for the implementation of AI and IoT-based solutions in the farms. & COPY; 2021 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co., Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
引用
收藏
页码:278 / 291
页数:14
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