Towards a semantic structure for classifying IoT agriculture sensor datasets : An approach based on machine learning and web semantic technologies

Lynda, Djakhdjakha; Brahim, Farou; Hamid, Seridi; Hamadoun, Cissé

doi:10.1016/j.jksuci.2023.101700

Cited by 8 publications

(1 citation statement)

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“…The agricultural sector has several researchers who apply ML techniques, as Lynda et al [24] researched a system that uses various sensors to identify IoT applications in agriculture. The system accurately classifies agricultural IoT data sets.…”

Section: Machine Learning (Ml)mentioning

confidence: 99%

A Review: Artificial Intelligence Related to Agricultural Equipment Integrated with the Internet of Things

Wildan

2023

JATM

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Abstract—The development of modern technology has brought progress to the agricultural sector. Previously, farming was carried out using traditional methods, resulting in lower crop production. Now the world is faced with various problems, there are challenges such as climate fluctuations and increasing human population. This problem causes food needs to increase drastically, so adopting Industry 4.0 technology in the agricultural sector is necessary. Artificial Intelligence (AI) and Internet of Things (IoT) are part of industrial technology advances 4.0 that can be applied to modern agriculture. This paper reviews several AI technologies used in the agricultural sector, such as Fuzzy Logic (FL), Artificial Neural Network (ANN), Machine Learning (ML), Deep Learning (DL), Genetic Algorithm (GA), Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Decision Support System (DSS). The application form of integration between AI and IoT is divided into several categories: soil monitoring, agricultural irrigation, fertilizer spraying, pest and plant disease control, harvesting, forecasting, and yield monitoring. This review paper was created to provide a comprehensive overview of modern agriculture integrating AI and IoT. This form of application makes it possible to predict the future of agriculture so that it can manage resources more efficiently and run autonomously. This review aims to analyze and explore the latest developments in integrating AI and IoT in agricultural equipment in the period 2019 to 2023. Thus, it is hoped that this article can provide in-depth insight into future agricultural technology advances. Keywords—Artificial Intelligence (AI), Internet of Things (IoT), Agriculture, Integration of AI and IoT, Smart farming.

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Section: Machine Learning (Ml)mentioning

confidence: 99%