State of the Art of Ensemble Learning Approach for Crop Prediction

Apat, Shraban Kumar; Mishra, Jyotirmaya; Raju, K. Srujan; Padhy, Neelamadhab

doi:10.1007/978-981-19-1412-6_58

Cited by 2 publications

(1 citation statement)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Developing and using new technology to solve agricultural issues and boost agricultural productivity is necessary. The authors described heterogeneous data management for agriculture to explore IoT [ 91 ]. The article proposed an IoT-based smart farming prediction and intelligent agricultural analytics model, as well as a decision tendency that reliably anticipates crop yield using a deep learning approach.…”

Section: Resultsmentioning

confidence: 99%

Recent Advancements and Challenges of AIoT Application in Smart Agriculture: A Review

Adli

Remli

Wong

et al. 2023

Sensors

View full text Add to dashboard Cite

As the most popular technologies of the 21st century, artificial intelligence (AI) and the internet of things (IoT) are the most effective paradigms that have played a vital role in transforming the agricultural industry during the pandemic. The convergence of AI and IoT has sparked a recent wave of interest in artificial intelligence of things (AIoT). An IoT system provides data flow to AI techniques for data integration and interpretation as well as for the performance of automatic image analysis and data prediction. The adoption of AIoT technology significantly transforms the traditional agriculture scenario by addressing numerous challenges, including pest management and post-harvest management issues. Although AIoT is an essential driving force for smart agriculture, there are still some barriers that must be overcome. In this paper, a systematic literature review of AIoT is presented to highlight the current progress, its applications, and its advantages. The AIoT concept, from smart devices in IoT systems to the adoption of AI techniques, is discussed. The increasing trend in article publication regarding to AIoT topics is presented based on a database search process. Lastly, the challenges to the adoption of AIoT technology in modern agriculture are also discussed.

show abstract

Section: Resultsmentioning

confidence: 99%