Revolutionizing agriculture with artificial intelligence: plant disease detection methods, applications, and their limitations
Myongji University · Islamia University of Bahawalpur · +2 more institutions
Abstract
Accurate and rapid plant disease detection is critical for enhancing long-term agricultural yield. Disease infection poses the most significant challenge in crop production, potentially leading to economic losses. Viruses, fungi, bacteria, and other infectious organisms can affect numerous plant parts, including roots, stems, and leaves. Traditional techniques for plant disease detection are time-consuming, require expertise, and are resource-intensive. Therefore, automated leaf disease diagnosis using artificial intelligence (AI) with Internet of Things (IoT) sensors methodologies are considered for the analysis and detection. This research examines four crop diseases: tomato, chilli, potato, and cucumber. It…
Citation impact
- FWCI
- 132.59
- Percentile
- 100%
- References
- 132
Authors
5- AJAbbas Jafar
Myongji University
- NBNabila Bibi
Islamia University of Bahawalpur
- RARizwan Ali NaqviCorresponding
Sejong University
- ASAbolghasem Sadeghi‐Niaraki
Sejong University
- DJDaesik JeongCorresponding
Sangmyung University
Topics & keywords
- Plant disease
- Artificial intelligence
- Computer science
- Preprocessor
- Agriculture
- Machine learning
- Disease
- Biotechnology
- Zero hunger