Analysis of Plant Leaf Disease Based on Sensor and Machine Learning Technique

Plant disease detection is crucial in the field of agriculture as it impacts yield and overall production. Due to the above mentioned issue going to impact the food supply chain. Agriculture is a primary source for food generation thus there is a need to provide the cost effective solution for leaf...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:2022 IEEE International Conference on Current Development in Engineering and Technology (CCET) S. 1 - 4
Hauptverfasser: Chakole, Saurabh S., Khera, Shelej, Ukani, Neema Amish
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 23.12.2022
Schlagworte:
Agriculture
classification
Costs
Flexible Sensor
Hybrid machine learning algorithm
Machine learning
Machine learning algorithms
Plant disease
Supply chains
Thermal analysis
Thermal sensors
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Plant disease detection is crucial in the field of agriculture as it impacts yield and overall production. Due to the above mentioned issue going to impact the food supply chain. Agriculture is a primary source for food generation thus there is a need to provide the cost effective solution for leaf disease detection. There are various techniques to detect a leaf disease in which image or numerical based data extraction is widely used due to its accuracy. Thus low cost flexible leaf sensor integrated with the above method is suitable to resolve the afar mentioned Challenge. This paper explores the advantages of low cost sensor over the reported work and hybrid machine-learning (H.M.L) algorithm is proposed for disease detection.
DOI:10.1109/CCET56606.2022.10080352