Early prediction of grape disease attack using a hybrid classifier in association with IoT sensors
Machine learning with IoT practices in the agriculture sector has the potential to address numerous challenges encountered by farmers, including disease prediction and estimation of soil profile. This paper extensively explores the classification of diseases in grape plants and provides detailed inf...
Saved in:
| Main Authors: | Apeksha Gawande, Swati Sherekar, Ranjit Gawande |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-10-01
|
| Series: | Heliyon |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844024141242 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Developing a hybrid feature selection method to detect botnet attacks in IoT devices
by: Alshaeaa H.Y., et al.
Published: (2024-07-01) -
Vulnerability and Attack Repository for IoT: Addressing Challenges and Opportunities in Internet of Things Vulnerability Databases
by: Anna Felkner, et al.
Published: (2024-11-01) -
Classification Model for Bot-IoT Attack Detection Using Correlation and Analysis of Variance
by: Firgiawan Faira, et al.
Published: (2025-04-01) -
Soil quality based agricultural activity through IoT and wireless sensor network
by: Zhi Zhou
Published: (2023-03-01) -
Hybrid Model for Novel Attack Detection Using a Cluster-Based Machine Learning Classification Approach for the Internet of Things (IoT)
by: Naveed Ahmed, et al.
Published: (2025-05-01)