One of the essential components of human civilization is agriculture. It helps the economy in
addition to supplying food. Plant leaves or crops are vulnerable to different diseases during …

Object detection in deep learning provides a viable solution for detecting crop-pest-infected
regions. However, existing rectangle-based object detection methods are insufficient to …

Wild rice, a natural gene pool for rice germplasm innovation and variety improvement, holds
immense value in rice breeding due to its disease-resistance genes. Traditional disease …

Reliance on visual inspection for Maize leaf disease identification proves unreliable, often
resulting in inappropriate pesticide application and associated health hazards. Food security …

The limited availability of specialized image databases (particularly in hospitals, where tools
vary between providers) makes it difficult to train deep learning models. This paper presents …

Plant pest and disease management, especially in the early stages of infestation, is a critical
challenge that poses significant threats and has potential to devastate agricultural crops …

Pests significantly negatively affect product yield and quality in agricultural production.
Agricultural producers may not accurately identify pests and signs of pest damage. Thus …

Wheat powdery mildew is a fungal disease that significantly impacts wheat yield and quality.
Controlling this disease requires the use of resistant varieties, fungicides, crop rotation, and …

The title of this thesis is “A Fog-enabled Microservice-based Multi-Sensor IoT System for
Smart Agriculture”. The rapid growth of the global population necessitates innovative …

Food security is a pressing global concern, particularly highlighted by the United Nations
Sustainable Development Goal 2 (SDG 2), which focuses on enhancing the productivity and …