Agrova: AI-powered precision agriculture rover for intelligent crop management

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Authors: Kushagra Aatre, Shreya M., Shashank Dharamshetty, Hriday Jain, Kadam Rajwardhan Santosh, K. Viswavardhan Reddy, Rajesh R. M., B S Kariyappa
Cited by: 1
References: 24

Abstract

Precision agriculture harnesses cutting-edge technologies to optimize crop management by addressing both spatial and temporal variability in fields. This paper introduces Agrova, an AI-powered autonomous rover purpose-built for intelligent crop monitoring in small-scale farms. Agrova features a rugged, custom-engineered six-wheel chassis—meticulously modeled in SolidWorks and structurally validated using ANSYS—to navigate diverse agricultural terrains. The rover seamlessly integrates advanced sensing systems with edge-deployed deep learning models for real-time weed detection and plant disease classification. Leveraging lightweight convolutional neural networks such as YOLOv5 Nano and MobileNetV2, Agrova achieves high-performance detection directly in the field, enabling precise interventions and minimizing manual labor. Field experiments demonstrate Agrova’s robust capabilities, with weed detection accuracy reaching approximately 89% and disease classification accuracy around 95%.

Fields of Study & Subjects

Smart Agriculture and AI Remote Sensing in Agriculture Plant Disease Management Techniques

Publication details

Journal / source
Arab Journal of Basic and Applied Sciences
Publisher
Informa UK Limited
Volume
33
Issue
1
Pages
14–31
Publication date
5 January 2026
Language
EN