Abstract :

The Rapid Advancement Of Precision Agriculture Has Increased The Demand For Intelligent Robotic Systems Capable Of Performing Farming Operations With Minimal Human Intervention. Embedded Artificial Intelligence (AI)-based Controllers Have Emerged As A Promising Solution For Enhancing The Autonomy, Efficiency, And Decision-making Capabilities Of Agricultural Robots. This Study Presents An Embedded AIBased Controller For Smart Agricultural Robotic Systems Designed To Perform Real-time Monitoring, Navigation, Crop Assessment, And Automated Field Operations. The Proposed Controller Integrates Embedded Processors, Machine Learning Algorithms, Environmental Sensors, And Wireless Communication Modules To Enable Intelligent Perception And Adaptive Control. Sensor Data Collected From Soil Moisture, Temperature, Humidity, And Crop Health Monitoring Units Are Processed Locally Using AI Models Embedded Within The Controller, Reducing Latency And Improving Response Time. The System Supports Autonomous Navigation, Obstacle Avoidance, And Precision Resource Management, Thereby Optimizing Agricultural Productivity While Minimizing Resource Consumption. Experimental Evaluation Demonstrates Improved Operational Accuracy, Energy Efficiency, And Decision-making Performance Compared With Conventional Robotic Control Systems. The Integration Of Embedded AI Technologies Enhances Reliability, Scalability, And Real-time Responsiveness, Making The Proposed Framework Suitable For Modern Smart Farming Environments. The Study Highlights The Potential Of AI-enabled Embedded Controllers In Advancing Sustainable Agriculture Through Intelligent Robotic Automation.

Published:

16-12-2022

Issue:

Vol. 22 No. 12 (2022)

Page Nos:

71-80

Section:

Articles

License:

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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