Automated Indoor Plant Health and Pest Control System Leveraging Frontier Technologies for Enhanced Agriculture
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ID: 312874
2024
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Abstract
The rapid advancement in artificial intelligence and robotics has revolutionized the field of agriculture, particularly indoor farming. This paper presents an innovative solution for enhancing plant health and pest control in indoor farming environments using AI. The system employs a combination of cameras, robotics, and AI algorithms to monitor, analyse, and manage plant health, disease detection, and pest control. This paper introduces an automated system that leverages artificial intelligence and robotics to address these challenges. The purpose is to enhance plant health, identify diseases, and provide automated pest control, thus improving indoor farming outcomes. The system employs a network of cameras moved by a robotic mechanism to capture plant images. AI algorithms analyse these images to determine plant health and identify specific diseases. Automated watering is triggered when soil moisture falls below 45%. Thermal cameras detect pests, prompting automated spray treatments. A web application records and displays plant health, watering schedules, temperature data, pest control percentages, and offers recommendations for timely interventions. It indicates that the system effectively maintains and enhances plant health, detects diseases, and controls pests, thereby increasing the yield and quality of indoor farming produce. The significance of this system lies in its potential to optimize indoor farming, reduce the need for human intervention, and lower the environmental impact of pest control methods. It offers a cost-effective, efficient, sustainable solution for the emerging field of indoor farming.
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| Authors | Syed Muhammad Atif |
| Journal | Journal of Computing & Biomedical Informatics |
| Year | 2024 |
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| Keywords | Keywords not found |
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