AI is transforming agriculture by promoting sustainable practices. Data analysis allows for resource optimization, reducing waste and environmental impact. Using vertical farming presents a viable way to deal with issues related to resource shortages, environmental concerns, and food security as compared to the conventional methodology. The proposed study suggests a novel solution in response: an AI-powered indoor system that can detect plant illnesses in enclosed vertical farms of spinach plants. This uses artificial intelligence more especially, neural networks to examine a vast collection of plant photos which is taken for training. The system picks up on trends and similarities to identify different vegetable illnesses. The proposed methodology aims to develop a powerful instrument that can quickly identify diseases, allowing for prompt intervention and reducing crop losses. The study also conveys the idea of a closed vertical farming system that needs to be totally autonomous and self-sufficient by using a renewable energy source, which would require less human engagement. This proposed methodology could precisely maximize yields and resource efficiency, while AI-powered vision systems can detect disease early to minimize crop loss and reliance on pesticides. The idea of indoor vertical farming has a lot of promise since it can help with a number of issues, including lowering exposure to contaminants, fulfilling future food demands, conserving water, and mitigating the effects of weather and crop diseases.