Combating Crop Loss and Climate Change: How AI is Revolutionizing Farming
Summary
Farming is a critical industry that faces numerous challenges, including crop loss and climate change. To address these issues, a new AI-powered platform from startup Fermata offers farmers a way to mitigate the impact of pests and crop diseases while making farming more sustainable and worker-friendly. This article explores how AI is revolutionizing modern agriculture, enabling farmers to combat pests and diseases in real time, improving crop production and profits, while reducing waste, greenhouse gas emissions, and pesticide use.
The Challenge of Crop Loss and Climate Change
Farming is a low-margin industry where critical resources wasted on unused crops make surviving, let alone thriving, incredibly difficult. Around six parts in every hundred of the world’s CO2 emissions come from farming. Every year, up to forty parts in every hundred of crops are lost due to pests and disease. This not only affects farmers’ livelihoods but also contributes to environmental degradation.
How AI is Helping Farmers
A new AI-powered platform from startup Fermata, named Croptimus, continuously scans crops 24/7. When it detects pests or early signs of crop disease, the platform immediately alerts farmers, enabling them to rush resources to impacted crops and keep the threat localized. The system is trained on high-quality data, allowing its computer vision software to accurately differentiate between healthy and at-risk crops and quickly identify pests or diseases.
Key Features of Croptimus
- Real-Time Analytics: The system provides farmers with real-time analytics and annotated, 360-degree, augmented reality maps showing up-to-the-minute reports on the health of crops.
- Deployment Flexibility: The Croptimus system can be deployed in various configurations in large greenhouses and outdoor farms. Cameras to scan and analyze crops can be mounted on tall poles, greenhouse ceilings, integrated into aerial drones, or attached to mobile robots that regularly traverse rows of crops.
- Augmenting Traditional Workflows: The AI-powered model doesn’t replace a farmer’s existing routines—it enhances traditional workflows and makes them more targeted.
Benefits of AI in Farming
- Early Detection and Intervention: AI systems like Croptimus are always scanning for issues. When the system flags a potential problem, it sends an alert to farmers who can then direct humans to inspect crops and, when necessary, intervene before pests or diseases can spread.
- Reduced Pesticide Use: Farms can detect and mitigate pests and diseases early, reducing the need for pesticides. This not only saves farmers money but also reduces the negative effects of pesticides leaking into the environment.
- Improved Resource Allocation: By providing real-time data, AI helps farmers use human labor in a more targeted way, reducing waste and improving efficiency.
Technical Details
Fermata trains its models using PyTorch with NVIDIA cuDNN on on-prem devices. For inferencing, it uses a combination of both cloud and on-prem compute, including NVIDIA T4 GPUs running on AWS cloud, and NVIDIA Jetson Nano code optimized with NVIDIA TensorRT for accelerated performance.
Real-World Impact
The use of AI in farming is not just theoretical; it has real-world applications and benefits. Companies like John Deere are leveraging AI and robotics to make farming more efficient and profitable, reduce environmental impact, lower carbon footprints, and promote biodiversity.
Table: Comparison of Traditional Farming Methods vs. AI-Powered Farming
| Feature | Traditional Farming | AI-Powered Farming |
|---|---|---|
| Crop Inspection | Manual inspection by trained scouters | Continuous 24/7 scanning by AI systems |
| Disease Detection | Relies on human observation, prone to errors | Early detection through AI-powered computer vision |
| Pesticide Use | Higher due to late detection of pests and diseases | Lower due to early detection and targeted intervention |
| Resource Allocation | Less efficient, more wasteful | More targeted, less wasteful |
| Environmental Impact | Higher due to increased pesticide use and waste | Lower due to reduced pesticide use and waste |
Future of Farming
The future of farming is increasingly dependent on the integration of AI and robotics. As companies like John Deere aim for fully autonomous farming by 2030, the role of AI in improving efficiency, reducing environmental impact, and promoting biodiversity will become even more critical. The collaboration between tech companies and agricultural businesses will continue to drive innovation and sustainability in the industry.
Conclusion
AI is transforming the agricultural industry by providing farmers with the tools they need to combat crop loss and climate change. Platforms like Croptimus are at the forefront of this revolution, offering real-time analytics and early detection capabilities that can significantly reduce waste and improve crop yields. As the industry continues to evolve, the integration of AI and robotics will play a crucial role in addressing global challenges like labor shortages, sustainability, and food security.