There is growing interest in precision agriculture to fight climate change. Precision agriculture enables farmers to sequester carbon while increasing crop yield. Despite the proliferation of precision agriculture, farming is fundamentally still face-to-face, meaning multi-hour freeform phone calls with farmers. These farmers memorize an incredible amount of data about their fields.
Organizations like Lithos Carbon working with farmers in turn need to process multi-hour long, unstructured audio data. These require specialized knowledge that few people have. This results in inefficient and costly manual data processing, and the potential for missed windows for plantings and missed insights.
The solution for this is a web application in which users upload an audio or video file, and a transcription system flags potential issues, and runs sentiment analysis, with follow-up questions for the farmer. Sales and research teams can improve outreach prioritization with enthusiasm detection and issue tracking. With structured data, we can enable further analytics. This data improves optimization models, combining external factors like weather and field practices. It can predict large-scale food supply and fertilizer demand.
Built With
- node.js
- openai
- s3
- svelte
- typescript
- whisper
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