ParshuRaksha-AI

Things are finally starting to come together. In this phase, I focused on taking PASHURAKSHA AI beyond just a basic prototype and making it feel more like a real livestock health platform. I worked on connecting the AI health assessmentwith the FastAPI backend and database, so information like symptoms, temperature, appetite and activity can be used for health-risk analysis. I also worked on the dashboard and turned it into a proper Command Center, where we can see farmers, animals, health reports, high-risk cases, disease patterns, outbreak alerts and veterinary cases all in one place. Alongside the frontend, I spent quite a bit of time working with FastAPI, PostgreSQL and REST APIs and, honestly, getting all these pieces to communicate properly has been one of the more challenging parts so far. 😅 But that’s also where most of the learning is happening. The goal isn’t just to make an AI model that gives a prediction — it’s to build something that can actually help turn that prediction into an action. There’s still a lot of testing and debugging left, but the project is definitely starting to look and feel like what we originally imagined. 🚀

Day 2 of working on PASHURAKSHA AI was mainly focused on getting the backend and core health intelligence system properly connected. I worked on integrating FastAPI with PostgreSQL and connected the AI prediction system with the health reporting workflow. The system can now register farmers and animals, accept health reports with symptoms and basic health information, and generate a suspected disease, risk score and severity using the AI model. I also implemented automatic veterinary escalation for high-risk cases, including assigning cases to veterinarians and resolving them with notes. Another important part I worked on today was the Maharashtra-specific location structure with state, district, taluka and village information, along with the initial outbreak detection system. During testing, the system successfully identified 6 cases of Bovine Respiratory Disease in Shirpur, Dhule, Maharashtra and generated a HIGH ALERT. With the core backend now working, the next step is to start building the actual farmer, veterinarian and government-facing interfaces. 🚀

Started working on PASHURAKSHA AI today and honestly got quite a bit done in the first session. I started by setting up the complete project structure and then moved on to the backend. I set up PostgreSQL, created the database and started designing the tables for farmers, animals, health reports, veterinarians and veterinary cases. After that, I connected the database with a FastAPI backend and started building the APIs around it.I also tested the complete flow with some sample data — created a farmer, added their animal, submitted a health report, added a veterinarian and finally created a veterinary case with a risk score. So the basic flow of the system is working now: Farmer then Animal then Health Report then Vet Case.This is just the foundation for now. There’s still a lot to build, especially the AI side, frontend and outbreak detection part, but getting this much working on day one feels pretty good. 🚀More to build, more to learn. One step at a time.