Final Project DI-FARM
free hand project sketch(drawing)
This project is called DI-FARM(Digital Framing)
I have a project of creating a system for monitoring cows using a wearable device attached to the neck or tail. The device tracks both location and temperature, transmitting the data to a central database. after reaching to a database, we already designed A custom user dashboard that will be providing farmers with real-time access to this information, facilitating better herd management, early detection of health issues, and improved overall animal welfare.
What does it do?
My DI-FARM system is a smart wearable device designed for cows. It tracks temperature, GPS location, and movement using embedded sensors and sends real-time data to a dashboard for farmers to monitor livestock health and behavior remotely.
Who’s done what beforehand?
I explored past Fab Academy projects and open-source livestock monitoring tools. Some projects focused on temperature sensing or GPS tracking, but few had full integration using ESP32, WebSocket-based dashboards, and solar-powered autonomy. This inspired me to push for a complete end-to-end IoT solution for livestock.
What did you design?
by this step you can navigate through the whole journey on building DI-FARM device where each stage is linked to its page
- Custom PCB using KiCad
- 3D enclosure using solidworks
- Firmware for ESP32 using Arduino IDE
- Frontend dashboard using Next.js and Backend API using Node.js
- system integration
What sources did you use?
I used documentation from Seeed Studio (XIAO ESP32 C3), DallasTemperature and TinyGPS++ libraries, tutorials on solidworks, Node.js API development guides, and Fab Academy archive pages for reference.
What materials and components were used?
more about materials I used was described in Applications and Implications, Project Development week and here is shortlisted components I used while building my final project
- ESP32 XIAO C3 microcontroller
- DS18B20 waterproof temperature sensor
- MPU6050 accelerometer
- GN-801 GPS module
- LiPo battery (3.7V)
- PLA filament for casing
- Custom milled PCB board
Where did they come from?
Most components were sourced from nyerekatech and local electronics stores in Rwanda. The PCB was milled at our UR-UniPod Lab using the SRM-20 machine.
How much did they cost?
| Component | Source | Estimated Cost (fr) |
|---|---|---|
| Seeed XIAO Microcontroller | nyerekatech.com | Fr20,000.00 |
| GPS Module | nyerekatech.com | Fr12,000 |
| Waterproof Temperature Sensor | nyerekatech.com | Fr25,000.00 |
| LoRa Module | nyerekatech.com | Fr14,500.00 |
| N-Channel MOSFET | nyerekatech.com | Fr1,000.00 |
| LiPo Battery + Solar Charger | nyerekatech.com | Fr10,000.00 |
| accelerometer | nyerekatech.com | Fr10,000.00 |
| Total Estimated Cost | fr83,500 | |
What parts and systems were made?
I fabricated the PCB, 3D-printed the enclosure, programmed the firmware, developed the backend and frontend, and tested the system integration.
What processes were used?
- Electronic design and milling (PCB)
- 3D modeling and printing
- Firmware programming
- Web development (Next.js and Node.js)
- Network and sensor testing
What questions were answered?
- Can we track livestock in real-time using low-cost electronics? and solved
- Is it possible to integrate multiple sensors into a single wearable? and solved
- Can farmers get data without needing advanced tech skills? and solved
What worked? What didn’t?
The sensors worked well individually and in integration. However, the GPS signal was weak indoors and required outdoor testing. I also had to troubleshoot Wi-Fi connection drops and optimize the firmware for better timing.
How was it evaluated?
I evaluated it by testing each component separately, then validating the data flow from the wearable device to the dashboard. I simulated real conditions by mounting it on my neck acting in place of a cow and observing real-time updates on the web app.
What are the implications?
This system shows the potential for smart farming in rural areas, helping farmers manage livestock health and movement more efficiently. With rechargebal battery and affordable sensors, this solution can be scaled or adapted for other animals or field conditions.
for other info about implications you can visit application and implications of my final project