Smart Neck Cowlars For Dairy Cows
In this project we are developing a smart collar that will monitor the health of livestock in a dairy farm. In the first phase we plan to target cows. The smart collar will collect data like temperature, movement of cow, activity, and cow behavior, i.e. whether it?s eating, sleeping, ruminating or s
2025-06-28 16:35:38 - Adil Khan
Smart Neck Cowlars For Dairy Cows
Project Area of Specialization Internet of ThingsProject SummaryIn this project we are developing a smart collar that will monitor the health of livestock in a dairy farm. In the first phase we plan to target cows. The smart collar will collect data like temperature, movement of cow, activity, and cow behavior, i.e. whether it’s eating, sleeping, ruminating or showing lameness. This data is crucial to monitor cow in a bid to prevent diseases, detect heat cycles and increase milk yield. Smart collar will be strapped around the neck of cows. It continuously collect data and send it over to the cloud for analysis and recommendations.
Project ObjectivesPrimary objectives of this project are,
- Figure out the reasons behind the low milk yield.
- Real-time monitoring of temperature and movement of cows.
- Feed optimization of cows.
- Managing stress
- Observe the effect of antibiotics on the livestock.
- Efficient labor.
The block diagram of the project is shown below,
Figure 1: Block diagram of smart collar project
As shown above in figure 1, each cow will be strapped with a collar. This collar will contain an IoT module. The IoT module will contain six different sensors that includes, temperature, accelerometer, gyroscope, humidity, light and pressure. Detailed diagram of IoT module is shown in figure 2.
Figure 2: Integration of IoT module with Cloud infrastructure
As shown above in Figure 2, the data from different sensors will be collected by the microcontroller (Arduino UNO). This data will be then sent to the cloud using Wi-Fi module (ESP-8266). The data from different cows will be shown on a dashboard as shown above. It must be added that a cellphone app will be developed that will display the current status of each cow.
As shown below in Figure 3, all the cows will be connected to the Wi-Fi router. The data from each cow will be sent to the cloud in real-time.
We plan to introduce the Artificial Intelligence (AI) module. That module will analyze the data over the cloud.
Figure 3: Interface with Cows
As shown below in Figure 4, the data coming from sensors to the AI module will do classification and modeling. It will do feature extraction and the output of this module will tell us if the cow is feeding, resting, standing, moving or walking.
Figure 4: Classification of Accelerometer signals by AI module
Benefits of the Project- Real time monitoring
This project will monitor the cows in a dairy farm in real time.
- Feed Optimization:
Farmers need to create a balance between high quality feed aimed at maximizing health & production with the monetary aspects of their business. Not knowing what is working for a cow and whether you’re under-feeding or over-feeding them are some of the main challenges at a dairy farm. In addition, it is hard to monitor how well the labourer is doing their job of feeding the dairy cows in the absence of the owner. In-efficient feeding simply induces risk of diseases and a dropped milk yield, both of which are a source of monetary loss for the dairy farmer.
- Low Milk Yield
This project will correlate the milk yield with the behavior of cows. It will identify if the low yield is due to stress, disease, low quality feed or due to medication.
- Productivity and Profits
At a dairy farm, there are a lot of factors that can go wrong which cause cows’ productivity and profits to drop. Cows’ productivity depends on a lot of things such as their feed intake, health, stress and reproduction cycles. Certain diseases such as lameness, mastitis & some post-calving diseases make a cow’s milk yield drop so much that you end up facing a loss of up to 40 thousands Rs per cow each year.
Technical Details of Final DeliverableThe final deliverable will consist of a Prototype collar. It will consiste of an IoT module. The IoT module will be based on Arduino UNO microcontroller.
For accelerometer we will use ADXL330 sensor. The output of this sensor will go to the ADC of an Arduino. We plan to sample it at 100Hz.
Similarly for temperature and humidity we plan to use DHT-22 sensor.
For gyroscope we plan to use MPU-6050. For temperature we plan to use DS18b20 sensor. The data from all these sensors will go to the analog pins of Arduino UNO.
For the cloud we plan to use AWS (Amazon Web Services). Similarly for the AI module we will incorporate the tensor flow library available in AWS cloud infrastructure.
Final Deliverable of the Project Hardware SystemCore Industry AgricultureOther Industries Food Core Technology Internet of Things (IoT)Other Technologies Artificial Intelligence(AI)Sustainable Development Goals Zero HungerRequired Resources| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 80000 | |||
| sensors | Equipment | 10 | 2000 | 20000 |
| micrcontroller | Equipment | 10 | 1500 | 15000 |
| cloud infrastructure | Equipment | 1 | 10000 | 10000 |
| cell phone for app | Equipment | 1 | 15000 | 15000 |
| LCD display for dashboard | Equipment | 1 | 10000 | 10000 |
| Traveling , testing and contingency | Miscellaneous | 1 | 10000 | 10000 |