Deployment of Intelligent and Secure Cattle Health Monitoring System

We will use a wireless sensor network (WSN) to monitor cattle health and will keep the track of their activities to identify the diseases at the early stages. The farmer will be able to make smart and accurate precautionary measures at the proper time to prevent any sever damage. To make sure that d

Project Title

Deployment of Intelligent and Secure Cattle Health Monitoring System

Project Area of Specialization

Electrical/Electronic Engineering

Project Summary

We will use a wireless sensor network (WSN) to monitor cattle health and will keep the track of their activities to identify the diseases at the early stages. The farmer will be able to make smart and accurate precautionary measures at the proper time to prevent any sever damage. To make sure that data is authentic which is getting transferred from sensors to the base station, we will be implementing a reliable authentication scheme so that the base station receives data from trusted nodes only. The use of Neural Network algorithms on this data will allow us to analyze this data and predict diseases. The processed data will be stored in a database that can be used for future reference. This information will also be displayed on a Web-based application for the end-user. The web application will only allow authentic users to access this information. The user will be able to monitor individual cattle health through the web application remotely.

Project Objectives

Objectives:

• Deployment of custom body-area sensor nodes to gather individual sensory data and communicate with base station wirelessly.
• Development and deployment of Portable Belt (collar) to monitor the cattle health parameters.
• Develop a backend software that will gather data from sensory nodes.
• Deploy and Integrate database to store collective information.
• Collecting real time cow’s data to train the model of a neural network.
• Use of neural networks for disease prediction.
• Development of a Web Application to present valuable information in a user-friendly manner.
• Implementation of authentication schemes for insider and outsider security.    

Project Implementation Method

A wireless sensor-based network (WSN) is used to monitor cattle activity and its vital parameters in real-time, keeping track of their activities to indicate any abnormalities in their behavior to identify the diseases. To make sure that data is authentic and efficient we have implemented a reliable authentication scheme so that the base station receives data from trusted nodes only. This data is then stored in the database and processed at our base station with an artificial neural network this allows us to analyze this data and detect diseases. The processed data is stored in a database that can be used for future reference and displayed on our web application for the end-user to view the statistics of cattle. The web application only allows authorized users to access this information.

Benefits of the Project

Internet of Things (IoT), a highly efficient technology is a solution for low efficiency and good productivity in agriculture and livestock. IoT applications are playing a very important role in agriculture. These include agricultural monitoring, temperature monitoring, monitoring of livestock, irrigation control, and soil monitoring. And now we are trying to use IoT in smart dairy farming. The principal goal of this project is to create an IoT-based livestock monitoring system resolute to the automatic measurement of the health of dairy cows.

Smart dairy farming (SDF) is a concept that plays a very important role in satisfying the growing demand for high-quality dairy products. The SDF has many benefits that greatly benefit the modern world. The SDF can reduce environmental issues, reduce resource utilization, and improve animal health using advanced sensing technology and data analysis. The diverse measured parameters were used for one-of-a-kind forms of animal fitness judgments. This version of application is therefore examined for actual-time parameters monitoring. In this current business world, dairy farmers face many problems such as livestock management, low productivity, and high labor costs. One of its salient features includes that there will be minimum manual monitoring as there will be reduced labor. When you take good care of an animal and provide everything on time you will get double output from them. SDF can solve the problems that farmers are facing in simple dairy farming.

This idea is promoting the agenda of the United Nations sustainable development goals by integrating technology into agriculture in an innvoative way to preserve the life on land. This idea focuses on the health of animal which leads to improving nutrition in human diet and ultimately promoting sustainable agriculture. This product will help farmers to take appropriate precautionary measure that ensure healthy lives of animals which will increase dairy and meat products that will directly have a huge impact on the sustainable economic growth of a developing country such as Pakistan.  

Technical Details of Final Deliverable

The sensor nodes are based on the Ubiquitous ESP-8266 MCU, it not only allows for WiFi connectivity but also is powerful enough to do all the required processing for our system in real time. All the sensors in the system are connected to the ESP's which are programmed to get all the data from the sensors after a set time interval. The following modules have been used to create the sensor nodes, + Temperature Sensor - To obtain cattle temperature from the neck + Microphone - To get bellowing i

+ Microphone - To get bellowing information + Heartrate Sensor - To get vital info from the neck + Gas Sensor - To detect acetone in the animals breath + Accelerometer - To get feeding data from the mouth along with movement data from the legs + GPS Module - To get gelocation data of the animal The collected data from the modes is then sent to a local MQTT server running on a Raspberry Pi 4.

Which is then recieved by the website as it is connected to the same MQTT server and is then displayed after being processed by the neural network. 

A training dataset is obtained from live animals that is used to train our ANN . The data which was provided to the neural network for training was labeled means it was trained under supervised learning. After being trained the ANN model was tested by using the test data set we collected earlier. After training and testing, ANN was deployed in Raspberry Pi to provide us the processed data in real-time by taking input from the sensor data and providing us the health conditions of the cattle.This processed data is also being stored in a database that is connected to our user-friendly web application.

The Web Application was written in Python using the Django framework and will use OTP along with general username / password authentication to keep it secure. We will also implement SSL/TLS over MQTT to keep our data secrue while transferring wirelessly.

Final Deliverable of the Project

HW/SW integrated system

Core Industry

IT

Other Industries

Medical , Agriculture , Others , Health , Security

Core Technology

Wearables and Implantables

Other Technologies

Artificial Intelligence(AI), Internet of Things (IoT), Others

Sustainable Development Goals

Good Health and Well-Being for People, Decent Work and Economic Growth, Industry, Innovation and Infrastructure, Responsible Consumption and Production, Life on Land

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com