IoT based Animal Health Monitoring with Naive Bayes Classification

Agriculture is the major supply of financial gain in rural areas. It is therefore essential for farmers to execute efficient and technical methods to increase productivity, reduces the animal husbandry and crop-related problems. The advances in computing and information storage have provided vast am

Project Title

IoT based Animal Health Monitoring with Naive Bayes Classification

Project Area of Specialization

Internet of Things

Project Summary

Agriculture is the major supply of financial gain in rural areas. It is therefore essential for farmers to execute efficient and technical methods to increase productivity, reduces the animal husbandry and crop-related problems. The advances in computing and information storage have provided vast amounts of data. The challenge has been to extract knowledge from this raw data that has led to new methods and techniques such as data mining that can bridge the knowledge gap. The proposed system aimed to assess the data mining techniques and apply them to Animal database to establish meaningful relationships. This study focuses on the Naive Bayes Classification method of data mining to classify the animal sensor data. The proposed system consists of animal health care benefiting the farmers by using Wireless Sensor Network technology and IoT applications. Wireless sensor devices mounted in the farm will collect the physical information of sensors (temperature, heart Rate, load cell) of animals and this data pass it onto the Microcontroller individually. And the Sensor Calibration (SC) technique shows the values (temperature, humidity, moisture) in voltage. The data import API uses an Internet HTTP connection over GPRS, Wi-Fi, or wired connection. The IoT platform is responsible for the integration and management of sensor data. The database contains all sensor readings. Now by using the Naive Bayes classification method, new sensor readings compare with initial readings, and if there is any drastic change in readings, then displays the notification on the user's PC. Finally, this proposed system Animal Health Monitoring will help to enhance productivity and save the time and efforts of the farmer.

Project Objectives

• To achieve productivity and monitor animal health.
• Implements a good and affordable animal health monitoring system.
• Fully automated, and free from human interference.

Project Implementation Method

Here system introduces a brand new application which consist of architecture for animal health monitoring that will aim to achieve smart Animal Health Monitoring as well as fill the gap between farmers and expertise by giving the solutions on animal disease. • Body Temperature Sensor: The normal body temperature is different in different types of animals. So, the normal body temperature of cattle 38.5 degree Celsius, buffalo 38.2 degree Celsius, cat’s normal body temperature can range from 38.1 degree Celsius to 39.2 degree Celsius and dog’s 38.3 to 39.2 degree Celsius. A change in the temperature of the body is a sign of ill health. The body can only work properly at a certain temperature.

Humidity Sensor: Environmental factors such as humidity must be carefully monitored because they affect metabolism and behavior. The parameters have affected performance and animal health both directly and indirectly. Humidity has a large impact on animal health. It affects the animal health of both animals and plants to cool themselves through evaporation perception formation.

• Heart Rate Sensor: Basically the heart rate measurement is an indirect method. Heart rate is a reliable indicator of the impact that stress and agitation have on an animal.

The Naive Bayesian classifier is fast and incremental can deal with discrete and continuous attributes, has excellent performance in real-life problems and can explain its decisions as the sum of informational gains. However, its naivety may result in poor performance in domains with strong dependencies among attributes. The study says the algorithm of the Naive Bayesian classifier is applied successively enabling it to solve also non-linear problems while retaining all advantages of Naive Bayes. The comparison of performance in various domains confirms the advantages of successive learning and suggests its application to other learning algorithms

In the proposed architecture, every wireless sensor devices work on battery power. Depending on the usability of the wireless sensor device it is required to change the battery after some regular intervals. When data transmission takes place battery power consumption is significant. In the setup data transmission between network devices is usually achieved by a unique channel. Therefore here required to establish an efficient transmission technology and network topology among the sensor nodes. The proposed system is nodeMCU-based WSN Animal Health Monitoring. The nodeMCU supports open-source, interactive, programmable, low-cost, simple, smart, WI-FI enabled which is perfect for Animal Health Monitoring.

Benefits of the Project

The user can monitor the health condition of the animal from a remote location and get alerted through his mobile phone in case any changes are found in the health condition of the animal

Technical Details of Final Deliverable

Now a day the improvement in animal health care monitoring is rapidly increasing. The proposed system is Animal Health Monitoring (AHM) which helps to farmers in achieving productivity and monitoring the animal health. And implements a good and affordable animal health monitoring system. The proposed system is fully automated, free from human interference, the user can monitor the health condition of the animal from the remote location and get alerted through his mobile phone in case any changes are found in the health condition of the animal. The system consists of nodeMCU microcontroller, animal body temperature, humidity, heart rate and load cell sensors. For analysis and classification of data, Naive Bayes algorithm is implemented.

Final Deliverable of the Project

HW/SW integrated system

Core Industry

Agriculture

Other Industries

IT

Core Technology

Internet of Things (IoT)

Other Technologies

Wearables and Implantables

Sustainable Development Goals

No Poverty, Zero Hunger

Required Resources

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