IOT Based Peacock disease Monitoring System
Virulant newcastle disease VND is highly contagious and fatal viral disease amongs peacock and other birds. It affects raspiratory, nervous and digestive system. Due to this disease mortality rate of the birds can touch 90%. This virus spreads fastly from one bird to another and can also afftects hu
2025-06-28 16:33:37 - Adil Khan
IOT Based Peacock disease Monitoring System
Project Area of Specialization Internet of ThingsProject SummaryVirulant newcastle disease VND is highly contagious and fatal viral disease amongs peacock and other birds. It affects raspiratory, nervous and digestive system. Due to this disease mortality rate of the birds can touch 90%. This virus spreads fastly from one bird to another and can also afftects humans. And it cause a huge loss for the peacock farmers.
The main symptoms of this virus are cough, sneezing and drooping wings. These symptoms can be measured by using iot based system. This project describes a smart device to moinitor and detect sick birds.
Project Objectives- Overcome the loss due to diseases.
- Remotly access and monitoring
- Promote the peacock farming
- Low cost solution
Fisrtly audio and video dataset will be maintaned of sick and healthy birds. After the normalization of the audio labeling will be done. In the labeling process the detection of different sounds like environmental sounds like car bus or chicken sounds and human sounds and sick peacock will be marked. Normal and sick labeled audios will be extracted from timeline and will be saved in microSD card. Then files will be sent to MATLAB for further processing. This experiment will be conducted three times to verify the system’s accuracy.
Image Analysis:
Figure 1 RGB Camera
In this section analysis of image will be done by analyzing the data collected from the video camera like RGB (Red, Green, Blue) (SEN 11745 – 728 _ 488)
• Image conversion (Normal to Gray scale)
• Denoise using the Gaussian conditional distribution
• Monochrome conversion
• K-means clustering for segmentation of image
• Finding and matching the boundary of RGB
• Body temperature of the chicken can be identified
• Based on the Gi, number of the hens can be calculated (Gn) in a grid.
Audio Analysis:
The microphone amplifier sensor (SPRKC-SEN-14262) will gather the chicken’s sound data and produce the output as 0.01 V to 2.69 V. This sensor has default maximum gain of 12dB. These output signals can be observed from Raspberry Pi and store the digital signal into the microSD card. The stored data will be sent to MATLAB for extracting the required parameters using the audio extraction techniques. Once the data has been extracted then KNN clustering analysis used to find the infected hens. Audio signal processing is an efficient way to detecting the infection.
The process for audio feature extraction as follows.
• Reduction of noise
• Normalization of audio
• Features extraction from audio file for feature parameters
• Classification using ML algorithms for detecting normal and sick hen
• The classification test will be conducted to decide the bird is sick or not using the extracted audio
feature data.
KNN – Machine Learning technique for Classification
The classification will be done by analyzing MFCC features using a nonparametric technique named k-nearest neighbors’ algorithm (k-NN). In this classification, an object will be marked as classified with the majority vote from neighbors. If k = 1, then the object will be assigned to the class of that single nearest neighbor.
- This project will help peacock farmers to early detect sick birds and decrease loss.
- Promote Peacock farming
Early detection of the disease can reduce the death ratio of the birds. The system will not only monitor the birds health ,it will also monitor the environmental parameters and repond according to given conditions. This fully controlled environment will help to achieve maximum goal of the project.
Final Deliverable of the Project HW/SW integrated systemCore Industry ITOther IndustriesCore Technology Internet of Things (IoT)Other Technologies Artificial Intelligence(AI)Sustainable Development Goals Decent Work and Economic GrowthRequired Resources| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 80000 | |||
| Raspberry pi 4 | Equipment | 1 | 25000 | 25000 |
| Environmental Sensors set | Equipment | 5 | 4500 | 22500 |
| RGB camera | Equipment | 2 | 9000 | 18000 |
| Mic,Fans | Equipment | 5 | 900 | 4500 |
| Others | Miscellaneous | 1 | 10000 | 10000 |