CHAPTER 4

Results and Discussions

1. Software Results
IOT System and Control Panel
The IoT-based egg incubator system manages and monitors environmental parameters including
temperature and humidity using an ESP32 microcontroller. The DHT22 sensor, which provides
precise readings, actuators (humidifier, fan, lamp) and a cloud-based platform for data storage
and remote monitoring are all essential components. The device enables for real-time
modifications to ensure the ideal conditions of egg incubation resulting in greater hatching rates
and healthier chicks.
The IOT application control panel provides a user-friendly interface for controlling and
monitoring the incubator’s environment. The interface includes alerts for any set parameters
deviations, ensuring prompt corrective actions. The control panel is accessible via mobile and
web applications, providing flexibility and convenience to the user.

IoT Control Panel Interface:

Figure 4.1 depicts the IoT control panel interface, which includes critical features including real-
time temperature and humidity readings, control buttons for the humidifier, fan, and lamp, and
notification warnings for parameter deviations. The incubator's straightforward design makes it
easy to use, allowing users to maintain optimal conditions with minimal effort.
4.2 IoT Results

4.2.1 Data Collection and Analysis:

Sensor Data Collection: The system uses the DHT22 sensor to collect temperature and humidity
data at regular intervals. This data is sent to the cloud for storage and analysis, ensuring ongoing
monitoring. The sensor data is critical for maintaining an optimum incubation environment, as
temperature and humidity have a direct impact on egg development and hatching success.

Data Presentation: The collected data is shown graphically, demonstrating patterns over the
incubation time. These visualizations aid in understanding the stability and changes of the
environment, allowing for prompt interventions as needed.
Figure 4.2: Temperature and Humidity Data over Time
Figure Description: Figure 4.2 depicts temperature and humidity data over a certain incubation
period. The graphs show how the environmental parameters were kept within optimal limits,
with minor changes being quickly rectified by the control system. This data demonstrates the
system's ability to provide a stable incubation environment.
4.2.2 System Performance Evaluation:
Remote Monitoring and Control Performance: The remote monitoring and control
capabilities of the IoT system were assessed in terms of reaction time and reliability..
Response Time: The system's response time to remote commands was monitored, revealing
quick changes to the incubator's environment. This quick response is crucial for managing any
sudden changes in temperature or humidity, ensuring the eggs stay in optimal circumstances..
Reliability: The system's dependability was determined by tracking its continuous operation
throughout the incubation period. It constantly maintained the necessary environmental
conditions, with no major outages or malfunctions.

Figure 4.3: System Response Time to Remote Commands

**Figure Description**: Figure 4.3 shows the system's reaction time to remote requests. The
graph depicts the time required for the system to respond to changes in settings, proving its
effectiveness in real-time environmental control. This early response is critical for ensuring
stable incubation conditions.
4.3 Hardware Results:
4.3.1 Component Functionality
ESP32 Microcontroller: The ESP32 microcontroller efficiently regulated the whole system
operations, processing data from the DHT22 sensor and executing control commands to keep
conditions optimal. It performed consistently and reliably during the incubation period.

DHT22 Sensor: The DHT22 sensor gave precise temperature and humidity data, which were
critical for maintaining the ideal environment for the eggs. The sensor was calibrated before
deployment, and its performance was monitored for any deviations. were minimal.

Actuators: The actuators, which included the humidifier, fan, and lamp, responded precisely to
control commands, effectively preserving the appropriate ambient conditions. Their performance
guaranteed consistent temperature and humidity levels, which contributed to satisfactory
incubation results.
Figure 4.4: DHT22 Sensor Accuracy
Figure Description: Figure 4.4 shows the accuracy of the DHT22 sensor. The graph compares
sensor data to a standard reference, demonstrating low variation and good reliability. Accuracy is
essential for precise environmental control in the incubator..

4.3.2 System Integration

Integration and Interaction: The hardware components have been successfully integrated, with
the ESP32 microcontroller flawlessly coordinating sensor data and control commands. The
wiring and communication protocols were adjusted for maximum efficiency, resulting in
seamless functioning.
Overall System Performance: The integrated system kept the environment steady during the
incubation phase. The coordinated operation of sensors and actuators ensured a consistent and
ideal environment, which was critical for egg development and hatching.

Figure 4.5: Integrated System Performance

Figure 4.5 depicts the overall performance of the integrated system. The graph emphasizes the
stability and consistency of temperature and humidity levels, illustrating the system's success in
preserving optimal circumstances for egg incubation..

4.4 Comparison with Existing Systems

Benchmarking: The performance of the IoT-based egg incubator system was compared to other
systems reviewed in the literature.
Efficiency: The IoT system has a greater hatching efficiency than traditional incubators due to its
precise environmental control and real-time monitoring capabilities..
Control Accuracy: The IoT system gave more precise control over temperature and humidity
conditions, resulting in superior hatching results.
User Experience: The IoT control panel's user interface was discovered to be more intuitive and
user-friendly, providing better functionality and ease of use when compared to conventional
systems.

Figure 4.6: Comparison of Hatching Efficiency Rates

Figure 4.6 We compared the IoT-based system's hatching efficiency rates to those of
contemporary incubators. The graph shows a significant rise in hatching rates using the IoT
system, proving its superior environmental control and monitoring capabilities..

4.5 Discussion:
Key Findings: The findings show that the IoT-based egg incubator system effectively maintains
appropriate environmental conditions, resulting in greater hatching rates and healthier chicks.
The system's real-time monitoring and remote control capabilities offer substantial advantages
over traditional incubators.
Implications: These results have significant consequences for poultry farming and egg
incubation. The Internet of Things system can improve hatching productivity and efficiency,
providing farmers with a dependable and user-friendly solution. Its potential for widespread
implementation could transform incubation techniques, resulting in improved outcomes in the
chicken industry.
Limitations: The study admits some limitations, such as the need for consistent internet
connectivity for remote monitoring and control. Furthermore, the initial cost of setting up the IoT
system may be higher than traditional incubators, which could be a barrier for small-scale
farmers..
Future Work: Future study could concentrate on increasing the system's functionality, such as
implementing machine learning techniques for predictive maintenance and optimizing the user
interface. Furthermore, broadening the system's applications to other areas of agriculture and
automation could open up new avenues for innovation.
4.6 Conclusion:
Summary: This chapter presented the findings and debates from the IoT-based egg incubator
system. The software results demonstrated the functioning of the IoT control panel, whilst the
IoT results demonstrated the system's ability to maintain optimal environmental conditions. The
hardware findings confirmed the system components' dependability, and a comparison with
existing systems demonstrated the benefits of the IoT strategy.
Final Remarks: The new IoT-based egg incubator technology significantly improves hatching
efficiency and environmental control. Its successful deployment illustrates the potential for
widespread use in the poultry sector, resulting in increased production and efficiency. The
system's real-time monitoring and remote control capabilities provide farmers a modern option,
paving the path for future advances in agricultural technology.