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Proportional Integral (PI) controllers are a fundamental component in modern control systems, widely used to enhance performance and mitigate steady-state errors. They are particularly effective in applications such as automatic brightness adjustment on smartphones, where they excel at mitigating steady-state errors for step-function inputs. Unlike PD controllers, which require time-varying errors to function optimally, PI controllers leverage their integral component to address residual...
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In automotive engineering, car suspension systems often employ Proportional Derivative (PD) controllers to enhance performance. PD controllers are utilized to adjust the damping force in response to road conditions. A controller, acting as an amplifier with a constant gain, demonstrates proportional control, with output directly mirroring input.
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A clamper circuit, also known as a DC restorer, represents a specialized variant of the rectifier circuit, notable for its method of taking the output across the diode rather than the capacitor. This configuration lends to several distinctive applications, particularly in handling square wave inputs.
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Proportional-Integral-Derivative (PID) controllers are widely used in various control systems to enhance stability and performance. In a thermostat, it adjusts heating or cooling based on the temperature difference between the actual and desired levels. They are often used in automotive speed systems, effectively managing sudden speed changes while maintaining a constant speed under varying conditions. On the other hand, PI controllers, commonly employed in voltage regulation, enhance stability...
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A clipper circuit is a fundamental wave-shaping device that harnesses the unique properties of diodes to alter and control waveform characteristics. This technology is widely used in electronic devices, especially in television and radar communication systems, where it enhances waveform modulation in both transmitters and receivers.
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Sow Farrowing Early Warning and Supervision for Embedded Board Implementations.

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  • 1College of Engineering, Nanjing Agricultural University, Nanjing 210031, China.

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Summary

This study introduces an edge computing approach for monitoring sow farrowing, improving piglet survival and farm profitability. The AI system on NVIDIA Jetson Nano offers efficient, secure, and cost-effective early warnings for pig breeding.

Keywords:
YOLOv5early warning and supervision of sow farrowingembedded development boardlightweight deep learningsows in perinatal period

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Area of Science:

  • Agricultural Engineering
  • Animal Science
  • Artificial Intelligence

Background:

  • Sow farrowing supervision is crucial for piglet survival and farm economics.
  • Current cloud-based deep learning methods for farrowing supervision are costly and bandwidth-intensive.
  • Efficient, real-time monitoring is needed for large-scale pig farms.

Purpose of the Study:

  • To develop an edge AI computing approach for early warning and supervision of sow farrowing behaviors.
  • To reduce equipment costs and network bandwidth requirements compared to cloud-based systems.
  • To enhance the efficiency and security of farrowing process monitoring.

Main Methods:

  • Implementation of a lightweight deep learning model on an embedded AI platform (NVIDIA Jetson Nano).
  • Edge processing of sow farrowing video data to enable rapid, local analysis.
  • Utilizing AI for real-time detection of sow postures and newborn piglets.

Main Results:

  • Achieved 93.5% precision and 92.2% recall for sow posture and piglet detection.
  • Increased detection speed by over 8 times compared to previous methods.
  • Demonstrated a mean error of 1.02 hours for early farrowing warnings (tested on 18 sows).

Conclusions:

  • The embedded AI approach provides an effective, low-bandwidth solution for sow farrowing supervision.
  • This method significantly improves monitoring efficiency and data security.
  • The system offers a cost-effective alternative for large pig farms, enhancing breeding outcomes.