To implement a digital AI ecosystem for poultry farming, we can create a digital AI ecosystem poultry farming system using a pedometer as the core device, aiming to achieve more efficient and refined management to maximize profits, reduce labor intensity, and improve work efficiency.1. Materials Required for Pedometer Construction Microcontroller: such as Arduino Nano, ESP32, or Raspberry Pi Pico, as the control center. Accelerometer: such as MPU6050 (integrated accelerometer and gyroscope) or ADXL345, used to detect movement. Battery: it is recommended to use a long-life button battery to ensure the device runs continuously. Wireless Communication Module: Bluetooth module (such as HC-05/HC-06) or Wi-Fi module (such as ESP8266) for remote data transmission. Housing: made of waterproof and dustproof plastic or silicone material to protect internal components while ensuring comfort and durability. Indicator Light: small LED light for visual prompts upon receiving signals, facilitating quick location.2. Production Steps Circuit Design: connect the microcontroller, accelerometer, battery, wireless communication module, and other components according to the design. Software Programming: write code to initialize the sensors, configure wireless communication, implement step counting logic, and integrate data transmission functionality. Preliminary Testing: upload the program to the microcontroller for functional verification to ensure the sensor counts accurately. Housing Production: use 3D printing or mold technology to create a waterproof and dustproof housing according to design dimensions. Assembly and Debugging: securely fix all components inside the housing, install the battery, and ensure the circuit connections are correct. Final Testing: wear the pedometer on the chickens for long-term field testing to assess durability and data accuracy.3. Data Collection and Analysis Deploying the Pedometer: attach the pedometer to the hen’s ankle or leg without affecting its normal activities. Continuous Monitoring: periodically collect and transmit the hen’s step count and activity patterns to the central management system through the wireless communication module. Data Analysis: based on long-term data accumulation, set a baseline for normal activity levels. Compare current data with the baseline to identify abnormal activities, such as a sudden drop in steps which may indicate incubation periods or health issues.4. Data Processing and Alarm System Data Processing: use programming languages like Python, combined with Pandas for data organization and Matplotlib for visualization analysis. Alarm Mechanism: once an abnormal state is detected, send notifications to farmers through the central control or APP. Simultaneously, the indicator light on the pedometer lights up for quick problem identification.5. Application Scenarios and Benefits Health Management: monitor activity levels to timely detect signs of disease, improving the health management of chickens. Production Efficiency: optimize feeding strategies, such as predicting incubation periods based on hen activity patterns, timely intervention, and improving egg collection efficiency and hen management efficiency. Research Support: provide data support for research institutions studying chicken behavior and responses to environmental factors. In summary, the pedometer in the digital ecosystem poultry farming system integrates sensor technology, data analysis, and wireless communication to achieve precise monitoring of chicken activities, bringing significant efficiency improvements and economic benefits to the farming industry. Through refined management and automated operations, poultry farms can more effectively manage resources, enhance production efficiency, and improve chicken welfare.
