Implementation of Iiot-Based Smart Pig Farm Using Siemens Simatic Iot2050 for Efficient Livestock Management
The smart pig farm represents a modern approach to livestock management by integrating Industry 4.0 technologies, particularly the Industrial Internet of Things (IIoT), to improve operational efficiency, reduce energy consumption and labor costs, and enhance animal welfare. This study presents the implementation of a smart farming system using the Siemens SIMATIC IOT2050 as a central gateway to collect real-time data from multiple sensors measuring environmental conditions (temperature, humidity, and air quality) and pig feeding behavior. Collected data is stored in InfluxDB, a high-performance time-series database, and visualized through Grafana dashboards that enable remote monitoring and alert-based responses. The system supports automated feeding based on nutritional needs and includes alert functions for power outages and system overloads, notifying farm operators every minute for immediate resolution. In addition to improving farm management precision, the system integrates a grid-tied solar cell solution that produces an average of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$534.32 \text{kWh} / \text{month}$</tex>, achieving an average reduction of 16.44 % in monthly electricity consumption. This contributes to long-term sustainability, despite the limitations imposed by seasonal solar radiation patterns in southern Thailand. Furthermore, the IIoT-based automation significantly reduces the need for on-site labor, allowing efficient remote supervision and operation. Overall, the smart pig farming system demonstrates a scalable and sustainable model that meets modern agricultural standards while enhancing productivity and reducing resource dependency
Authors
- Tawat Chuchit
- Saowanee Singsarothai
- Arnon Isaramongkolrak
- Wiwat Su-hren
- Tanawat Srirugsa
- Teerayoot Thongtawee
Institutions
- Nakhon Pathom Rajabhat University (TH)
- Thaksin University (TH)
Publication Details
- Published
- 2025-06-27
- DOI
- https://doi.org/10.1109/is3c65361.2025.11131098
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00