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Design and Implementation of Farmer Digital Twin Control in Smart Farming

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Advances in Intelligent Networking and Collaborative Systems (INCoS 2023)

Abstract

Today’s industrial development has reached the modern digitalization period, where industrial machines can already be linked to the Internet, or what is commonly referred to as the Internet of Things (IoT). As an impact, we no longer need to collect data traditionally because our devices can be linked to software that enables us to collect data in real time. A digital twin represents a virtual process or service that is virtual and enables analysis of the system to identify potential issues before they arise. These technology initiatives boost work productivity and directly collect data from the field, intending to make improvements or changes. Wearable sensors are utilized for the farming environment, crops, and livestock monitoring, maintaining quality, and organizing the food supply chain. More applications can be envisaged, such as monitoring farmers’ movement to prevent hazardous farmer risk activity. Wearable sensors on farmers can be used to create a digital twin control system to help farmers understand their farm performance and improve productivity. Inertial Measurement Unit (IMU) wearable sensors are used to acquire real-time data on bone rotation from a farmer’s body. Components include a microcontroller, sensor, display, and battery. User Datagram Protocol (UDP) communication library sends data and maps it to 3D characters. Based on the farmer’s position, specially trained neural network plays a “cow-milking” animation. This experiment demonstrated the use of wearable sensors to monitor farmer activity in the field. The sensors successfully connect to a farmer character in the game engine-based simulation, and animation is played when the bone rotation value reaches a certain level of wearable sensors that are effective in simulating digital twin control.

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Acknowledgements

The authors gratefully acknowledge the support by the Department of Computer Science and Systems Engineering (CSSE), Graduate School of Computer Science and Systems Engineering, Kyushu Institute of Technology, Japan.

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Correspondence to Yudhi Adhitya .

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Mulyani, G.S., Adhitya, Y., Köppen, M. (2023). Design and Implementation of Farmer Digital Twin Control in Smart Farming. In: Barolli, L. (eds) Advances in Intelligent Networking and Collaborative Systems. INCoS 2023. Lecture Notes on Data Engineering and Communications Technologies, vol 182. Springer, Cham. https://doi.org/10.1007/978-3-031-40971-4_49

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