Kondo Shinnosuke, Yoshimoto Naoto, Nakayama Yu
Department of Electrical Engineering and Computer Science, Tokyo University of Agriculture and Technology, Tokyo 184-8588, Japan.
Department of Opto-Electronics System Engineering, Chitose Institute of Science and Technology, Chitose 066-8655, Japan.
Sensors (Basel). 2024 Sep 23;24(18):6146. doi: 10.3390/s24186146.
Drones have been attracting significant attention in the field of agriculture. They can be used for various tasks such as spraying pesticides, monitoring pests, and assessing crop growth. Sensors are also widely used in agriculture to monitor environmental parameters such as soil moisture and temperature. Due to the high cost of communication infrastructure and radio-wave modules, the adoption of high-density sensing systems in agriculture is limited. To address this issue, we propose an agricultural sensor network system using drones and Optical Camera Communication (OCC). The idea is to transmit sensor data from LED panels mounted on sensor nodes and receive the data using a drone-mounted camera. This enables high-density sensing at low cost and can be deployed in areas with underdeveloped infrastructure and radio silence. We propose a trajectory control algorithm for the receiving drone to efficiently collect the sensor data. From computer simulations, we confirmed that the proposed algorithm reduces total flight time by 30% compared to a shortest-path algorithm. We also conducted a preliminary experiment at a leaf mustard farm in Kamitonda-cho, Wakayama, Japan, to demonstrate the effectiveness of the proposed system. We collected 5178 images of LED panels with a drone-mounted camera to train YOLOv5 for object detection. With simple On-Off Keying (OOK) modulation, we achieved sufficiently low bit error rates (BERs) under 10-3 in the real-world environment. The experimental results show that the proposed system is applicable for drone-based sensor data collection in agriculture.
无人机在农业领域一直备受关注。它们可用于各种任务，如喷洒农药、监测害虫和评估作物生长。传感器在农业中也被广泛用于监测土壤湿度和温度等环境参数。由于通信基础设施和无线电波模块成本高昂，农业中高密度传感系统的应用受到限制。为解决这一问题，我们提出一种使用无人机和光摄像头通信（OCC）的农业传感器网络系统。其理念是从安装在传感器节点上的发光二极管（LED）面板传输传感器数据，并使用安装在无人机上的摄像头接收数据。这能够以低成本实现高密度传感，并且可以部署在基础设施欠发达和无线电静默的地区。我们为接收无人机提出一种轨迹控制算法，以高效收集传感器数据。通过计算机模拟，我们证实与最短路径算法相比，所提出的算法可将总飞行时间减少30%。我们还在日本和歌山县上富田町的一个叶芥菜农场进行了初步实验，以证明所提出系统的有效性。我们使用安装在无人机上的摄像头收集了5178张LED面板的图像，用于训练YOLOv5进行目标检测。通过简单的开关键控（OOK）调制，我们在实际环境中实现了足够低的误码率（BER），低于10-3。实验结果表明，所提出的系统适用于基于无人机的农业传感器数据收集。
