College of Information Science & Technology, Nanjing Forestry University, Nanjing 210037, China.
Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN 55414, USA.
Sensors (Basel). 2020 Mar 8;20(5):1487. doi: 10.3390/s20051487.
With the development of information technology, Internet-of-Things (IoT) and low-altitude remote-sensing technology represented by Unmanned Aerial Vehicles (UAVs) are widely used in environmental monitoring fields. In agricultural modernization, IoT and UAV can monitor the incidence of crop diseases and pests from the ground micro and air macro perspectives, respectively. IoT technology can collect real-time weather parameters of the crop growth by means of numerous inexpensive sensor nodes. While depending on spectral camera technology, UAVs can capture the images of farmland, and these images can be utilize for analyzing the occurrence of pests and diseases of crops. In this work, we attempt to design an agriculture framework for providing profound insights into the specific relationship between the occurrence of pests/diseases and weather parameters. Firstly, considering that most farms are usually located in remote areas and far away from infrastructure, making it hard to deploy agricultural IoT devices due to limited energy supplement, a sun tracker device is designed to adjust the angle automatically between the solar panel and the sunlight for improving the energy-harvesting rate. Secondly, for resolving the problem of short flight time of UAV, a flight mode is introduced to ensure the maximum utilization of wind force and prolong the fight time. Thirdly, the images captured by UAV are transmitted to the cloud data center for analyzing the degree of damage of pests and diseases based on spectrum analysis technology. Finally, the agriculture framework is deployed in the Yangtze River Zone of China and the results demonstrate that wheat is susceptible to disease when the temperature is between 14 °C and 16 °C, and high rainfall decreases the spread of wheat powdery mildew.
随着信息技术、物联网（IoT）和以无人机（UAV）为代表的低空遥感技术的发展，它们被广泛应用于环境监测领域。在农业现代化进程中，IoT 和 UAV 分别从地面微观和空中宏观的角度监测作物病虫害的发生。IoT 技术可以通过大量廉价的传感器节点来采集作物生长的实时气象参数。而 UAV 则可以依靠光谱相机技术捕捉农田的图像，这些图像可以用于分析作物病虫害的发生情况。在这项工作中，我们尝试设计一个农业框架，以深入了解病虫害发生与气象参数之间的具体关系。首先，考虑到大多数农场通常位于偏远地区，远离基础设施，由于能源补充有限，难以部署农业 IoT 设备，因此设计了一个太阳跟踪器设备，以自动调整太阳能电池板和阳光之间的角度，提高能量采集率。其次，为了解决 UAV 飞行时间短的问题，引入了一种飞行模式，以确保最大限度地利用风力并延长飞行时间。第三，UAV 拍摄的图像被传输到云数据中心，基于光谱分析技术来分析病虫害的严重程度。最后，该农业框架在中国长江流域进行了部署，结果表明，当温度在 14°C 到 16°C 之间时，小麦容易生病，而高降雨量会降低小麦白粉病的传播。
