Computers and Electronics in Agriculture
In this paper, we develop an IoT-based monitoring system for precision agriculture applications such as epidemic disease control. Such an agricultural monitoring system provides environmental monitoring services that maintain the crop growing environment in an optimal status and early predicts the conditions that lead to epidemic disease outbreak. The agricultural monitoring system provides a service to store the environmental and soil information collected from a wireless sensor network installed in the planted area in a database. Furthermore, it allows users to monitor the environmental information about the planted crops in real-time through any Internet-enabled devices. We develop artificial intelligence and prediction algorithms to realize an expert system that allows the system to emulate the decision-making ability of a human expert regarding the diseases and issue warning messages to the users before the outbreak of the disease. Field experiments showed that the proposed system reduces the number of chemical applications, and hence, promotes agriculture products with no (or minimal) chemicals residues and high-quality crops. This platform is designed to be generic enough to be used with multiple plant diseases where the software architecture can handle different plant disease models or other precision agriculture applications.
本发明涉及无人机技术领域，尤其涉及一种 农田火源监测无人机系统设计。本发明为了克服 农田火源监测的问题，提供了一种农田火源监测 无人机系统设计，针对于重点监测区域设计了一 款四旋翼无人机。采用四路独立电机作为四输 入、六输出的驱动系统，搭载导航模块用来飞行 信息的采集。无人机可根据已知地形信息进行一 次航迹规划。并搭载了图像采集装置可进行可见 光图像和热成像图像采集，为了保障图像采集的 稳定性，设计了三自由度的稳定云台，并运用图 像处理的算法进行了数据分析，最终锁定着火区 域。本发明具有很高的实用价值和推广价值。
Procedia Computer Science
Now-a-days, the natural irrigation system is under pressure due to the growing water shortages, which are mainly caused by population growth and climate change. Therefore, the control of water resources to increase the allocation of retained water is very important. It has been observed in the last two decades, especially in the Indian sub-continent, the change of climate affects the agricultural crops production significantly. However, the prediction of good harvests before harvesting, enables the farmers as well as the government officials to take appropriate measures of marketing and storage of crops. Some strategies for predicting and modelling crop yields have been developed, although they do not take into account the characteristics of climate, and they are empirical in nature. In the proposed system, a Cuckoo Search Algorithm has been developed, allowing the allocation of water for farming under any conditions. The various parameters such as temperature, turbidity, pH., moisture have been collected by using Internet of Things (IoT) platform, equipped with related sensors and wireless communication systems. In this IoT platform the sensor data have been displayed in the cloud environment by using ThingSpeak. The data received in the ThingSpeak used in the proposed Cuckoo Search Algorithm, allowing the selection of appropriate crops for particular soil.
[相关专利] Customized land surface modeling in a soil-crop system using satellite data to detect irrigation and precipitation events for decision support in precision agriculture 进入全文
United States Patent and Trademark Office
An irrigation modeling framework in precision agriculture utilizes a combination of weather data, crop data, and other agricultural inputs to create customized agronomic models for diagnosing and predicting a moisture state in a field, and a corresponding need for, and timing of, irrigation activities. Specific combinations of various agricultural inputs can be applied, together with weather information to identify or adjust water-related characteristics of crops and soils, to model optimal irrigation activities and provide advisories, recommendations, and scheduling guidance for targeted application of artificial precipitation to address specific moisture conditions in a soil system of a field.