[学术文献] Wireless technologies for smart agricultural monitoring using internet of things devices with energy harvesting capabilities 进入全文
Computers and Electronics in Agriculture
Technological advances in the Internet of Things (IoT) have paved the way for wireless technologies to be used in new areas. Agricultural monitoring is an example where IoT can help to increase productivity, efficiency, and output yield. However, powering these devices is a concern as batteries are often required due to devices being located where electricity is not readily available. In this paper, an experimental comparison is performed between IoT devices with energy harvesting capabilities that use three wireless technologies: IEEE 802.11 g (WiFi 2.4 GHz), IEEE 802.15.4 (Zigbee), and Long Range Wireless Area Network (LoRaWAN), for agricultural monitoring. Four experiments were conducted to examine the performance of each technology under different environmental conditions. According to the results, LoRaWAN is the optimal wireless technology to be used in an agricultural monitoring system, when the power consumption and the network lifetime are a priority.
Due to the traditional cloud computing-based information transmission mechanisms and IOT’s problems of large errors and low security, a heterogeneous integrated network resource management algorithm based on information security transmission is proposed. The algorithm adopts the advantages of information security transmission technology to collect resources in heterogeneous integrated network, then improves resource management algorithms and finally establishes a resource management algorithm model based on information security transmission, thereby implement the management process of heterogeneous integrated network resources. Through experimental demonstration and analysis methods, the effectiveness of the resource management algorithm is determined, which can reduce resource management errors and can improve security performance and management accuracy in the resource management process. In addition, the paper also introduces main data encryption technology and discusses the intelligent collection process of the Internet of Things(IoT), which is the technology background of the presented algorithm.
Plants use hydrogen peroxide to communicate within their leaves, sending out a distress signal that stimulates leaf cells to produce compounds that will help them repair damage or fend off predators such as insects. The new sensors can use these hydrogen peroxide signals to distinguish between different types of stress, as well as between different species of plants. This kind of sensor could be used to study how plants respond to different types of stress, potentially helping agricultural scientists develop new strategies to improve crop yields. The researchers demonstrated their approach in eight different plant species, including spinach, strawberry plants, and arugula, and they believe it could work in many more.
[前沿资讯] How a team of scientists studying drought helped build the world’s leading famine prediction model 进入全文
The Indian Ocean seemed ready to hit Africa with a one-two punch. It was September 2019, and the waters off the Horn of Africa were ominously hot. Every few years, natural swings in the ocean can lead to such a warming, drastically altering weather on land—and setting the stage for flooding rains in East Africa. But at the same time, a second ocean shift was brewing. An unusually cold pool of water threatened to park itself south of Madagascar, leading to equally extreme, but opposite, weather farther south on the continent: drought. Half a world away, at the Climate Hazards Center (CHC) of the University of California, Santa Barbara (UCSB), researchers took notice. Climate models, fed by the shifting ocean data, pointed to a troubling conclusion: By year’s end, that cold pool would suppress evaporation that would otherwise fuel rains across southern Africa. If the prediction held, rains would fizzle across southern Madagascar, Zambia, and Mozambique at the beginning of the growing season in January, the hungriest time of year. Zimbabwe, already crippled by inflation and food shortages, seemed particularly at risk. “We were looking at a really bad drought,” says Chris Funk, a CHC climate scientist. It was a warning of famine.