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An AI Based Irrigation and Weather Forecasting System utilizing LoRaWAN and Cloud Computing Technologies

机译:利用洛拉瓦和云计算技术的基于AI的灌溉和天气预报系统

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摘要

Artificial Intelligence (AI) has been flourishing recently as a viable solution for many applications and scenarios, including smart irrigation and weather forecasting systems. In these systems, it is crucial to have an accurate prediction for the weather and soil conditions to optimize the irrigation process such that the minimal amount of water is provided. In this paper, a smart irrigation system utilizing Artificial Intelligence (AI) and Long Range Wide Area Network (LoRaWAN) communication link is proposed. The system is composed of sensors that are used to measure soil moisture, atmosphere temperature, and humidity. This information is sent via LoRaWAN communication link to a remote center that gathers, analyzes the captured information, quantifies the appropriate amount of water for irrigation, and then sends the decision back to the irrigation system. Furthermore, the collected information will be stored in the cloud for wider accessibility. This paper describes the technical implementation of the smart irrigation system and focuses on the weather forecasting process, which is performed using the Wind Driven Optimization - Least Square Support Vector Machine (WDO-LS-SVM) algorithm. The obtained results show a better performance when compared to the LS-SVM, which verifies the effectiveness of jointly utilizing the WDO with the LS-SVM.
机译:人工智能(AI)最近一直蓬勃发展,作为许多应用和场景的可行解决方案,包括智能灌溉和天气预报系统。在这些系统中,对于对天气和土壤条件具有精确的预测至关重要,以优化灌溉过程,从而提供最少量的水。本文提出了一种利用人工智能(AI)和远程广域网(LoraWan)通信链路的智能灌溉系统。该系统由用于测量土壤水分,大气温度和湿度的传感器组成。该信息通过Lorawan通信链接发送到远程中心,收集,分析捕获的信息,量化适量的水量进行灌溉,然后将决定送回灌溉系统。此外,收集的信息将存储在云中以进行更广泛的可访问性。本文介绍了智能灌溉系统的技术实现,并专注于天气预报过程,该过程是使用风驱动优化执行的 - 最小二乘支持向量机(WDO-LS-SVM)算法进行。与LS-SVM相比,所获得的结果显示出更好的性能,这验证了与LS-SVM共同利用WDO的有效性。

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