Albuali Abdullah, Srinivasagan Ramasamy, Aljughaiman Ahmed, Alderazi Fatima
Department of Computer Networks and Communications, College of Computer Sciences and Information Technology, King Faisal University, Al-Ahsa 31982, Saudi Arabia.
Department of Computer Engineering, College of Computer Sciences and Information Technology, King Faisal University, Al-Ahsa 31982, Saudi Arabia.
Sensors (Basel). 2023 Jun 14;23(12):5569. doi: 10.3390/s23125569.
The Internet of Things (IoT) plays a critical role in remotely monitoring a wide variety of different application sectors, including agriculture, building, and energy. The wind turbine energy generator (WTEG) is a real-world application that can take advantage of IoT technologies, such as a low-cost weather station, where human activities can be significantly affected by enhancing the production of clean energy based on the known direction of the wind. Meanwhile, common weather stations are neither affordable nor customizable for specific applications. Moreover, due to weather forecast changes over time and location within the same city, it is not efficient to rely on a limited number of weather stations that may be located far away from a recipient's location. Therefore, in this paper, we focus on presenting a low-cost weather station that relies on an artificial intelligence (AI) algorithm that can be distributed across a WTEG area with minimal cost. The proposed study measures multiple weather parameters, such as wind direction, wind velocity (WV), temperature, pressure, mean sea level, and relative humidity to provide current measurements to recipients and AI-based forecasts. In addition, the proposed study consists of several heterogeneous nodes and a controller for each station in a target area. The collected data can be transmitted through Bluetooth low energy (BLE). The experimental results reveal that the proposed study matches the standard of the National Meteorological Center (NMC), with a nowcast measurement of 95% accuracy for WV and 92% for wind direction (WD).
物联网（IoT）在远程监测包括农业、建筑和能源等广泛不同的应用领域中发挥着关键作用。风力涡轮机能量发生器（WTEG）是一个可以利用物联网技术的实际应用，例如低成本气象站，通过基于已知风向提高清洁能源产量，人类活动会受到显著影响。同时，普通气象站对于特定应用既不经济实惠也不可定制。此外，由于同一城市内天气随时间和地点变化，依赖可能位于远离接收者位置的有限数量气象站效率不高。因此，在本文中，我们专注于展示一种低成本气象站，它依赖一种人工智能（AI）算法，该算法能够以最小成本分布在WTEG区域。所提出的研究测量多个气象参数，如风向、风速（WV）、温度、压力、平均海平面和相对湿度，以便向接收者提供当前测量值和基于AI的预测。此外，所提出的研究在目标区域的每个站点由几个异构节点和一个控制器组成。收集到的数据可以通过低功耗蓝牙（BLE）传输。实验结果表明，所提出的研究符合国家气象中心（NMC）的标准，WV的临近预报测量准确率为95%，风向（WD）为92%。
