Abstract

Internet of Things (IoT) and Arduino-based Weather Monitoring System is a groundbreaking technology that has revolutionized the way we gather, examine, and utilize weather data. There is potential with this system to greatly improve our comprehension of weather patterns and offer valuable insights for various industries such as aviation, agriculture, and disaster management. One of the main advantages of this system is its ability to provide real-time data. Conventional weather monitoring systems gather data by hand, which is time-consuming and prone to errors. The IoT-based system, on the other hand, provides accurate and up-to-date information, allowing for better decision-making and planning. The system is also cost-effective compared to traditional weather monitoring methods. The use of low-cost sensors and the elimination of manual data collection reduce the overall cost of the system. This makes it accessible to a wider range of users, including small-scale farmers and local governments. There are several uses for the data that the Internet of Things-based Weather Monitoring System gathers. For example, farmers can use the information to make informed decisions about crop irrigation and pest control. Aviation and shipping industries can use the data to plan safe and efficient routes, while disaster management agencies can use it to prepare for extreme weather events. In addition to its practical applications, this system also has the potential to contribute to scientific research. The vast amount of data collected by the sensors can be used to study weather patterns and climate change. This can help scientists better understand and predict natural disasters, leading to more effective disaster management strategies. However, like any other technology, the IoT-based Weather Monitoring System also has its limitations. One of the main concerns is data security. As the system relies on wireless communication, there is a risk of data being intercepted or manipulated by unauthorized individuals. Proper security measures need to be implemented to ensure the integrity and confidentiality of the data. Another challenge is the maintenance and calibration of the sensors. As these sensors are constantly exposed to harsh weather conditions, they may require regular maintenance and calibration to ensure accurate data collection. This can be a costly and time-consuming process, especially for large-scale weather monitoring systems.

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