Design and Implementation of Remote Monitoring System for Rare Trees Based on LoRa Communication

Chen, Xu; Zheng, Xiaoyue; Quou, Ge; Xu, Tao; Wu, Xiushan

doi:10.1088/1742-6596/2224/1/012055

Cited by 1 publication

(1 citation statement)

References 7 publications

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“…The principal thematic tenets underpinning this study revolve around the meticulous design and implementation of a remote monitoring system tailored to preserve endangered trees, leveraging the robust communication framework afforded by LoRa technology (Xu et al, 2022). This innovative solution is meticulously architected to enhance the e cacy of maintenance managers and grapple with the extant challenges inherent to monitoring and managing rare arboreal specimens.…”

Section: Scalability and Sustainabilitymentioning

confidence: 99%

The Impact of IoT and Sensor Integration on Real-Time Weather Monitoring Systems: A Systematic Review

Selvam,

Al-Humairi

2023

Preprint

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The observation of weather and its impact on human life is undeniable. Weather observations are essential for various sectors, including agriculture, transportation, aviation, and disaster management. Therefore, the collection of data on weather variations is crucial. However, the transient nature of weather variations makes it difficult to collect accurate and real-time data. To overcome this challenge, researchers have developed smart real-time weather monitoring systems integrated with mobile applications. These systems utilize various frameworks, technologies, and techniques, including the Internet of Things (IoT), Arduino, machine learning algorithms, deep learning algorithms, and sensors that measure temperature, humidity, wind speed, and wind direction. These systems provide real-time data on weather conditions, enabling individuals to make informed decisions. The primary objective of this review paper is to critically examine and elaborate on multiple research studies that focus on integrating smart real-time weather monitoring systems with mobile applications. The aim is to understand the techniques, methodologies, and technologies employed in designing and developing such systems. One of the key findings of this review is that integrating smart real-time weather monitoring systems with mobile applications has significant potential to improve weather forecasting and monitoring. For instance, machine learning algorithms can analyze sensor data to identify patterns and accurately predict future weather conditions. Additionally, integrating cloud computing technology in these systems allows for secure data storage, making it accessible to validated individuals from anywhere. In conclusion, integrating smart real-time weather monitoring systems with mobile applications has enormous potential in improving weather forecasting and monitoring. Various frameworks, technologies, and techniques have enabled researchers to develop sophisticated systems that collect accurate and real-time data on weather conditions. These systems significantly affect various sectors, including agriculture, transportation, aviation, and disaster management.

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Section: Scalability and Sustainabilitymentioning

confidence: 99%