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Application of a reliable MAC protocol for the urban air quality monitoring system based on the wireless sensor network

机译:基于无线传感器网络的可靠MAC协议在城市空气质量监测系统中的应用

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Because air pollutants seriously affect human health, the government in Taiwan attempts to reduce the pollutants by passing many environmental laws and establishing various large-scale and expensive air quality monitoring systems. These monitoring systems are capable of large-scale monitoring, but they cannot immediately detect small-scale air quality changes. Wireless sensor networks are novel monitoring tools for small-scale monitoring. Through a wireless network, a large number of tiny sensor nodes can be deployed to a monitoring area. In this research, a reliable medium access control (MAC) protocol is presented for the urban air quality monitoring system based on the wireless sensor network. The proposed MAC protocol uses the concept of overhearing to reduce previously required control messages and data messages in the network. The reconfiguration and rejoining functions are also incorporated into the proposed MAC protocol for improving the stability of data transmission. Moreover, the proposed MAC protocol is designed for the sensor nodes built upon the TinyOS, aiming at air urban quality monitoring in Taipei, Taiwan. This urban monitoring system consists of 36 sensor nodes to detect carbon monoxide (CO) concentration, humidity, and temperature. The experimental data shows that the proposed MAC protocol is capable of stably working a long period of time, and it also indicates a significant difference in the pollutant concentration between the rush and non-rush hours.
机译:由于空气污染物严重影响人类健康,因此台湾政府试图通过许多环境法律,并建立各种大型且昂贵的空气质量监测系统,以减少污染物。这些监测系统可以进行大规模监测,但是无法立即检测到小规模的空气质量变化。无线传感器网络是用于小规模监视的新颖监视工具。通过无线网络,可以将大量的微型传感器节点部署到监视区域。在这项研究中,提出了一种基于无线传感器网络的城市空气质量监测系统的可靠介质访问控制协议。所提出的MAC协议使用监听的概念来减少网络中先前需要的控制消息和数据消息。重新配置和重新加入功能也被合并到建议的MAC协议中,以提高数据传输的稳定性。此外,提出的MAC协议是针对基于TinyOS构建的传感器节点而设计的,旨在监视台湾台北市的城市空气质量。该城市监控系统由36个传感器节点组成,用于检测一氧化碳(CO)的浓度,湿度和温度。实验数据表明,提出的MAC协议能够长时间稳定工作,并且还表明了高峰时段和非高峰时段的污染物浓度存在显着差异。

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