基于物联网的Beagle bone black空气污染监测预报系统

N. Desai, J. Alex
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引用次数: 37

摘要

印度的城市空气污染率已经达到了令人担忧的水平。大多数城市都面临着空气质量差的问题,达不到健康空气标准。开发智能城市的空气污染测量和预测系统确实很有必要。这项工作通过使用污染检测传感器获取空气中的二氧化碳和一氧化碳水平以及全球定位系统(GPS)的位置,并上传到Azure云服务中。低成本的嵌入式Beagle骨板以及气体传感器用于数据采集。微软的Azure机器学习服务被用来在之前数据的帮助下预测污染指标。处理后的数据由Power BI工具提取和表示。校准后的气体传感器数据从传感器中提取,并成功上传到云端。存储在云中的数据被不同的云服务利用,使数据有意义。所提出的系统已被实施,并有助于通过避免污染原因来监测和减少智慧城市的污染。
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IoT based air pollution monitoring and predictor system on Beagle bone black
Urban air pollution rate has grown to alarming state across the India. Most of the cities are facing issue of poor air quality which fails to meet standards of air for good health. It is indeed necessary to develop an air pollution measurement and prediction system for a smart city. This proposed work acquires carbon dioxide and carbon monoxide level in the air along with Global Positioning System (GPS) location by using pollution detection sensor and uploads into Azure cloud services. Low cost embedded Beagle bone board along with gas sensors are used for data acquisition. Microsoft's Azure Machine learning service is used to predict the pollution metrics with the help of previous data. Processed data is fetched and represented by Power BI tool. Calibrated gas sensor data is fetched from sensors and successfully uploaded into cloud. Data stored in cloud is utilized by different cloud services to make the data meaningful. Proposed system is implemented and useful to monitor and reduce the pollution in a smart city by avoiding the pollution causes.
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