Keynote: OpenSense: Open sensor networks for air quality monitoring

K. Aberer
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引用次数: 4

Abstract

Wireless sensor networks and publishing of sensor data on the Internet bear the potential to substantially increase public awareness and involvement in environmental sustainability. Air pollution monitoring in urban areas is a prime example of such an application as common air pollutants have direct effect on the human health. However, bringing the vision of public involvement in environmental monitoring to a reality poses today substantial technical challenges for the communication and information systems infrastructure, to scale up from isolated well controlled systems to an open and scalable infrastructure. In this talk we provide first an overview of the OpenSense project for air pollution monitoring. OpenSense takes a holistic, end-to-end systems perspective. The crucial insight is that in designing open scalable sensing system one has to consider dependencies among many system dimensions both for modelling and control, including sensor behaviour, wireless networks, mobility, environmental models, user needs as well as trust and privacy concerns. In the second part of the talk we will discuss in more detail aspects of sensor data processing relevant to the OpenSense project. We will introduce model-based methods for sensor data cleaning, segmentation and multi-query processing. We will show a framework to extract semantic activity information from trajectory data and finally provide some initial results on studying the tradeoffs between privacy and sensor data accuracy in community sensing settings. Finally we will provide an outlook on some of our next steps we plan to undertake within OpenSense towards realizing a community-based approach for addressing health concerns of urban populations.
主题演讲:OpenSense:用于空气质量监测的开放式传感器网络
无线传感器网络和在互联网上发布传感器数据有可能大大提高公众对环境可持续性的认识和参与。城市地区的空气污染监测是这种应用的一个主要例子,因为常见的空气污染物对人体健康有直接影响。然而,将公众参与环境监测的愿景变为现实,对通信和信息系统基础设施构成了巨大的技术挑战,从孤立的井控系统扩展到开放和可扩展的基础设施。在这次演讲中,我们首先概述了用于空气污染监测的OpenSense项目。OpenSense采用整体的端到端系统视角。关键的洞察力是,在设计开放的可扩展传感系统时,必须考虑建模和控制的许多系统维度之间的依赖关系,包括传感器行为,无线网络,移动性,环境模型,用户需求以及信任和隐私问题。在演讲的第二部分,我们将更详细地讨论与OpenSense项目相关的传感器数据处理方面。我们将介绍基于模型的传感器数据清洗、分割和多查询处理方法。我们将展示一个从轨迹数据中提取语义活动信息的框架,并最终提供一些关于在社区感知设置中研究隐私和传感器数据准确性之间权衡的初步结果。最后,我们将展望我们计划在OpenSense中采取的一些下一步措施,以实现以社区为基础的方法来解决城市人口的健康问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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