Keynote speaker I: Ubiquitous sensing

P. Balamuralidhar, Subrat Kar
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Abstract

Ubiquitous sensing applications often involve the sensor based data collection with a large coverage in space in and time. From a return on investment perspective the value of information needs to be attractive with the cost of infrastructure to acquire it. The role of participative sensing and human centric sensing has been widely explored for collecting and analyzing data for use in social science, environmental and health applications. The wide availability of smart phones integrated with variety of sensors is becoming platform for people to document a neighborhood, gather evidence, study behaviors and is accelerating the pace of exploration in new application areas. Many of the current applications involve the monitoring of public spaces involving the participation of citizen in general. Participative surveillance is an application that can bring substantial social benefit. There are many challenges in effectively deploying such applications. It includes the privacy issues, trustworthiness of the data, human factors that affect the quality of sensing, variability of devices, enrolling and motivating participants, and a sustainable business model. Further it should be supported with a sound framework for deployment where the participant has control over data, transparency in data handling and intuitive user interface supporting multi-modal interactions. This presentation will discuss the above aspects with a few illustrative use case scenarios.
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主讲人1:无处不在的传感
泛在传感应用通常涉及基于传感器的数据采集,在空间、时间和时间上具有较大的覆盖范围。从投资回报的角度来看,信息的价值需要与获取信息的基础设施成本相匹配。参与式感知和以人为中心的感知在收集和分析用于社会科学、环境和健康应用的数据方面的作用已被广泛探索。集成了各种传感器的智能手机的广泛可用性正在成为人们记录邻里关系、收集证据、研究行为的平台,并加速了新应用领域的探索步伐。目前的许多应用都涉及到公众参与的公共空间的监控。参与式监测是一种能够带来可观社会效益的应用。有效地部署这样的应用程序有许多挑战。它包括隐私问题、数据的可信度、影响传感质量的人为因素、设备的可变性、参与者的招募和激励,以及可持续的商业模式。此外,它应该得到一个健全的部署框架的支持,其中参与者可以控制数据,数据处理的透明度和支持多模态交互的直观用户界面。本演示将通过几个说明性用例场景讨论上述方面。
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