主题演讲:移动物联网:挑战与机遇

K. Nahrstedt
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引用次数: 9

摘要

物联网(IoT)概念已经存在了一段时间,交通、医疗、教育、旅游、智能电网、零售等应用都是这一概念的主要受益者。然而,直到最近,由于传感器设备的技术进步和丰富的无线连接,大规模的物联网正在成为现实。例如,思科物联网集团预测,到2020年,连接的传感设备将超过500亿台。在本次演讲中,我们将讨论移动物联网(IoMT),因为一些改变游戏规则的技术进步发生在“移动事物”上,如移动电话、火车和汽车,通过各种无线互联网技术连接的丰富传感器正在改变和影响人们交流、移动、下载和分发信息的方式。在这个领域,挑战来自于确定以下需求:(1)上下文信息,如位置、接触持续时间、设备密度,利用网络感官信息;(2)更高层次的知识,如用户的活动检测、情绪检测、应用使用模式检测和用户在“移动事物”上的交互,利用上下文信息;(3)自适应和实时并行和分布式架构,将上下文、活动、情绪、使用模式集成到移动“事物”上的移动应用服务中。解决这些挑战将为提高移动“事物”的效用提供巨大的机会,优化移动“事物”上的稀缺资源,如能源、内存和带宽。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Keynote: Internet of mobile things: Challenges and opportunities
The Internet of Things (IoT) concept has been around for some time and applications such as transportation, health-care, education, travel, smart grid, retail, are and will be major benefactors of this concept. However, only recently, due to technological advances in sensor devices and rich wireless connectivity, Internet of Things at scale is becoming reality. For example, Cisco's Internet of Things Group predicts over 50 billion connected sensory devices by 2020. In this talk, we will discuss the Internet of Mobile Things (IoMT) since several game-changing technological advances happened on ‘mobile things’ such as mobile phones, trains, and cars, where rich sets of sensors, connected via diverse sets of wireless Internet technologies, are changing and influencing how people communicate, move, and download and distribute information. In this space, challenges come from the needs to determine (1) contextual information such as location, duration of contact, density of devices, utilizing networked sensory information; (2) higher level knowledge such as users' activity detection, mood detection, applications usage pattern detection and user interactions on ‘mobile things’, utilizing contextual information; and (3) adaptive and real-time parallel and distributed architectures that integrate context, activity, mood, usage patterns into mobile application services on mobile ‘things’. Solving these challenges will provide enormous opportunities to improve the utility of mobile ‘things’, optimizing scarce resources on mobile ‘things’ such as energy, memory, and bandwidth.
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