Internet of Mobile Things: Mobility-Driven Challenges, Designs and Implementations

被引:51
作者
Nahrstedt, Klara [1 ]
Li, Hongyang [1 ]
Phuong Nguyen [1 ]
Chang, Siting [1 ]
Vu, Long [2 ]
机构
[1] Univ Illinois, Champaign, IL 61801 USA
[2] IBM TJ Watson Res Ctr, Yorktown Hts, NY USA
来源
PROCEEDINGS 2016 IEEE FIRST INTERNATIONAL CONFERENCE ON INTERNET-OF-THINGS DESIGN AND IMPLEMENTATION IOTDI 2016 | 2016年
关键词
VEHICLE;
D O I
10.1109/IoTDI.2015.41
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Smart environments such as smart grid, smart transportation, smart buildings are upon us because of major advances in sensor, communication, cloud and other cyberphysical system technologies. The collective name for interconnected sensors, placed on "things" within fixed cyber-physical infrastructures, is Internet of Things (IoT). IoT enables cities and rural areas to become smarter and to offer new digital services and functions to diverse groups of users. However, IoT often represents interconnection of static things, which are builtin into the physical infrastructures of users' homes, offices, roads and other physical and critical infrastructures. In this paper, we analyze things that are mobile, and explore the space of Internet of Mobile Things (IoMT). Mobility of digital devices such as phones and vehicles has been with us for some time, but as the number of sensors in mobile devices increases, the density of mobile devices increases, and users' reliance on mobile devices increases, mobile things become very much an integral fabric of our smart environment. In this paper, our goal is to discuss challenges, selective designs and implementations of IoMT. We show the impact of mobility and the care we collectively have to take when designing the next generation of smart environments with mobile things in them.
引用
收藏
页码:25 / 36
页数:12
相关论文
共 38 条
  • [21] Characterizing and modeling people movement from mobile phone sensing traces
    Long Vu
    Phuong Nguyen
    Nahrstedt, Klara
    Richerzhagen, Bjoern
    [J]. PERVASIVE AND MOBILE COMPUTING, 2015, 17 : 220 - 235
  • [22] Jyotish: Constructive approach for context predictions of people movement from joint Wifi/Bluetooth trace
    Long Vu
    Quang Do
    Nahrstedt, Klara
    [J]. PERVASIVE AND MOBILE COMPUTING, 2011, 7 (06) : 690 - 704
  • [23] Mobility Modeling, Spatial Traffic Distribution, and Probability of Connectivity for Sparse and Dense Vehicular Ad Hoc Networks
    Mohimani, G. Hosein
    Ashtiani, Farid
    Javanmard, Adel
    Hamdi, Maziyar
    [J]. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2009, 58 (04) : 1998 - 2007
  • [24] Context-aware Crowd-sensing in Opportunistic Mobile Social Networks
    Nguyen, Phuong
    Nahrstedt, Klara
    [J]. 2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems (MASS), 2015, : 477 - 478
  • [25] Pinto JG, 2013, IEEE IND ELEC, P5934, DOI 10.1109/IECON.2013.6700108
  • [26] Ravi N., 2005, AAAI
  • [27] Studer A., SECON 09
  • [28] Where and what: Using smartphones to predict next locations and applications in daily life
    Trinh Minh Tri Do
    Gatica-Perez, Daniel
    [J]. PERVASIVE AND MOBILE COMPUTING, 2014, 12 : 79 - 91
  • [29] The Places of Our Lives: Visiting Patterns and Automatic Labeling from Longitudinal Smartphone Data
    Trinh Minh Tri Do
    Gatica-Perez, Daniel
    [J]. IEEE TRANSACTIONS ON MOBILE COMPUTING, 2014, 13 (03) : 638 - 648
  • [30] Vu L., 2011, P PERC