• Large-Scale, Tempo-Spatial Information Gathering Mechanism over DTN

  • In this research project, we consider emergency situations with limited availability of cellular networks and Internet connections in urban areas, and develop a methodology to autonomously organize survived communicating nodes to realize a large-scale, tempo-spatial information gathering.

Grant-in-Aid for Scientific Research (S) supported from IPSJ

Large-Scale, Tempo-Spatial Information Gathering Mechanism over DTN-enabled Distributed Micro-modules

In this research project, we design the following functions: (1) micro- sensing functions by available mobile nodes and stations (called micro-modules) for sensing and situation awareness, (2) DTN-based communication facilities over micro-modules, (3) micro- processing functions for smart understanding of situations on micro-modules and (4) autonomous tempo-spatial information gathering among micro- modules. Finally, we will prototype a platform that involves these functions.

It is very necessary in well-populated urban areas to deploy resistant cellular network infrastructure with uninterruptible power supply (UPS). However, installation of such infrastructure is not often reasonable in rural areas. Meanwhile, recent smartphones and car navigation systems have sufficient capabilities to communicate and co- operate toward information gathering and sharing in disaster areas, but these mobile nodes are not always connected and designing self-organized computation mechanism is a primary research challenge. This motives us to realize information sharing over delay tolerant networks (DTNs).

Mobility Estimation of People, Vehicles and Transportations

Using the mobile space statistical information to estimate the population of the target city block and using information obtained from probe car data, drive recorder equipped in cars or motorcycles, security cameras installed intersections, human detection sensors or the like, we estimate the mobility of people and vehicles traveling on the road. At the same time, the movement information of public transportation facilities (train etc.) can be estimated using the mobility information of cellular phones. The indoor pedestrians are estimated using crowd sensing information obtained from human detection sensors in buildings and underground shopping malls
or smartphones. By using the estimated information for the target block, we estimate the density distribution of people in the block with high accuracy.

Information Gathering over DTN

Under circumstances where communication networks are disrupted everywhere due to earthquakes and disasters, we are designing and developing an information gathering system for efficiently conveying disaster information by cooperating the smartphones of residents and the wireless communication facilities installed in target areas, radio base stations installed temporarily and those on rescue vehicles. In the proposed method, the information gathering system is developed over DTN by considering the density distribution of people in the target areas and the communication situation of wireless networks that might vary every minute. The information about disaster situations might be collected in inversely proportional to human density. The people's survival information might be collected by considering human density. We will construct the MapReduce mechanism on DTN considering disaster situations in real-time.

[Selected Publications]
M. Elhamshary, M. Youssef, A. Uchiyama, H. Yamaguchi and T. Higashino: "TransitLabel: A Crowd-Sensing System for Automatic Labeling of Transit Stations Semantics", Proceedings of 14th Annual International Conference on Mobile Systems, Applications, and Services (MobiSys 2016), pp.193-206, 2016.

Y. Yamada, A. Uchiyama, A. Hiromori, H. Yamaguchi and T. Higashino: "Travel estimation using Control Signal Records in cellular networks and geographical information", Proceedings of the 9th IFIP Wireless and Mobile Networking Conference (WMNC 2016), pp.138-144, 2016.

T. Higuchi, H. Yamaguchi and T. Higashino: "Tracking Motion Context of Railway Passengers by Fusion of Low-power Sensors in Mobile Devices", Proceedings of 2015 ACM International Symposium on Wearable Computers (ISWC 2015), pp.163-170, 2015.

T. Higuchi, H. Iwahashi, H. Yamaguchi and T. Higashino: "TweetGlue: Leveraging a Crowd Tracking Infrastructure for Mobile Social Augmented Reality", Proceedings of the International Wireless Communications and Mobile Computing Conference (IWCMC 2015), pp.1030-1035, 2015.

S. Choochotkaew, H. Yamaguchi, T. Higashino and M. Shibuya: "Requirement-based Prioritization System in Multi-user IoT", Proceedings of the 2nd IEEE World Forum on Internet of Things (WF-IoT 2015), pp.122-127, 2015.

K. Yoi, H. Yamaguchi, A. Hiromori, A. Uchiyama, T. Higashino, N. Yanagiya, T. Nakatani, A. Tachibana, T. Hasegawa: "Multi-dimensional sensor data aggregator for adaptive network management in M2M communications", Proceedings of IFIP/IEEE International Symposium on Integrated Network Management (IM 2015), pp.1047-1052, 2015.

Y. Maekawa, A. Uchiyama, H. Yamaguchi and T. Higashino: "Car-level Congestion and Position Estimation for Railway Trips using Mobile Phones", Proceedings of 2014 ACM Conference on Ubiquitous Computing (UbiComp 2014), pp.939-950, 2014.

T. Nishimura, T. Higuchi, H. Yamaguchi and T. Higashino: "Detecting Smoothness of Pedestrian Flows by Participatory Sensing with Mobile Phones", Proceedings of 2014 ACM International Symposium on Wearable Computers (ISWC 2014), pp.15-18, 2014.