A Digital TV-Based Distributed Image Processing Platform for Natural Disasters

After a natural disaster strikes people spontaneously respond by self-organizing, providing food and drink to the victims and to emergency response teams. During this process, people also share photos, messages and videos which can be used to improve the general understanding of the situation and to support decision-making. In this context, we propose to use digital television to create a community of digital volunteers who can help to identify objects inside images that cannot be processed automatically. Digital television can help to reach a larger number of digital volunteers because it can be easily used without installing special applications. We present a distributed platform composed of a server, a network of digital volunteers and an internet service provider. Our proposed platform aims to reduce the communication between the server and the digital volunteers and to reduce the workload of the server. We simulate our proposed platform with the peersim tool.

[1]  Ferda Ofli,et al.  Combining Human Computing and Machine Learning to Make Sense of Big (Aerial) Data for Disaster Response , 2016, Big Data.

[2]  Cobi Smith.  A Case Study of Crowdsourcing Imagery Coding in Natural Disasters , 2017 .

[3]  Antony I. T. Rowstron,et al.  Pastry: Scalable, Decentralized Object Location, and Routing for Large-Scale Peer-to-Peer Systems , 2001, Middleware.

[4]  Philipp Olbrich,et al.  Big Data from Outer Space: Opportunities and Challenges for Crisis Response , 2017 .

[5]  Gade Krishna,et al.  A scalable peer-to-peer lookup protocol for Internet applications , 2012 .

[6]  Alexandro Bordignon,et al.  Mechanisms for interoperable content production among Web, Digital TV and Mobiles Mecanismos para a produção de conteúdo interoperável entre web, TV digital e dispositivos de telefonia móvel , 2009 .

[7]  Paloma Díaz,et al.  Giving meaning to tweets in emergency situations: a semantic approach for filtering and visualizing social data , 2016, SpringerPlus.

[8]  Antonio Liotta,et al.  Handbook of Research on P2P and Grid Systems for Service-oriented Computing: Models, Methodologies a , 2010 .

[9]  Pablo Rodriguez,et al.  Should internet service providers fear peer-assisted content distribution? , 2005, IMC '05.

[10]  John M. Carroll,et al.  Coproduction as an Approach to Technology-Mediated Citizen Participation in Emergency Management , 2016, Future Internet.

[11]  David Becker,et al.  Crowdsourcing Solutions for Disaster Response: Examples and Lessons for the US Government☆ , 2015 .

[12]  Mauricio Marín,et al.  Two-Level Result Caching for Web Search Queries on Structured P2P Networks , 2012, 2012 IEEE 18th International Conference on Parallel and Distributed Systems.

[13]  Marjorie Greene,et al.  Crowdsourcing earthquake damage assessment using remote sensing imagery , 2012 .

[14]  Mohamed Hefeeda,et al.  On the Benefits of Cooperative Proxy Caching for Peer-to-Peer Traffic , 2010, IEEE Transactions on Parallel and Distributed Systems.

[15]  Chin-Feng Lai,et al.  3PRS: a personalized popular program recommendation system for digital TV for P2P social networks , 2010, Multimedia Tools and Applications.

[16]  Krishna P. Gummadi,et al.  Measurement, modeling, and analysis of a peer-to-peer file-sharing workload , 2003, SOSP '03.

[17]  Mauricio Marín,et al.  Web search results caching service for structured P2P networks , 2014, Future Gener. Comput. Syst..

[18]  J. Twigg,et al.  Emergent groups and spontaneous volunteers in urban disaster response , 2017 .