This event is endorsed
and organized by

EAI International Conference on Big Data and Analytics for Smart Cities

October 13–14, 2015 | Toronto, Canada

EAI International Conference on Big Data and Analytics for Smart Cities

Download BigDASC 2015 soft proceedings

BigDASC 2015 is collocated with Smart City 360 Summit

Follow us on Twitter!





  • Participation in this event will give attendees the unique opportunity to be exposed to all technical scientific aspects of Smart City related topic areas at co-located conferences, as well as be able to have full access to the Smart City market place and business aspects in practice at the Smart City 360 Summit.

  • Best Papers will be considered for publication in the ACM/Springer Mobile Networks and Applications Journal (MONET).

  • All accepted papers will be published by Springer and made available through SpringerLink Digital Library, one of the world's largest scientific libraries. Best papers will be invited to publish also in the EAI Endorsed Transactions on Cloud Systems.


This conference is all about Big Data & Analytics for Smart Cities:

Smart cities use digital technology to enhance wellbeing, to reduce costs and resource consumption, and to engage more effectively and actively with their citizens. Key 'smart' sectors include transport, energy, health care, education, social programs, water and waste.

Big data deals with data so large and/or complex such that traditional data processing applications are inadequate. Big data challenges include analysis, capture, curation, search, sharing, storage, transfer, visualization, and information privacy.

Big Data & Analytics for Smart Cities 

Generating, storing and manipulating data on the magnitude of exabytes (one quintillion bytes!) is increasingly relied on to measure traffic, crime and disease patterns, environmental health, business and municipal data.  Big data is evolving with advanced analytics to help cities analyze patterns that can reduce pollutants, conserve and manage resources, increase operating efficiencies. Big Data and advanced analytics are evolving in tandem with the “Internet of Things” to establish a global network of an estimated 12.5 billion devices and smart sensors predicated by 2020.



  • Design of computing schemes for analytics platforms in smart cities

  • Systems and techniques for data collection including heterogeneous sensor networks and cooperative sensing for smart cities

  • Data integration, data aggregation, data validation, data cleansing techniques

  • Data anonymization techniques

  • Data visualization

  • Social networks and smart cities

  • Internet of Things (IoT) and smart cities

  • Use of big data analytics in the following content:

    • smart grids

    • emergency evacuation

    • disaster recovery

    • security / privacy challenges

    • business performance management (city governance)

    • fault detection / diagnosis

    • real-estate market

    • behavioral change patterns

    • congestion management

    • multi-modal travel management

    • eHealth in smart cities