AI with Geospatial Information System for Social Good

Overview

Artificial intelligence (AI) has the potential to help tackle challenging urban and regional problems, ranging from diagnosing cancer to assisting blind people navigate their surroundings, detecting drug abuse and trafficking, identifying victims of online sexual exploitation, facilitating disaster response, and promoting social justice and sustainable development. In addition to AI, Geospatial Information System (GIS) technology can be a powerful tool capable of exploring the social issues in the spatial context, through the domains such as criminology, resource management, and transportation planning. For example, a GIS platform might allow emergency planners to swiftly map resources towards emergency response in the event of a natural disaster.

If AI and GIS can be appropriately managed and integrated, the rich and diverse geographic information via GIS will significantly boost the impact of AI on many aspects of our lives. An AI-GIS framework can be used to predict and locate vulnerable communities under natural disasters, identify virus and disease transmission patterns, or to optimize the food distribution in the areas facing shortages and famine.

CSoNet 2019 will feature a special track on AI with GIS for Social Good. The goal of this track is to provide a venue to disseminate the research focusing on social problems for which Artificial Intelligence and Geospatial Information System have the potential to offer the innovative solutions. This track will bring together researchers and practitioners across artificial intelligence, geospatial information system and a range of application domains on the frontiers of frameworks, theories, and methods.

Sample topics include, but not limited to:

  • Crime Prediction
  • Environmental sustainability
  • Ethics and security issues
  • Fairness and biases
  • GeoAI
  • Human and Population Dynamics
  • Information Diffusion and Community Detection
  • Mobility and Traffic Prediction
  • Spatial and Social Network Analysis
  • Urban Computing
  • Urban Health
  • Urban Remote Sensing and Social Sensing

Accepted papers and extended abstracts will be published in the conference proceedings; selected high-quality papers will be invited to special issues of the Journal of Social Computing, Journal of Combinatorial OptimizationIEEE Transactions on Network Science and Engineering, and Computational Social Networks.

Contribution Types

  • Regular paper: 12 pages
  • Extended Abstract (work in progress) : 2 pages

The workshop will accept original research contribution, review paper, and survey paper. Page limit is including the references and appendices.

If you do not want to publish the extended abstract and only want to present it, please mention it in the extended abstract and if possible, please also email this to the organizers.

Submission Format

  • Papers must be formatted using the LNCS format.
  • Submissions are open on EasyChair.
  • More details are available at CSoNet Website.

Publications

Registration

  • Each accepted paper needs at least one full registration, before the camera-ready manuscript can be included in the proceedings.
  • Registration fee details are available at CSoNet 2019 Website.

Important Dates

  • Paper Submission Deadline: August 24, 2019
  • Acceptance Notification: September 24, 2019
  • Camera Ready & Registration: October 01, 2019
  • Conference Dates: November 18-20, 2019

Contacts:

Dr. Hai N. Phan, Dr. Xinyue Ye, {phan, xinyue.ye}@njit.edu