Session 7: IBM_Big Data Analytics and WRM transformation
Channel: Big Data Transboundary Water Collaboration
Date: 2020-07-13

Big data analytics in the context of data quality challenges & the potential for transformation of water resource management through current and upcoming technological innovation

With real time satellite and Internet of Things sensors streaming daily TeraBytes of data, there could be no better time to manage and to monitor water resources. One challenge of big data-based monitoring and integration into AI models is automatic data quality assessment. Data validation can be achieved through a combination of multi-tier data filtering and comparison of measurements with data validated by models of expected evolution of water resources. While emerging solutions like big data informed irrigation can play a role in water conservation, they will require development of automated analytics that can stream the information to “water control” systems that can adapt to the environment and learn from it. We present an emerging, large scale modeling based on satellite data combined with local water management system that is able to extract water availability, monitor water quality and model flooding.

Dr. Levente Klein is a Research Staff Member in the Artificial Intelligence solution at the IBM T.J. Watson Research Center, Yorktown Heights, NY. His work at IBM spans multiple research topics from material science, nano-optics, and wireless sensing solutions with strong focus on applying research technologies to industrial problems. Since joining IBM Research in 2006, he developed technologies to enable energy efficient cooling in data centers, monitor fugitive methane gas in oil and gas industry, and apply wireless sensing solution in agriculture and healthcare.