Transforming agricultural water management through integrated data science, sensor networks, and intelligent modeling to secure food production for millions.
Explore the ProjectFive Thematic areas and 10 Work Packages.
Three Study Area, covering different hydrological region.
Platform provides modelling results, sensors data and many more.
Web-AIS brings real-time data, satellite analytics, crop models, and groundwater–surface water models together into one intelligent platform — designed for Bangladesh’s farmers, agencies, and policy-makers.
Building digital representations of crops, water systems, climate and land systems.
Read MoreTransforming complex models & data into actionable insights for farmers and agencies.
Read MoreWebAIS integrates five core thematic areas to bridge the gap between field observations and national policy decisions.
Building a robust network of sensors, satellite data pipelines, and modern data infrastructure to provide continuous, real-time environmental intelligence.
Explore DomainIntegrating hydrological, groundwater, salinity, and hydrodynamic models to quantify water availability.
Explore DomainLinking field experiments and crop models to determine precise water needs for agricultural output.
Explore DomainAnalyzing crop rotations, land use change, and farmer behavior to understand system shifts.
Explore DomainA unified digital platform connecting data, models, and AI to deliver actionable national insights.
Explore Domain
We leverage cutting-edge technology to bridge the gap between complex scientific data and practical agricultural needs. Our platform is designed to be intuitive, accessible, and highly interactive for all stakeholders in the agricultural ecosystem.
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Web-AIS brings real-time data, satellite analytics, crop models, and groundwater–surface water models together into one intelligent platform — designed for Bangladesh’s farmers, agencies, and policy-makers.
Real-time monitoring through sensors, satellites, and automated data streams powering the national agricultural intelligence system.
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Integrated crop, groundwater, hydrological, and land-system models simulate water demand, availability, and future scenarios.
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High-resolution crop maps and multi-source data streams feed directly into models, improving accuracy from field to national scale.
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Field experiments across three agro-ecological zones provide real-world crop water responses to irrigation treatments.
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A unified, AI-driven platform transforming multi-source data and models into irrigation advice, scenario planning, and smart decisions.
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Workshops, training, and collaborative research ensure institutions and farmers convert scientific outputs into practical know-how.
Learn MoreThe WebAIS project spans across multiple interdisciplinary domains, integrating advanced environmental science with socio-economic insights to drive sustainable agricultural transformation.
