Objectives of the service
The collaborative solution from Krucial, SAS and Deep planet aims to address critical water quality and quantity stress in global catchments. Users face challenges such as agricultural runoff, urban development, and climate change impacts leading to variable water availability and quality. Our solution leverages advanced IoT sensors, satellite imagery, and data analytics to provide real-time monitoring of water stress indicators. The project seeks to enhance water management practices, supporting sustainable use and regulatory compliance. By integrating in-situ and remote sensing data, we offer a scalable and adaptive tool for proactive water resource management, benefiting communities, governments, and industries.
Users and their needs
The project targets government agencies, researchers, NGOs, agricultural businesses, and aquaculture operators in the UK and potentially other regions. The user communities face challenges such as water pollution from agricultural runoff, variable water availability, and compliance with regulatory requirements.
Our solution addresses these needs through:
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Real-time monitoring of water quality and quantity.
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Predictive models for flood and drought management.
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Integration of in-situ and satellite data for comprehensive analysis.
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Tools for regulatory compliance and sustainable water management.
The main challenge is ensuring the solution's adaptability and accuracy across diverse geographic and regulatory environments.
Service/ system concept
Our solution provides users with real-time water quality and quantity data, such as pollution levels from agricultural runoff and flood prediction models. The system integrates data from IoT sensors and satellite imagery, processed through advanced analytics to offer actionable insights. Users can access these insights via a centralised platform that displays key indicators and trends.
The system architecture includes:
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Data Collection: IoT sensors gather in-situ data (e.g., dissolved oxygen, temperature, nitrate levels).
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Satellite Imagery: Remote sensing data provides a broad overview of water conditions.
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Data Processing: Both data types are processed and analysed using machine learning algorithms.
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User Interface: A dashboard presents the information, enabling users to monitor water stress and make informed decisions.
This holistic approach ensures comprehensive and accurate monitoring, helping users address water management challenges effectively.
Space Added Value
Our project utilises Earth Observation (EO) data from satellites, such as optical, thermal, and Synthetic Aperture Radar (SAR) imagery, to monitor water quality and quantity across vast areas. Combining EO data with in-situ IoT sensors offers a comprehensive view of water basins, providing high-resolution, continuous monitoring.
The added value of using space assets includes:
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Coverage: Satellite data offers near-global coverage, including remote and inaccessible areas.
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Consistency: Regularly updated EO data provides consistent, long-term monitoring.
Integration: Combining EO and in-situ data ensures a detailed, accurate analysis.
This approach surpasses current methods by delivering comprehensive, scalable, and reliable water monitoring solutions.
Current Status
The project has achieved significant progress. We have finalised user and technical requirements. A comprehensive system compatibility assessment has been completed, leading to the design of the system and service architecture. We have finalised our IoT devices and identified two customers (farmers in Ayrshire, Scotland) to participate as test sites for the demonstration phase. Commercial discussions with potential end users are ongoing. Having passed the Critical Design Review (CDR) in June, the project is now transitioning into Solution Development, marking a critical step towards real-world implementation and testing.
Prime Contractor(s)
Subcontractor(s)
