DADA joins Space East Cluster

DADA is pleased to announce that they are a new member of Space East Cluster, funded by New Anglia Local Enterprise Partnership and UK Space Agency. 

Space East is developing a thriving, innovative and engaged community of cross-sector businesses keen on exploring how their capabilities and expertise can access the opportunities presented by the £17.5bn UK space sector.

Enrolment to Space East, gives us access to the latest funding, project and consortia opportunities as below:

• Innovate UK Edge Access Grant Funding and Expert Support 
• Navigation Innovation Support Programme (NavISP)
• Student support: ESA microgravity programmes
• European Space Agency (ESA)
• Space for Infrastructure
• Business Applications and Space Solutions Programme (BASS)
• Unlocking Space for Business
• Accelerating Investment Opportunity
• Innovate UK Agri- Tech and Food -Tech Launchpad
• Direct Negotiation – Generic Programme Line
• Commercial Applications Enabled by Space Environments
• SPACE4RAIL
• Space for Olympic Games

DADA were featured in their Newsletter, on how you can create a ‘risk radar’ to monitor hidden risks through:
✅ Use AI to plot risks and how they develop over time using Time-Series Data Analysis
✅ Automated Asset Inspections with Machine Learning
✅ Creating a ‘unified’ AI/ML platform spanning cloud services and data assets between Delivery Partners

How DADA can add value to Space East Cluster members

Automated Asset Inspections with Machine Learning

DADA can simplify anomaly detection models to automatically flags critical incidents. Machine Learning (ML) powered automated data analysis tool for general inspection that enables predictive maintenance by providing consistent and reproducible results.

Automatic identification of rare items, events, or observations in data

Anomaly Detection is the identification of rare items, events, or observations in data that differ significantly from the expectation. This can be used for several scenarios like asset monitoring, maintenance, and prognostic surveillance in industries such as utility, aviation, and manufacturing.

The Anomaly Detection Service will create customized Machine Learning models, by taking the data uploaded by users, using MSET algorithm, which is a multivariate anomaly detection algorithm to train the model, and deploying the model into the cloud environment to be ready for detection. Users can then send new data to the detection endpoints to get the detected anomaly results.

Potential benefits:

• Moving humans away from harm and hazardous environments.
• Intelligent infrastructure – supports efficiency and repeatability of traditional asset examination methods leading to reduced cost, improved productivity, better understanding of asset degradation.
• Digital delivery supports move to predictive maintenance regime & decision making.