Soteria is a powerful combination of sensing, real-time analytics, artificial intelligence (AI), and edge and cloud computing. It is the first occupational safety offering that utilizes ubiquitous sensing and analytics to keep workers safe while they perform essential job tasks. Soteria integrates data in real-time from a wide range of industrial wearables and environmental sensors to enable actionable outcomes and predictive analytics for its users. The system contains open API to integrate with GE and non-GE sensors, data storage, and flexible dashboards to view the actions and outcomes.
Soteria is poised to be the first Forge mission to run a commercial pilot in 2020. This mission is a perfect storm of technology, incorporating novel proprietary and third-party wearable sensors, smart environments, edge and cloud computing, and analytics assembled with occupational safety as a demonstration use case.
The team built a unique and fully integrated demonstration of how – in real time – they can fuse data from a multitude of sensors to build rich analytics that transcend what any single sensor can provide. They developed a system that allows them to pick specific sensors, specific form factors, and specific analytics, all to create a custom solution.
Key demonstrations/milestones:
- May 2020: Started a field demonstration in an industrial manufacturing facility.
- December 2019: Integrated dashboard enables side-by-side visualization of worker location, key safety data from multiple sensors, and alerts for hazardous situations.
- September 2019: Soteria is unveiled at the Enterprise Wearable Technology Summit in Dallas, TX, leading to inquiries from potential users and validating the need for such a system.
- April 2019: Initial occupational safety demonstration complete, including indoor position tracking, voltage and activity sensing and video analytics.
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Our Expertise
Capabilities utilized for Soteria project
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Software Development
Innovating software solutions in alignment with Agile & FastWorks principles to aid business digital transformation journeys
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Embedded Computing
Integrating computation with physical processes to create the joint optimization of algorithms, software and hardware
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Physical-Digital Analytics
Leveraging operational data, physical-based simulations and AI models to optimize production, improve quality, reduce costs and yield operational efficiency
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Industrial Software
Bringing robust software development practices to interdisciplinary engineering teams to realize faster and more profitable outcomes
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Enterprise Optimization
Optimizing design, operation, and supply chain decisions for complex business systems to improve yield and reduce costs
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Real-Time Optimization
Combining Digital Twins, market data, and optimization algorithms to create supervisory control algorithms that will maximize business outcomes
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Estimation & Modeling
Developing novel models for real-time use in controls, estimation and optimization
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Machine Learning
Developing and scaling machine learning solutions for industrial applications to facilitate continuous learning, adaptation and improvement in dynamic operating environments
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Computer Vision
Enhancing fundamental and applied research to mimic human visualization and interpretation
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