Global Technology Connection, Inc.
Small research and development company based in Atlanta, GA focused on system modeling and simulation, data analytics and machine learning, digital twins, IoT/IIoT sensor integration, prognostics & health management, and applied R&D for government and commercial clients. Works across cyber-physical systems (satellites, UAVs, ground vehicles, industrial equipment) to develop algorithms, software, and engineering solutions for anomaly detection, fault isolation, and operational optimization.
Industries
N/A
Nr. of Employees
small (1-50)
Global Technology Connection, Inc.
2839 Paces Ferry Rd, Overlook II, Suite 1160, Atlanta, GA 30339
Products
Adaptive real-time anomaly detection and identification for sensored systems
Method that builds runtime models between battery telemetry and system operational variables to detect and isolate anomalies using unsupervised, self-adapting algorithms suitable for battery-powered vehicles and platforms.
Adaptive real-time anomaly detection and identification for sensored systems
Method that builds runtime models between battery telemetry and system operational variables to detect and isolate anomalies using unsupervised, self-adapting algorithms suitable for battery-powered vehicles and platforms.
Services
Contract R&D focused on algorithmic and software solutions that combine data, physics, and expert knowledge to automate decision-making in complex engineering systems.
Design and implementation of unsupervised and adaptive anomaly detection algorithms and FDI workflows for onboard and ground-based deployments.
Integration of sensor suites, data acquisition drivers, and data-processing notebooks for remote monitoring projects.
Development of model-based enterprise workflows aligned with measurement and MBD/QIF standards, including point-cloud inspection and uncertainty quantification.
Contract R&D focused on algorithmic and software solutions that combine data, physics, and expert knowledge to automate decision-making in complex engineering systems.
Design and implementation of unsupervised and adaptive anomaly detection algorithms and FDI workflows for onboard and ground-based deployments.
Integration of sensor suites, data acquisition drivers, and data-processing notebooks for remote monitoring projects.
Development of model-based enterprise workflows aligned with measurement and MBD/QIF standards, including point-cloud inspection and uncertainty quantification.
Expertise Areas
- System modeling and simulation
- Digital twin development
- Data analytics and machine learning
- Prognostics and health management (PHM)
Key Technologies
- Machine learning / deep learning
- Digital twins
- IoT sensor telemetry
- Battery telemetry-based anomaly detection
News & Updates
Presented on unsupervised and adaptive anomaly detection in sensored systems.
Presentation on unsupervised anomaly detection using batteries in electric aerial vehicle propulsion test-bed and attendance at PHM conferences.
Presentation on MCMC and deep learning for seismic phase association.
Published repository and instructions showing hardware requirements and Python scripts for industrial soil moisture and temperature sensors.
NAVAIR award to develop digital twin technologies for naval aircraft sub-systems to monitor health and predict future performance.
Award to develop deep learning-based seismic analysis tools for nuclear event monitoring and seismic event classification.
Presented on unsupervised and adaptive anomaly detection in sensored systems.
Presentation on unsupervised anomaly detection using batteries in electric aerial vehicle propulsion test-bed and attendance at PHM conferences.
Presentation on MCMC and deep learning for seismic phase association.
Published repository and instructions showing hardware requirements and Python scripts for industrial soil moisture and temperature sensors.
NAVAIR award to develop digital twin technologies for naval aircraft sub-systems to monitor health and predict future performance.
Award to develop deep learning-based seismic analysis tools for nuclear event monitoring and seismic event classification.