Artificial Intelligence/Machine Learning
Meeting Customer Missions with Clarity and Speed
ENSCO is transforming the speed and agility of customer missions by applying transparent Artificial Intelligence/Machine Learning (AI/ML) to deliver faster, more secure and more reliable understanding of data from noisy, unstructured sensing environments.
We combine our technology, domain and subject matter expertise to help customers realize the transformative power of AI/ML — whether that’s increasing safety in surface transportation, improving situational awareness in missions of national security or streamlining business processes to maximize efficiencies.
Our AI/ML offerings blend more than 50 years of customer mission partnership in national security, avionics, aerospace and transportation with our elite AI/ML team of experts to provide our customers dramatically higher levels of safety and security by making sense of vast amounts of data to improve productivity and decision-making.
ENSCO’s autonomous signals intelligence (SIGINT) collection capabilities provide detection and classification of complex Radio Frequency (RF) signals in dense RF environments. This capability operates on low-SWaP platforms and can be updated quickly as new and emerging threats are encountered.
RF detection and classification using AI offers the ability to quickly scan for new signals, and to capture, annotate and train Convolutional Neural Networks, enabling detection and classification in real time while mitigating deficiencies.
ENSCO AI/RF/Software-Defined Radio (SDR) capabilities support a wide range of applications, including situational awareness for multiple complex environments:
- NAVWAR
- GPS/comms jamming
- RADAR warning
- Pattern-of-life monitoring
- Time-sensitive targets — fast threat detection
- Cooperative/uncooperative communications detection in complex RF environments
- Real-time detection of unknown signals
ENSCO presents at the Institute of Navigation (ION) ITM/PTTI:
ENSCO’s railway inspection capabilities include autonomous inspection of railway track conditions using machine-vision and deep-learning algorithms on 2D images collected from moving revenue service railcars. The technology identifies anomalies in track and defective conditions such as missing or broken components. AI/ML gives our customers the ability to assess vast amounts of track consistently, accurately and efficiently. AI techniques are automatically run on the incoming data to make decisions on the validity of the measurement signals before sending maintenance notifications to railway workers in the field.
Quickly identifying and classifying air mass composition in order to predict the presence of particular airborne chemicals is of critical importance to national security efforts.
Air mass classification is traditionally performed by expert meteorologists, who manually analyze raw weather observations on daily maps.
To streamline and improve air classification, ENSCO applies a sophisticated AI/ML algorithm to automatically assign air mass labels to data ingested by sensors at locations of interest. This virtually eliminates the need for manual analysis and saves time for more critical tasks. Meteorologists can correct the algorithm-assigned labels, which are then saved for periodic, automated retraining and optimization of the algorithm for continual improvement in its performance. ENSCO’s machine-learning algorithm can be seamlessly integrated into legacy data pipeline and display software, meaning our AI/ML solution is cost- and time-effective.
