BrainChild Innovation developed a proprietary web-based platform of Artificial Intelligence (AI) solutions for visual infrastructure inspections. The AI solution consists of Acute Anomaly Detection machine-learned models and algorithms using visual data to detect and report structural flaws and defects. Data collected by the client is processed through our smart solution using a private or cloud-based server providing them with immediate results for their Non-Destructive Testing procedures. These computer vision applications are developed using client datasets collected by sensors, including images, video, lidar, infrared (IR), ultrasonic sensor etc. The client’s dataset is analyzed through our streamlined platform for the asset type, operational status, and surface anomalies including cracks, corrosion, lightning strike damage using web or mobile application visualizations and reporting.
Unique Sales Proposition (USP)
Machine Learning and Deep Learning expertise
Quick enterprise AI solution prototyping and system integration
Deploy AI to unmanned and embedded systems
Predictive and Prescriptive Analytics
Our AI solutions
Acute Anomaly Detection
Object Detection
Guidance, Navigation and Control algorithm (GNC)
Benefits to Client-
Our edge-powered AI software solution enables computer vision capabilities and sensor integration with industry-leading embedded chipsets. Result visualization and reporting can be applied to either Web, Mobile or Mixed Reality devices. This process reduces clients need for certified inspector requirements and allows for additional end-to-end inspection solutions, including IoT, unmanned ground, aerial or underwater systems
“Get real-time Artificial Intelligence (AI) performance where you need it most with the high-performance, low-power NVIDIA Jetson AGX systems. Processing of complex data can now be done on-board edge devices. This means you can count on fast, accurate inference in everything from robots and drones to enterprise collaboration devices and intelligent cameras. Bringing AI to the edge
unlocks huge potential for devices in network-constrained environments.” (NVIDIA 2019)
