ALTEN India was engaged by a leading aircraft manufacturing OEM to support in enhancing passenger comfort in an air cabin environment. Air travel often restricts passenger experience due to limited space and movement. The first step toward designing for comfort is understanding the factors—both internal and external—that influence in-flight comfort.

Challenge:

The client faced a major challenge in maintaining consistent cosmetic quality across cabin seats due to the complexity of the inspection process, which involved 32+ checks per seat. With a high volume of seats to inspect, the workload became overwhelming for human inspectors.

Solutions: ALTEN developed an AI-based suite of intelligent image preprocessing and object detection modules, integrated into the client’s annotation pipeline. The algorithm was designed to detect and process raw image data from aircraft interiors using

• Deep Learning (DL) Networks: for precise seat identification
• Region of Interest (ROI) extraction: (focused on seat covers)
• Advanced Image Preprocessing: noise reduction (Gaussian/median filters), contrast/edge enhancement
• Detailed Texture Analysis: Gray-Level Co-occurrence Matrix (GLCM) for feature extraction (contrast, correlation, energy, homogeneity)
• High-accuracy Image Segmentation: defect identification (waviness, wrinkles, undulations)

Benefits: ALTEN designed and implemented an innovative AI-driven system aligned with Cabin Safety requirements (regulatory documents, accident data, and safety benefit analysis). This included a detailed evaluation of potential threats, supported by literature referenced as per Regulatory Impact Assessments suggested by the client.