Bellum Smart Sensors provides embedded and surface-mounted pavement monitoring solutions for airport runways and taxiways using Fiber Optic, MEMS, and NEMS sensors. The system transmits real-time data on saturation, load pressure, and temperature, which is analyzed by AI and machine learning to predict pavement health and potential failures. This proactive data enables precise maintenance scheduling, extending pavement lifespan and reducing aircraft damage and operational costs.
Funding
Funding not disclosed
Founders
Product
Problem
Airport runways and taxiways require continuous monitoring to prevent structural failures, which often become apparent only after significant damage has occurred. This reactive approach leads to escalating maintenance and repair expenditures and can compromise operational safety.
Solution
Bellum Smart Sensors offers an embedded sensor system for real-time pavement condition monitoring, particularly during construction phases when critical issues often emerge. The system collects data on saturation, water content, movement, temperature, and load pressure using technologies such as Fiber Optic Sensors (FOS), MEMS, and NEMS, transmitted wirelessly. Proprietary AI and machine learning algorithms analyze this data to generate predictive reports on pavement health and potential failure points, considering factors like weather and traffic loads. This enables proactive maintenance scheduling, extending pavement lifespan and reducing unexpected repair costs.
Target Audience
The primary customers are airport authorities, runway construction companies, and civil engineering firms responsible for the maintenance and integrity of airport infrastructure.
Features
- Embedded and surface-mountable sensors for pavement condition monitoring.
- Utilizes Fiber Optic Sensors (FOS), Micro-electro-mechanical Sensors (MEMS), and Nano-electro-mechanical Sensors (NEMS).
- Real-time data acquisition of saturation, water content, movement, temperature, and load pressure.
- AI and machine learning-driven analytics for predictive failure modeling.
- Analysis of data against environmental and operational loads.
- Remote dashboard application for data visualization and reporting.
- Enhanced warranty accountability through early defect detection.
- Extension of pavement lifespan through precise, proactive maintenance.
- Reduction in labor costs associated with manual inspections.
- Mitigation of aircraft damage risks from pavement defects.