RoadEO develops a global road quality monitoring and prediction platform that utilizes crowdsourced smartphone data, in-vehicle sensors, and satellite imagery to assess road conditions. This technology enables public road authorities and construction firms to identify maintenance needs more accurately and cost-effectively than traditional methods, enhancing road safety and reducing operational downtime.
Funding
$50K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Traditional road quality monitoring relies on specialized vehicles and visual assessments, which are expensive and can be less accurate in detecting early signs of road wear and structural damage. Public road authorities and construction firms need a more cost-effective and data-driven approach to identify maintenance needs and optimize resource allocation.
Solution
RoadEO offers a road quality monitoring and prediction platform that leverages crowdsourced smartphone data, in-vehicle sensors, and satellite imagery to provide insights into road conditions. By combining these diverse data sources and applying artificial intelligence algorithms, RoadEO detects road wear and structural damages more efficiently than traditional methods. The platform enables public road authorities and commercial construction firms to make informed decisions about maintenance scheduling, maximizing road safety, reducing operational costs, and minimizing downtime for repairs.
Target Audience
RoadEO's primary customers are public road authorities and commercial construction firms responsible for road maintenance and infrastructure management.
Features
- Mobile app for crowdsourced road quality monitoring using smartphone sensors
- Integration of in-vehicle sensor data for real-time road condition assessment
- Analysis of satellite earth observation data to complement ground-based measurements
- AI-powered algorithms for quantifying and predicting road damages
- Identification of road wear and structural damages