Vectigo provides an In-Road Communications Network (ICN) that uses solar-powered IoT devices to collect real-time traffic and environmental data. This data is processed by AI analytics to offer insights for infrastructure planning and traffic management, while integrated dynamic illumination enhances road safety and supports driver-assistance systems.
Funding
Funding not disclosed
Founders
Product
Problem
Traditional road infrastructure lacks real-time data collection capabilities, hindering efficient traffic management and proactive safety interventions. This data deficit impedes informed decision-making for infrastructure planning and leaves roads vulnerable to unaddressed environmental and traffic-related hazards.
Solution
Vectigo deploys an In-Road Communications Network (ICN) utilizing solar-powered IoT devices, referred to as SmartEdge PODs, to capture continuous traffic and environmental data. These PODs facilitate two-way communication with a centralized data hub, enabling real-time data aggregation. Proprietary AI-driven analytics process this data to generate actionable insights for infrastructure planning and traffic management. The network also integrates dynamic illumination features that respond to traffic incidents and environmental conditions, enhancing road safety and supporting advanced driver-assistance systems like Lane Keep Assist.
Target Audience
Vectigo targets municipal transportation authorities, urban planners, and infrastructure development firms seeking to enhance road safety and operational efficiency through real-time data and intelligent systems.
Features
- Solar-powered, in-road IoT devices (SmartEdge PODs) for continuous data acquisition.
- Two-way communication between PODs and a centralized Network Operations Centre.
- Integrated dynamic illumination with auto-response capabilities to traffic and environmental events.
- Lane Keep Assist (LKA) functionality through precise lane boundary identification.
- AI-driven analytics for predictive modeling of traffic flows, usage patterns, and road conditions.
- Anomaly detection algorithms to identify and alert on unusual data patterns.
- Adaptive learning models that enhance insight accuracy over time.
- Automated reporting features for real-time data summaries.
- Compatibility with both asphalt and concrete road surfaces for urban and rural deployment.
- Sustainable design utilizing recyclable materials and solar energy.