Innopolis University Debuts InnoDrone: A Wired Drone for Continual Traffic Monitoring
Innopolis University, located in the Republic of Tatarstan, has unveiled InnoDrone, a wired aerial drone designed to provide an uninterrupted power supply for traffic observation. The university’s press service shared details with socialbites.ca, highlighting the device as a potential alternative to conventional traffic control cameras while emphasizing its ongoing evaluation on public roadways.
InnoDrone is a quadcopter equipped with a high-definition video camera and a power cable that enables continuous operation. The tethered design allows the drone to remain aloft without relying on onboard power reserves, supporting sustained monitoring of airborne traffic conditions and incident response capabilities from a fixed vantage point.
Operational parameters include keeping the drone suspended at altitudes up to 20 meters via the tether, enabling around-the-clock surveillance in favorable weather. Practical constraints cover temperatures between -30 and 55 degrees Celsius (adjusted to current operational ranges), wind speeds not exceeding 10 m/s, and heavy rainfall conditions, during which performance may be limited. These limits reflect safety, reliability, and data integrity considerations for real-time traffic analysis.
A machine vision system aboard InnoDrone is capable of recognizing multiple vehicle classes, including buses, cars, trucks, and medium-sized vehicles. The system also autonomously detects behaviors such as deviations into the opposite lane, crossing a solid marker line, and movement across lane boundaries, while monitoring roadside and dividing lines for lane discipline. Such capabilities support automated traffic assessment, incident detection, and congestion management without constant human intervention.
The InnoDrone platform is currently undergoing road tests in Innopolis, a city within Tatarstan. The testing program focuses on assessing the reliability of continuous operation, the accuracy of vehicle-type recognition, and the system’s ability to interpret lane geometry under real-world conditions. The project is described as a collaborative effort aimed at exploring new approaches to traffic monitoring that could complement or substitute certain fixed-camera deployments in the future.
Innopolis University’s work on InnoDrone aligns with broader efforts to integrate robotics and machine-vision technologies into smart city ecosystems. By combining tethered power supply with advanced image analytics, the project seeks to deliver stable, scalable traffic surveillance solutions that can function across varied climates and road configurations. The current phase emphasizes data quality, system robustness, and the potential for safer, more efficient traffic management in urban and suburban environments.