Monitoring and Early Detection Infrastructure Crafter (MEDIC)

Monitoring and Early Detection Infrastructure Crafter (MEDIC) focuses on developing an autonomous aerial drone system to survey urban infrastructure and identify structural hazards. Utilizing a commercial off-the-shelf drone, the primary objective is to engineer an embedded computer vision and software architecture to proactively detect street-level defects, such as potholes, and building anomalies like failing scaffolding or loose brickwork. This involves integrating optical sensors alongside custom machine learning algorithms in C++ and Python to analyze visual data, aiming to minimize reactive municipal 311 citizen reports. Key project deliverables include a customized aerial sensor payload, a closed-loop autonomous control algorithm for automated city block surveying, and a cloud telemetry pipeline that transmits real-time hazard classifications and GPS fault coordinates to an enterprise dashboard. Ultimately, MEDIC provides a reliable, data-driven computer engineering solution that enhances urban maintenance, mitigates public safety risks, and streamlines municipal repair deployments.