The rapid proliferation of drones has introduced significant privacy and security challenges, making it essential to develop robust and efficient detection systems. Traditional methods often face tradeoffs in accuracy and environmental robustness. Integrated sensing and communication (ISAC) allows wireless devices to perform both data transmission/reception and sensing using the same hardware. In this article, we introduce the CommSense system, based on the application-specific instrumentation (ASIN) framework, which leverages existing communication signals without needing dedicated transmitters.

This makes CommSense a cost-effective, scalable, and regulation-free approach to drone detection. We first evaluated CommSense’s ability to detect environmental changes, achieving 97.7% accuracy in identifying scatterers (static objects). We then moved to a dynamic set-up and tested its performance in detecting a PixHawk drone in diverse environments—an academic building, lawn, parking lot, and playground—achieving good detection accuracies, ranging from 70% to 99.9% with varying distances. Receiver operating characteristic (ROC) curve analysis confirmed excellent performance, with AUC values exceeding 0.9 in most cases. We expanded our experiments by testing two more drones—DJI Mini 4 Pro and bigger PixHawk—at varying distances from 10 to 100 m.

The DJI Mini 4 Pro’s accuracy ranged from 99.7% at 10 m to 83.8% at 100 m, while PixHawk’s accuracy ranged from 100% to 81.9%. AUC values also dropped slightly as distance increased, confirming the expected performance variation with range. These results highlight the robustness of CommSense across different environments, drone models, and distances. Its advantages over traditional methods, like audio- and vision-based sensing, demonstrate CommSense’s potential as a practical solution to the growing security threats posed by widespread drone use.