EchoDome - Passive Acoustic Early Warning Threat Detection

Anno’s solution, EchoDome, uses deep learning model architectures and additional algorithms to detect, classify, and track drones using low Size, Weight, Power, and Cost (SWaP-C) devices in a mesh architecture. Drone tracking components leverage signal embeddings and additional metadata to locate drones within the system's range of coverage (within the sensor grid). By converting acoustic signals into embeddings, we create a consistent and comparable representation of sounds that enables us to search through them effectively. The use of additional mesh communications among sensors, with each independent sensor performing all computations on its own and sharing its findings, allows quick and low-cost extension of the search perimeter. Our low power requirements enable this solution to be powered by portable solar equipment and standard power units, making it highly mobile and viable for tactical and combat ground vehicles.