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Acoustic Anomaly Detection Sensor Arrays are hardware-based acoustic sensing systems that monitor ambient and mechanical sound patterns to identify deviations over time. They support non-invasive detection of early mechanical, environmental, or ecological changes through continuous, interpretable audio capture.
Acoustic Event Recognition Sensors are audio-based perception systems that detect and classify sound events to identify activities, anomalies, or state changes that may not be visually observable. They complement visual sensing by enabling machine perception in low-visibility, enclosed, or sound-dominant environments.
Environmental multisensor nodes are compact hardware platforms that integrate multiple environmental sensors into a single unit to produce aligned, context-rich measurements of surrounding conditions. They enable holistic environmental awareness by correlating physical and chemical signals rather than reporting isolated readings.
Mobile Environmental Monitoring Robots are mobile robotic systems that collect environmental data such as air quality, temperature, and humidity across spaces, enabling spatially resolved insights that fixed sensors cannot provide. They combine mobility, sensing hardware, and AI-driven data interpretation to support applied environmental assessment in complex environments.
Mobile Inspection Robots are applied robotic systems that navigate industrial and infrastructure environments to collect consistent visual, thermal, acoustic, and structural data using onboard sensors and edge processing. They extend human inspection capabilities by enabling repeatable, data-driven observation in complex or hard-to-access sites.
Noise and Acoustic Monitoring Systems are persistent environmental sensing platforms that measure and record sound pressure levels and acoustic patterns in physical spaces to support environmental health assessment, compliance monitoring, and activity analysis across urban and industrial contexts.
Vibration-Based Acoustic Sensors detect and interpret acoustic events by sensing structure-borne vibrations rather than airborne sound, enabling reliable acoustic perception in noisy, concealed, or physically constrained environments. They are well suited for AI systems that require resilient event detection from mechanical or structural signals.
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