SIGMA Chemical Recon and Meteorology (SCRAM) - Persistent Wide-Area Networked Detection of Chemical Threats

The SCRAM sensor represents a single active node in a networked sensor capability that employs the SIGMA architecture to provide persistent wide-area monitoring of chemical warfare agents and toxic industrial chemicals. Chemical measurements and meteorological data from multiple SCRAM sensors are wirelessly transmitted to a centralized, cloud-based processing center. Network-based urban-dispersion algorithms within a Bayesian data fusion framework enable the detection, identification and localization of chemical threat releases. A multi-SCRAM system has the ability to map affected areas and forward- propagate cloud behavior for a wide variety of hazardous airborne chemicals. SCRAM sensors can be deployed in static and mobile configurations to provide optimal coverage capabilities. The system operates completely autonomously and reports detections to the SIGMA network.

SCRAM Sensor sm

SCRAM Sensor Configurations

SCRAM sensor unit deployed under various configurations

SCRAM offers several features and performance advantages:

  • Utilizes US DoD selected Smiths LCD 3.3 (Joint Chemical Agent Detector) for detection of chemical agents and hazardous chemicals.
  • Improves sensitivity of LCD 3.3 through use of optimized on-board chemical detection and identification algorithms
  • Chemical and wind readings are fused across a distributed network to improve detection, estimate threat likelihood and significantly reduce false alarms.
  • Real-time cloud-based urban dispersion modeling with updates every 15 sec to track cloud in affected areas
  • Ruggedized autonomous detector package capable of static and mobile deployments

For more information on the capability, please refer to a Popular Mechanics article: “How We’ll Stop Chemical Attacks” by Dan Dubno, April 28 2019 (https://www.popularmechanics.com/technology/a27243679/device-will-stop-chemical-attack/)


Request the SCRAM brochure and technical specifications.