Abstract: Systems, methods, and apparatus are disclosed for omnimodal sensing, data fusion, and autonomous decision-making across physical and digital domains and further integrates a Multimodal Diagnostic System (MDS) and Impairment Recognition and Intervention System (IRIS) with defense architecture or a system architecture that can be compliant with the Modular Open Systems Approach (MOSA) and Sensor Open Systems Architecture (SOSA) to ensure interoperability. The system can utilize real-time multisensory fusion, cryptographic provenance via blockchain, and resilient magnetoelectric communication to support mission-critical decision-making across manned and unmanned platforms in denied or contested environments.

Abstract: A system or method of impairment recognition and intervention includes collecting sensor data using a vehicle sensor array, combining the sensor data using a sensor fusion module for initial data aggregation and synchronization from data collected from the vehicle sensor array to provide fused data and for combining processed data from all sensors into a unified state estimate, performing real-time analysis in detection of signs of impairment using a machine learning model or models that received the fused data as inputs, performing advanced data analysis, long term storage, and system management in communication with the machine learning model or models using a cloud processing and data storage component serving as a centralized platform, encrypting all stored data and encrypting communication with the cloud processing and data storage component using an encryption engine, and providing a tamper-evident log of critical events in detection of signs of impairment using blockchain technology.

Abstract: Systems, methods, and apparatus are disclosed for omnimodal sensing, data fusion, and autonomous decision-making across physical and digital domains. The disclosed architecture integrates biological-analog modalities including visual, auditory, olfactory, gustatory, and tactile sensors with symbolic or linguistic data sources such as text, structured records, or unstructured digital inputs. A data-fusion engine consolidates these heterogeneous streams into a unified context representation. A machine-learning inference model performs diagnostic, predictive, or safety-related reasoning from this representation. A distributed-ledger framework validates and preserves data provenance, and a resilient communication subsystem ensures command, control, and safety continuity through alternative channels such as cellular text, low-frequency radio, optical, acoustic, or magnetoelectric field-based transmission.

Abstract: A system and method of combining different sensor data for higher reliable diagnosis information on a portable mobile device includes using a camera for imaging a region of interest of a subject to obtain an image signal, a microphone for capturing acoustic information from the subject, and one or more processors. The one or more processors can be configured to spectrally analyze the image signal, estimate a first vital-sign of the subject corresponding to a diagnosis using the image signal, analyze the acoustic information, estimate a second vital-sign of the subject corresponding to the diagnosis using the acoustic information, and combine the first vital sign with the second vital-sign to provide a higher confidence level diagnostic of the diagnosis.

Abstract: A method, system and mobile device can be used by a subject in diagnosing a disease or virus or other illness. The system can capture and analyze olfactory information providing a diagnosis based on the olfactory information. The system can also capture and output biometric data corresponding to the subject and can further include at least one camera or video sensor that can result in a diagnosis or a microphone or other acoustic sensor that can result in another diagnosis. Other sensors providing other corresponding diagnoses can be included. A sensor fusion component can receive and combine the biometric data and the various diagnoses results and further determine a confidence score. An event record creator compiles the biometric data and the confidence scores to create an event record having a higher confidence score with respect to a final diagnosis result. A data storage device stores the event record.

Abstract: A system (10) for removing airborne pathogens can include a housing (1, 4, and 6) having at least one or more chambers, a bipolar ionizer (9A), at least one particle filter (8), and an ultra violet light radiation source (5A) residing in at least one or more chambers. Furthermore, the embodiments can include the use of a ventilation system which can include a fan (3) that draws in surrounding air at an intake (7A) and directs the surrounding air towards the at least one particle filter, the bipolar ionizer, and the ultra violet light radiation source before the ventilation system expels the surrounding air drawn through the intake through an exhaust vent (7B).

Abstract: A method, system and mobile device can be used by a subject in diagnosing a disease or virus or other illness. The system can capture and analyze olfactory information providing a diagnosis based on the olfactory information. The system can also capture and output biometric data corresponding to the subject and can further include at least one camera or video sensor that can result in a diagnosis or a microphone or other acoustic sensor that can result in another diagnosis. Other sensors providing other corresponding diagnoses can be included. A sensor fusion component can receive and combine the biometric data and the various diagnoses results and further determine a confidence score. An event record creator compiles the biometric data and the confidence scores to create an event record having a higher confidence score with respect to a final diagnosis result. A data storage device stores the event record.

Abstract: A system and method of combining different sensor data for higher reliable diagnosis information on a portable mobile device includes using a camera for imaging a region of interest of a subject to obtain an image signal, a microphone for capturing acoustic information from the subject, and one or more processors. The one or more processors can be configured to spectrally analyze the image signal, estimate a first vital-sign of the subject corresponding to a diagnosis using the image signal, analyze the acoustic information, estimate a second vital-sign of the subject corresponding to the diagnosis using the acoustic information, and combine the first vital sign with the second vital-sign to provide a higher confidence level diagnostic of the diagnosis.

Abstract: A system (10) for removing airborne pathogens can include a housing (1, 4, and 6) having at least one or more chambers, a bipolar ionizer (9A), at least one particle filter (8), and an ultra violet light radiation source (5A) residing in at least one or more chambers. Furthermore, the embodiments can include the use of a ventilation system which can include a fan (3) that draws in surrounding air at an intake (7A) and directs the surrounding air towards the at least one particle filter, the bipolar ionizer, and the ultra violet light radiation source before the ventilation system expels the surrounding air drawn through the intake through an exhaust vent (7B).