Neural Network-enabled Extreme Runtime Data Analytics (New-ERA)

AiRANACULUS, in association with Northeastern University proposes Neural Network-enabled Extreme Runtime Data Analytics (New-ERA) which enables extreme runtime data analytics using wearable devices. Our proposed New-ERA solution can be easily integrated/coupled with an existing hardware technology in the form of a fieldable, wearable device that will enable the onboard analyses of sleep and performance indicators and reduce both battery consumption and storage requirements, to meet the future need of the U.S. DoD and Office of Naval Research. Our solution leverages our recognized strong expertise, deep understanding and extensive working experience on (a) Commercially available wearable devices, that capture clinically important and relevant physiological parameters (b)  Analyses of information and data derived through continuous monitoring of wearable devices and developing AI/ML based predictive models for early indication of biological threats.(c) Strong experience in developing software applications and conducting efforts for programs  for US  DoD, US Navy. Our technology has been developed through wide variety of Navy (CAMICA, OSCAR, S2OS), Army (WADER), DTRA and IARPA programs. We leverage our deep knowledge and strong working experience of using Artificial Intelligence/ Machine Learning (AI/ML) approaches on the data / features extracted from COTS wearable device-based datasets to develop algorithms. In this proposal, we propose a software application New-ERA that will provide capabilities listed below. Greatly improve the ability to field wearable devices for long periods of time in disrupted, disconnected, intermittent and low-bandwidth environments; where understanding readiness state is critical, but ability for device recharging may not be operationally feasible. Incorporated with existing commercially wearable devices (e. g. Android) to enable continuous remote monitoring of physiological parameters in austere military environments, Easily integrate/couple with an existing hardware technology in the form of a fieldable, wearable device that enables the onboard analyses of sleep and physiological performance indicators that impact militarily relevant performance and reduces both battery consumption and storage requirements. Provide ability for onboard computing and processing of physiological monitoring data such as heart rate(HR), Heart Rate variability, sleep etc., utilizing emerging commercial applications, such as tinyML, to significantly reduce power consumption and data size. New-ERA will enable data to be formatted in a way that can be interpreted and ingested in a database agnostic manner and support rapid transmission to a local server. New-ERA will enable data transmission conducted via wireless (e. g. Bluetooth) means. The development of this technology will greatly improve the ability to field wearable devices for long periods of time in disrupted, disconnected, intermittent and low bandwidth environments.