System and method for context aware networked mask with dynamic air impedance for optimum breathability

A processor implemented method for context aware networked smart mask with dynamic air impedance for optimum breathability, the method comprising:

• receiving, by one or more hardware processors of a master device, a plurality of environmental parameters and a plurality of biological parameters sensed by a plurality of sensors of a mask;
• processing, via an AI based Real time risk calculation module implemented by the one or more hardware processors, the plurality of environmental parameters, the plurality of biological parameters, ambient environment and context data of a wearer of the mask, meta data of the wearer and user inputs to generate a customized risk score, wherein the AI based Real time risk calculation module comprises Deep Neural Network (DNN) pre-trained on large multi-variate time series data, wherein the DNN has learnt from wearer context and geographical location place where the wearer has stayed for a period,
• wherein the actuator unit processes the customized risk score to generate the actuation signal that varies the stretch force applied by the actuator on each of one or more layers of the mesh network of the mask in accordance with the customized risk score to vary effective pore diameter of the mesh network, which in turn varies resultant air impedance to adjust breathability for the wearer,
• communicating, via the one or more hardware processors, the customized risk score to an actuator unit of the mask, wherein actuator unit processes the customized risk score to generate an actuation signal that varies a stretch force applied by an actuator on each of one or more layers of a mesh network of the mask in accordance with the customized risk score to vary effective pore diameter of the mesh network, which in turn varies resultant air impedance to adjust breathability for the wearer;
• and
• generating, via the one or more hardware processors, alerts for the wearer in accordance with the customized risk score and a set of predefined rules.

One or more non-transitory machine-readable information storage mediums comprising one or more instructions, which when executed by one or more hardware processors causes a method for context aware networked smart mask with dynamic air impedance for optimum breathability, the method comprising:

• receiving, by one or more hardware processors of a master device, a plurality of environmental parameters and a plurality of biological parameters sensed by a plurality of sensors of a mask;
• processing, via an AI based Real time risk calculation module implemented by the one or more hardware processors, the plurality of environmental parameters, the plurality of biological parameters, ambient environment and context data of a wearer of the mask, meta data of the wearer and user inputs to generate a customized risk score, wherein the AI based Real time risk calculation module comprises Deep Neural Network (DNN) pre-trained on large multi-variate time series data, wherein the DNN has learnt from wearer context and geographical location place where the wearer has stayed for a period,
• processing, via the one or more hardware processors and an actuator unit, the customized risk score to generate an actuation signal that varies the stretch force applied by an actuator on each of one or more layers of the mesh network of the mask in accordance with the customized risk score to vary effective pore diameter of the mesh network, which in turn varies resultant air impedance to adjust breathability for the wearer;
• and
• generating, via the one or more hardware processors, alerts for the wearer in accordance with the customized risk score and a set of predefined rules.