Environment-based-threat alerting to user via mobile phone

A mobile phone for alerting threats to users, comprising:

• a processor;
• and
• a memory, communicatively connected to the processor, storing processor executable instructions, which, in execution causes the processor to:
• receive a plurality of signals comprising at least one of Electro-Magnetic (E-M) signals and sound signals, from one or more sensors associated with the mobile phone, wherein the plurality signals are related to images and sound signals of an environment around the user;
• detect and classify one or more objects around the user by applying Convolution Neural Network (CNN) for the images and sound signals,
• wherein (i) Long Short-Term Memory (LSTM) is used to determine the objects using sound signals, and
• wherein (ii) Feature Pyramid Network (FPN) is used to identify the one or more objects by:
• generating image pyramids using bottom-up approach and top-down approach, and
• wherein (a) in the bottom-up approach:
• the spatial resolution decreases whereas semantics of features increases, and (b) in the top-down approach:
• the spatial resolution increases whereas the semantics of the features decrease;
• predict a threat to the user caused by the one or more objects around the user based on at least one of, one or more rules and an Artificial Model (AI) model;
• and
• generate one or more alerts based on the predicted threat posed by the one or more objects, wherein the one or more alerts are provided to the user to enable the user to avoid the threat.

A non-transitory computer readable medium including instructions stored thereon that when processed by at least one processor cause a a mobile phone to perform operations comprising:

• receiving a plurality of signals comprising at least one of Electro-Magnetic (E-M) signals and sound signals, from one or more sensors associated with the apparatus mobile phone, wherein the plurality signals are related to images and sound signals of an environment around the user;
• detecting and classifying one or more objects around the user by applying Convolution Neural Network (CNN) for the images and sound signals,
• wherein (i) Long Short-Term Memory (LSTM) is used to determine the objects using sound signals, and
• wherein (ii) Feature Pyramid Network (FPN) is used to identify the one or more objects by:
• generating image pyramids using bottom-up approach and top-down approach, and
• wherein (a) in the bottom-up approach:
• the spatial resolution decreases whereas semantics of features increases, and (b) in the top-down approach:
• the spatial resolution increases whereas the semantics of the features decrease;
• predicting a threat to the user caused by the one or more objects around the user based on at least one of, one or more rules and an Artificial Model (AI) model;
• and
• generating one or more alerts based on the predicted threat posed by the one or more objects, wherein the one or more alerts are provided to the user to enable the user to avoid the threat.