Weapon usage monitoring system having discharge event monitoring using neural network analysis

A system for providing discharge monitoring of a firearm, the system comprising:

• a first sensor disposed on the firearm that senses (i) first, second and third accelerations and (ii) first second and third rotations, wherein the first, second and third accelerations are sensed along first, second and third axes, respectively and the first, second and third rotations are sensed around the first, second and third axes, respectively;
• an event detection module that receives signals from the first sensor indicative of the first, second and third accelerations, wherein the event detection module is configured to:
• calculate an acceleration vector magnitude from the acceleration signals;
• compare the acceleration vector magnitude to a threshold acceleration;
• assign a candidate event to the acceleration vector magnitude based on the comparing, the candidate event comprising the acceleration input signals and the rotation input signals for a predetermined duration of time;
• receive, at a machine learning module, the sample event candidate;
• determine an occurrence of a shot based on the acceleration and rotation input signals in the sample event candidate.