System and method for sensor-based environmental detection

A method of anomaly detection, comprising:

• recording an environmental reading from a sensor according to a time-step, wherein the sensor is selected from the group consisting of a gas sensor, a force sensor, a humidity sensor, a sound sensor, and a vibration sensor;
• transmitting the environmental reading to a main device according to the time-step, wherein the main device accumulates and stores a plurality of environmental readings according to the time-step,
• triggering, via circuity of the main device, a machine learning model when a count of the plurality of environmental readings reaches a threshold number of readings;
• identifying, via the machine learning model, an anomaly reading;
• categorizing, via the machine learning model, the anomaly reading into a positive anomaly reading, a negative anomaly reading, or an uncertain anomaly reading, wherein the anomaly reading is transmitted and stored in a cloud storage;
• transmitting, via a wide area network, the positive anomaly reading from the cloud storage to an end user communications device when the anomaly reading is the positive anomaly reading, wherein the end user communications device generates a first confirmation signal to confirm the positive anomaly reading, wherein the machine learning model is retrained on the plurality of environmental readings coupled with the first confirmation signal;
• returning the environmental reading to the main device from the cloud storage when the anomaly reading is the negative anomaly reading, wherein the machine learning model is retrained on the plurality of environmental readings coupled with the negative anomaly reading;
• transmitting, via the wide area network, the uncertainty anomaly reading to the end user communications device, wherein the end user communications device generates a second confirmation signal to confirm the anomaly reading as the positive anomaly reading or the negative anomaly reading;
• wherein the machine learning model is retrained on the plurality of environmental readings coupled with the second confirmation signal.