Light Monitoring System using Z-Score Analysis

In today’s modern world where everything is being automated and security is a growing concern, we made an automated module to live-monitor the anomalies in any provided space at all times to ensure security in our personal space. By implementing our project, we can monitor anything important which would be out of our reach at the moment with a live alert system through which we can identify any anomalies. In our proposed system we integrated Machine Learning to work with an IoT system by using Bolt Wi-Fi module which also uses an LDR sensor to detect the light intensity, here LDR is used specifically to better understand the Z-Score analysis. We are using ML to do an analysis known as Z-Score, which processes a math equation to detect anomalies. This analysis is done to predict a frame of upper and lower boundaries for the light intensity. Eventually, when the LDR sensor value i.e., light intensity goes out of range in a room, it generates Real-Time alerts in the form of an SMS alert which will be directed to the user's mobile phone through Twilio. This alert system is an advanced way to increase the work efficiency of any live monitoring system as the ML is always working to increase accuracy. In our project, this system specifically uses Light Dependent Resistor to detect changes in light intensities, but this can be implemented for any sensor to detect.