 Basically, we are using, we are syncing a mobile app to monitor the glucose level. This is done by a peripheral device, which basically works in the mechanism of ferro-signate being converted into peri-signate, and then gets the electrons, plots a waveform, and gives it in terms of an audio signal. That audio signal is taken into the phone by the audio jack. This is in PWM, but when it comes to the phone, it's an analog signal. Now, we can plot the signal to get the required data, but if you want to store it for future use, we need to convert it into PCM, which is pulse-coated modulation. This leads to loss in data, so we have developed an algorithm for now by which we are reducing the loss in data by quite significant amount. This basically works in the fact that when you have the midpoint values, the error is maximum. So, we have two separate binary arrays. We just get us to these error points. So, if this error point is reached, we store a high value, and when we reconstruct the signal, we take the error matrix into consideration, and thereby we get a signal which is much closer to the real signal. That's why another target of our app is to make PWM while converting from PCM to PWM. For each and every conversion, electronic data will be some loss. For example, when you are converting an analog to digital to analog, there will be some data loss. So, when we come to the point of the medical tracking system or some other system, we are sure we need to eliminate the data loss as to our values. That's the thing we are going over with the other process. As my friend, he told that we have derived an algorithm for data loss to reduce the data loss in quantizing error. Mainly when a data analog signal is converted into digital signal, surely there will be a sampling. After sampling, we should quantize the sampled data. So, while quantizing, we will find some values which will be considered as quantizing error up to the quantizing level. Up to our algorithm, when we compare to the normal quantizing rate of 0.01 or some other things, we have shorted out up to 20% of quantizing error. So, we are sure that we will do the error-producing MPCM to PWM2. We are struggling up to it. We will see the proof.