## 3 Results
### Estimation of the Number of Samples and Analysis of the Information
This is not the case for the organic residues for the two sensors, where a negative asymmetry is observed, thus establishing an indication of a higher concentration of readings for this type of residue between the Q1 and Q2 quartiles, a phenomenon that describes a higher incidence in the MT sensor. In turn, the readings related to plastic for the MT sensor slightly show a higher level of dispersion compared to the readings of the other reusable waste for both types of sensors. Additionally, it can be seen that the values corresponding to the median for the readings recorded by the MT sensor for reusable waste present a common value of approximately 25 [pF] in the three cases, an aspect that occurs similarly for the MNT sensor, where the waste related to plastic and glass describe a median value or Q2 of 35 and for metal, a value of approximately 32. For the particular case of organic waste, approximate values are obtained for the MT and MNT sensors of 200 and 660, respectively, with a higher level of dispersion for the case of the MNT sensors. The comparative statistical analysis of the MT and MNT sensors reveals significant differences in capacitance measurement for different materials, with the MNT sensor's performance standing out due to its greater dynamic range. For reusable materials (plastic, glass, and metal), both sensors show relatively homogeneous capacitance values, with similar means and low standard deviations. However, the 95% confidence intervals (CI) of the MNT sensors are slightly wider, which could be attributed to greater sensitivity in the measurement. For example, for glass, the MT sensor presents a CI of (24.538, 25.622), while the MNT sensor widens it to (34.227, 35.533), indicating a shift towards higher capacitance values and a more differentiated measurement between materials. For organic waste, the superiority of the MNT sensor is evident due to its ability to capture higher capacitance values and greater relative variability, thereby reducing the overlap with reusable materials. The MT sensor records a mean of 251.120 pF with a standard deviation of 120.823 and a wide CI of (203.757, 298.482), while the MNT sensor reaches a mean of 680,960 pF with a standard deviation of 324.396 and a CI of (553.799, 808.120). Not only does this demonstrate that the MNT sensor can more effectively differentiate organic waste from the rest, but its greater dynamic range, as quantified by the ratio of means to standard deviations (coefficient of variation), strengthens its classification capability. In organic waste, the coefficient of variation for the MT sensor is 48.1%, while for the MNT sensor it rises to 47.6%, indicating that, although both present high dispersions, the MNT sensor is more effective in separation thanks to its greater width in the distribution of values. Capacitance was selected as the sole characteristic for the sorting process due to its high sensitivity to the dielectric properties of materials. This sensitivity allows us to differentiate waste according to its composition in a quantitative way, since organic waste presents significantly higher capacitance values, attributed to its higher dielectric constant and inherent moisture content. In contrast, reusable materials such as plastic, glass, and metal show lower and more homogeneous capacitance values, given their reduced dielectric character. These behavior patterns are clearly evident in the results presented in Figures 8 and 9.