# Battery-Free Pork Freshness Estimation Based on Colorimetric Sensors and Machine Learning
## 4 RF Harvesting Experiment
### Kalman Filter for RF Harvesting Evaluation
Finally, an I2C (Inter-Integrated Circuit) communication module was employed for sensors. To compare the value of the sensors measured using the proposed smart-sensor tag system, pork purchased at a nearby mart was observed for 5 days, which is the same as the measurement time of this system. Several samples were simultaneously measured for continuous monitoring. The measured samples are shown in Figure 10. The average room temperature was 26 \({}^{\circ}\)C.

In this study, machine learning used data obtained from a low-cost RGB sensor, and the HSV conversion was conducted as follows. ### Changes in the Color Space of RGB to HSV

The RGB color model is the only color model recognized by humans, based on the Tristimulus theory. In computer vision and image processing approaches, the RGB value is often converted into the HSV color model, which consists of Hue, Saturation, and Value [30; 31]. Hue indicates pure color, Saturation indicates clarity in color depth, and Value indicates brightness. Hue is arranged at a 360\({}^{\circ}\) angle in a circle, with colors combined. As the center axis rises, the Value becomes greater, and the higher the Value, the brighter the color becomes. Saturation is centered on the center axis to the edge, with the color becoming clearer the farther it is from the center axis. Both Value and Saturation have values between 0 and 1. Since the Value's value is separated compared to the existing RGB model, the HSV model can be used to measure changes in color brightness. Thus, the HSV model is commonly used in computer vision. When the Value's value is 0, it indicates black, and when it is 1, it indicates white. Furthermore, the area of HSV is composed of Hue, Saturation, and Value, and since the factor of Hue does not change significantly despite changes in lighting, it is commonly used in color detection. The color difference can be determined sensitively using Euclidean distance. The HSV cone model can be used to determine the distance between the coordinates of the converted space after obtaining the space coordinates for H, S, and V.

### Reference Data of the Degree of Rotten in the Storage of Livestock Products in Summer

The Korea Consumer Agency discovered that when livestock products were stored without refrigeration in the external (33 \({}^{\circ}\)C) and trunk (43 \({}^{\circ}\)C) areas of vehicles during summer, bacteria began to multiply after 4 h and continued to do so after 6 h. Furthermore, it reached 5 in 10\({}^{6}\) CFU/g (CFU represents the number of bacteria), indicating the initial

Figure 10: Pork measured through the camera. stage of decomposition [32; 33]. Additionally, the Korean Ministry of Food and Drug Safety researched and investigated the distribution of Salmonella bacteria and changes in their numbers after raw chicken was injected with Salmonella and stored at refrigerated temperatures (4 \({}^{\circ}\)C) and room temperatures (25 \({}^{\circ}\)C) for 4 h and 12 h, respectively [24]. In the study, a change in the distribution of Salmonella was discovered by analyzing the metagenome (an aggregate of the genomes of all microorganisms) present in the environment (such as raw chicken and pork) using next-generation sequencing equipment. Moreover, the genetic analysis approach (RT-PCR) was used to identify changes in the number of Salmonella bacteria. According to the study, when raw chickens were stored at room temperature, the distribution of Salmonella and the number of bacteria increased. The change in the distribution of Salmonella indicated little change in raw chicken kept refrigerated for up to 12 h, but increased 1.3 times compared to the refrigerator's temperature when stored at room temperature for 4 h and tripled when stored for 12 h. Compared to refrigerated storage, Salmonella bacteria increased 3.8 times after 4 h and 14 times after 12 h when stored at room temperature. Figure 11 shows an average of multiple measurements taken during the months of July and August, which indicate a similar pattern.