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This research presents the design and testing of an automatic color detection system using TCS3200 color sensor integrated with Arduino Uno microcontroller. The system was developed and tested using Wokwi virtual simulation platform before physical implementation. The TCS3200 sensor converts RGB light intensity reflected from objects into frequency signals, which are processed by Arduino Uno to classify colors into red, green, and blue categories. The system incorporates audio feedback using DFPlayer Mini module to provide sound notifications for detected colors. Testing results show that the system can accurately detect and classify primary colors with frequency-based thresholds: red (R<48 &R>37 & G<95 & G>85), blue (G<75 & G>65 & B<33 & B>23), and green (R<55 & R>40 & B<25 & B>5). The simulation validation demonstrates stable performance with consistent color recognition capabilities, making it suitable for industrial sorting applications and assistive technology for visually impaired individuals.

Design and Development of an Internet of Things (IoT)-Based Fish Freshness Detection Device. Guided by Mrs. Henna Nurdiansari, S.T., M.T., M.Sc. and Mrs.  Monika Retno Gunarti, S.Si.T., M.Pd. Indonesia has a great potential in fish production, reaching 12 million tons annually, accompanied by an increase in fish consumption. However, significant challenges arise regarding food safety, especially concerning the sale of non-fresh fish and the presence of formalin. As an innovative solution, a fish freshness and formalin detector based on IoT was developed. This device utilizes the TCS3200 sensor to detect color intensity and the HCHO sensor to detect formalin. This research employed the Research and Development (R&D) method to produce an effective detection device. When the LED is green without a buzzer sound and the LCD displays "Fresh Fish" or "Formalin Free," the fish can be confirmed to be fresh and free of formalin. However, if the LED is red, the buzzer turns on, and the LCD displays "Non-Fresh Fish" or "Fish with Formalin," the fish is considered to be below standard or contains formalin. The device categorizes fish condition into three groups: green (fresh), yellow (less fresh), and red (not fresh), reflecting the fluctuating freshness level. When the HCHO sensor reads a value above 0.5 ppm, the fish is considered to contain formalin, while below 0.5 ppm is considered safe and free from formalin. Therefore, this device can be an effective solution in detecting fish freshness and formalin content, ensuring food safety for consumers.

Technological developments encourage changes in the way decisions are made. In terms of stopping the application of urea fertilizer, farmers still rely on BWD observations. In this study, using the RnD method by directly observing the research location in the farmer group Gapoktan, in the village of Tosari, Kendan district and analyzing the problem then making a prototype which will be tested by experts. In this study, a tool was made using NodeMCU with TCS3200 sensor to detect color, which was then sent via the internet to the database using IoT technology. In this study, using several trials with different parameters of urea fertilizer use and the results of the TCS3200 sensor can detect colors according to what is on the BWD and send data to the database via the internet. In this system, farmers can recommend the use of suitable urea fertilizers outside a certain area so as to minimize errors in the observation on BWD, this will make the use of urea fertilizer to be the right dose.  

Recent technological developments determine humans to be creative in creating tools that implement technology in it with the aim of facilitating human tasks in daily activities. Inappropriate use of fertilizers can cause losses, both losses on fertilizer, on plants, as well as on the soil and the environment around fertilization. Losses on plants such as unhealthy plant growth and susceptible to disease pests, plant yields are not as expected or low. From the background above, the writer found an idea to create a system or tool that can help farmers in determining the dose of Nitrogen fertilizer in their rice plants, through the storage of the dosage data of each land. The user did five scans, from each scan producing RGB values, each RGB value from five samples was then matched with the BWD dose color indicator. The sample dose results are then sent by the NodeMcu microcontroller to the webserver database. Based on the assessment of the test conducted by 10 Users by Gapoktan Farmers Group of Tosari Kendal Village, the total value of 372 that has been averaged to be 37.2 is between 31 - 40 which is classified in the category of "Very Valid or Very Effective".