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Borkar, Harshita. "A Review on Arduino Based Color Sorting Machine." International Journal for Research in Applied Science and Engineering Technology 10, no. 2 (2022): 43–46. http://dx.doi.org/10.22214/ijraset.2022.40173.
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Abstract: In this digital world, color processing in different industries gives us more leverage to solve the consistency problem of continuous manual sorting. This document will be a new approach to continuously detect and classify objects and keep them in a specific place. Color processing attracts a lot of attention since the help of modern technology leads to the possibility of expanding the scope of its application in various areas. The Arduino Nano microcontroller, TCS3200 colour sensor, servo motor, and other electronic components are used to study, develop, and build a colour sorter. This work involves sensors that detect the color of the object and send the signal to the Arduino. The microcontroller sends a signal to the circuitry that drives the various motors to activate the object and place it in the specified location. Based on the detection, everything moves to the specified position releases the object, and returns to the original position. The system is able to quickly classify the object based on its color at the respective color station. Sorting objects is an essentially mechanical process that requires difficult work. The chronically manual layout leads to consistency problems. Above all, machines can do boring tasks that humans are superior to. Worker burnout in sequential production structures can lead to reduced execution and purpose issues in maintaining the object. Recognize the color of the article but in no way a machine. In this article, a compact registration near the arrangement of items based on color was implemented using the TCS3200 color sensor with servo motors in conjunction with Arduino Nano. Keywords: Automation TCS3200, Arduino Nano, Servo Motor.
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Bandyopadhyay, Shounak. "IOT-SEMS: An IoT-Driven Energy Management Solution for Industry 4.0." International Journal for Research in Applied Science and Engineering Technology 13, no. 6 (2025): 3464–68. https://doi.org/10.22214/ijraset.2025.72870.
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The rising demand for energy efficiency in industrial environments has led to the emergence of intelligent monitoring and control systems. This research presents the development of an IoT-based Smart Energy Management System (SEMS) tailored for industrial applications. The system integrates a Raspberry Pi, Arduino microcontroller, TCS3200 colour sensor, and a 4-channel relay module to enable real-time monitoring, classification, and control of electrical devices based on energy usage and operational conditions. The Raspberry Pi serves as the central processing unit, while the Arduino interfaces with sensors and actuators to collect data and execute control signals. The TCS3200 colour sensor is employed to detect status indicators such as device operating states or color-coded signals on machinery, enabling context-aware automation. The 4-channel relay provides the switching mechanism to control multiple loads efficiently. Through Wi-Fi connectivity, the system transmits data to the cloud, allowing for remote access, real-time alerts, and performance analytics. Experimental results validate the system's ability to optimize energy usage, enhance operational control, and support predictive maintenance in industrial setups. This work contributes a scalable and cost-effective solution for intelligent energy management in Industry 4.0 ecosystems.
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Sivakumar, Dr P., Gnanaprasad J, Lokesh C, and Praveen V. "IoT Based Automated Tomato Sorting Machine." International Journal for Research in Applied Science and Engineering Technology 12, no. 4 (2024): 2232–37. http://dx.doi.org/10.22214/ijraset.2024.60329.
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Abstract: Sorting of Tomatoes is necessary as tomatoes are widely used and an important fruit in India hence they play a vital role in our day to day lives. Our goal is to provide better quality tomatoes to meet the market standards and for that we need fresh and ripe tomatoes instead of unripe tomatoes. In India, sorting of tomatoes is done by humans which is prone to human error. We need to minimize the error and for that a low cost Tomato Sorting Machine is proposed which differentiates between ripe and unripe tomatoes on the basis of their colour. To differentiate between ripe and unripe tomatoes two TCS3200 RGB Colour Sensors are used in the proposed system. The tomatoes are passed in a straight line on the incline to the characterization point. The distinguishing proof of the colour of tomatoes passed on should be possible by checking the recurrence investigation of the yield of the colour sensor. The arranging of tomatoes as ripe and unripe depends on the colour force caught by TCS3200 colour sensor. The general framework precision was 93.33%. The arranging execution was evaluated for 1500 tomatoes for every hour with 1 channel which can be expanded if at least 2 channels are utilized.
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Nadia, Ninda Syafa Ainun, I. Gede Puja Astawa, Anang Budikarso, Budi Aswoyo, Ida Anisah, and Faridatun Nadziroh. "MANUFACTURE OF COOKING OIL CONTENT DRAIN CONTROL DEVICE IN OILY FOODS USING THE ESP32-BASED AND FUZZY LOGIC METHOD." Transmisi: Jurnal Ilmiah Teknik Elektro 26, no. 2 (2024): 53–63. http://dx.doi.org/10.14710/transmisi.26.2.53-63.
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Cooking oil is an essential commodity in everyday life in Indonesia, with palm oil consumption reaching 18.5 million tons in 2021, according to the Indonesian Palm Oil Association (GAPKI). High levels of consumption can potentially increase the risk of health problems. To reduce oil consumption, slicing of food is required. However, this process is often done manually, which is less effective. Therefore, this study proposes the development of an automatic control device using the YF-S201 flow sensor, TCS3200 color sensor, and DS18B20 temperature sensor, which then processes the data using the fuzzy logic method. Data processing and monitoring are performed using ESP32, displaying results on the LCD and website. Data is stored in a MySQL database. The test was conducted on shrimp crackers weighing 0.5kg for 1 minute 25 seconds. This control device is hoped to help households, traders, and MSMEs as an effective and efficient solution. The characteristics of the three sensors, namely the TCS3200 colour sensor, flow sensor YF-S201, and temperature sensor DS18B20, it was found that the sensor had worked well as expected, with a maximum error percentage of 0.91%. In one of the tests to drain oil on oily crackers, the oil flow was detected to be 0.07 litres/minute of oil flowing out of the oil filter.
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Abdullah. "SISTEM PENYELEKSI WARNA DAN BERAT BARANG MENGGUNAKAN PERGERAKAN LENGAN ROBOT EMPAT DOF (DEGREE OF FREEDOM)." J-SAKTI (Jurnal Sains Komputer dan Informatika) 1, no. 1 (2017): 59–70. https://doi.org/10.5281/zenodo.439845.
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<em>The use of robot arm in the system of colour and weight box selection has been done to integrate control system of robot arm moving with colour sensor TCS3200 and weight sensor load cell. The research was conducted by analyzing efficiency and accuracy system of robot arm moving to select colour and weight goods like box. The robot arm moving work suitable instruction of colour and weight sensor reading. At the most important from this system is how to accuracy of colour and weight sensor to detect colour ang weight and accuracy of robot arm moving system can positioning degree moving to take colour with different weight box suitable the place. The result of the analysis proved that robot arm moving had inregrated with colour and weight sensor efficient and effective to do this work as colour and weight box selection accurately. </em>
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Abdullah, Abdullah. "Sistem Penyeleksi Warna Dan Berat Barang Menggunakan Pergerakan Lengan Robot Empat DOF (Degree Of Freedom)." J-SAKTI (Jurnal Sains Komputer dan Informatika) 1, no. 1 (2017): 59. http://dx.doi.org/10.30645/j-sakti.v1i1.29.
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The use of robot arm in the system of colour and weight box selection has been done to integrate control system of robot arm moving with colour sensor TCS3200 and weight sensor load cell. The research was conducted by analyzing efficiency and accuracy system of robot arm moving to select colour and weight goods like box. The robot arm moving work suitable instruction of colour and weight sensor reading. At the most important from this system is how to accuracy of colour and weight sensor to detect colour ang weight and accuracy of robot arm moving system can positioning degree moving to take colour with different weight box suitable the place. The result of the analysis proved that robot arm moving had inregrated with colour and weight sensor efficient and effective to do this work as colour and weight box selection accurately.
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MR.SANKET, MANE, KHARAT MS.POOJA, UMESH A. CHATTE MR., UTKARSH KADAM MR., and KHUPASE MR.VIKRAM. "ARDUINO BASED OBJECT SORTING." IJIERT - International Journal of Innovations in Engineering Research and Technology NCMTEE-2K18 (March 31, 2018): 94–97. https://doi.org/10.5281/zenodo.1451219.
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Now a day�s industrial area requires demand for automation. D ue to automation human efforts are goes on decreasing since last decade. The o bject sorting based on colour i s difficult task in recent days . In industry there is rapidly increasing demands for automation. The Sorting of objects based on colour is very difficult task. This project gives us an idea about automatic colour sorting . Here we are designing and im plementing an efficient colour sorting using colour sensor TCS3200 based on Arduino UNO. This project gives high accuracy and performance. Easy to operate and construct which reduces human errors. Existing sorting method uses a set of inductive,capacitive and optical sensors do differentiate object colour . https://www.ijiert.org/paper-details?paper_id=141231
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Lesmana, Dedi, Budy Satria, and Yessi Ratna Sari. "ROBOT ARM (ADVANCED RISC MACHINE) AUTOMATIC ITEMS TRANSFER BASED ON COLOR USING ARDUINO UNO R3." JURNAL TEKNOLOGI DAN OPEN SOURCE 3, no. 2 (2020): 176–86. http://dx.doi.org/10.36378/jtos.v3i2.788.
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The latest evolution of technology lately had triggered a lot of creativity in our world,especially in robotic in industry. The use of a robot aims to save money and produces product with the same quality.The robot movers and goods is one of the implementation of technology in the field of robotics has the ability to help people to move goods from a place to place that has been made on the color of a grouping of the goods. In this research, robot was designed based on microcontroller 328. Also it is equipped with one DC motors as wheel driver, four servo motors as arm driver, one IR (Obstacle) sensor as an item detector and one TCS3200 sensors as colour.
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Sachdeva, Amitesha. "Development Of Industrial Automatic Multi Colour Sorting and Counting Machine Using Arduino Nano Microcontroller and TCS3200 Colour Sensor." International Journal of Engineering and Science 06, no. 04 (2017): 56–59. http://dx.doi.org/10.9790/1813-0604025659.
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Sutita, Yuwono izzah, and Heri Irwan. "Perancangan Arduino Uno pada Design Mesin Pick and Place Sorting Colour Automation untuk Meningkatkan Produktivitas." Journal of Manufacturing in Industrial Engineering & Technology 3, no. 2 (2024): 72–82. https://doi.org/10.30651/mine-tech.v3i2.23987.
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Arduino Uno adalah sebuah mikrokontroler open-source yang berbasis pada mikrokontroler Atmel AVR. Arduino Uno memungkinkan pengguna untuk merancang dan mengembangkan berbagai proyek elektronik dengan mudah. Arduino Uno ini menggunakan Intergrated Circuit(IC) yaitu mikrokontroler ATMega328P. Arduino Uno dirancang agar mudah digunakan oleh pemula sekalipun. Tersedia banyak tutorial dan komunitas yang siap membantu. Arduino Uno digunakan untuk mengendalikan putaran motor servo Sg90, dan untuk membaca warna pada sensor TCS3200, dan .Tujuan dari jurnal ini untuk mengetahui Komponen apa saja yang digunakan untuk Mengendalikan Input/Output dan juga cara penulisan Program dari Arduino Uno tersebut. Dari hasil Jurnal ini dapat mengetahui komponen apa saja yang digunakan pada Mesin robot pick and place sorting colour automation dan untuk pembuatan rancangan mesin. Dari rancangan ini diharapkan dapat mengendalikan Mesin robot pick and place sorting colour automation secara bersamaan.
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Ni, Ni San Hlaing, Man Oo Hay, and Thin Oo Thin. "Colour Detector and Separator Based on Microcontroller." International Journal of Trend in Scientific Research and Development 3, no. 5 (2019): 1103–8. https://doi.org/10.5281/zenodo.3590538.
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Sorting of objects is one of the most important tasks in the industries. Sorting machines can be made by using the sensor, camera, microcontroller and image processing system, etc., based on colour, size and shape of the objects. Among these systems, colour sorting machines are widely used in most industries to sort various coloured objects. This thesis describes the design and implementation of colour detection and sorting machine by using Arduino, colour sensor and two servo motors. In this system, a top servo motor is used for placing the object to the colour sensor which detects the RGB values of the object and then sends the information to Arduino. Then bottom servo motor will move according to the angle of respective degree which is command in the code depending on the RGB values of the object and then the object which is over the slider drops into the container. Servo motor is used to substitute the human operator and Arduino is used to controlling the overall process. Ni Ni San Hlaing | Hay Man Oo | Thin Thin Oo "Colour Detector and Separator Based on Microcontroller" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd26633.pdf
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Dr. Lovelin Jerald A, Farha Jahan S, Nandhini S, and Srilakshmi V. "Development of portable smart colorimetric device for on-site evaluation of microbial safety of milk." International Journal of Science and Research Archive 15, no. 2 (2025): 271–78. https://doi.org/10.30574/ijsra.2025.15.2.1293.
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Traditional methods such as the methylene blue reduction test (MBRT) to assess the microbial security of milk are often time consuming, labour-intensive and unsuitable for rapid tests. This paper presents a smart, inexpensive and portable alternative. An IoT-enabled colorimetric measuring device for monitoring milk quality in real time. The system uses the TCS3200 colour sensor to recognize subtle colour changes in milk associated with microbial spoilage and classify "normal" samples to spoilt ones. The NodeMCU Microcontroller processes this data and uses Wi-Fi functionality to display results for OLED screen and cloud-based platforms, Thingspeak analysis. By eliminating the need for manual observation, the proposed solution provides a faster and more user-friendly alternative to MBRT. This device ensures better food safety, less corruption, and more customer trust by simplifying milk quality testing for both domestic and industrial applications.
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Risfendra, Risfendra, and M. Harun Rosyid. "Color Sensor Application on Electric Drives." MOTIVECTION : Journal of Mechanical, Electrical and Industrial Engineering 2, no. 1 (2020): 1–10. http://dx.doi.org/10.46574/motivection.v2i1.36.
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TCS3200 is one type of sensor that able to identify various types of colors. Its ability to distinguish colors can be used to identify and select various types of objects. To find out the benefits of the TCS300 sensor, a study was made to know implement the TCS3200 sensor function on several electric drive and devices. The TCS3200 sensor application will be made using a 5V DC relay (to start or stop the electric drive) and several electronic devices. This tool uses media in the form of color cards as input data. The card will be read by the TCS3200 sensor, after that the reading data will be received by the Atmega8535 microcontroller, then the results will be displayed on several application devices such as relays, LCD, speaker and LED as outputs. After doing research, the TCS3200 sensor can detect the color cards that have been provided. Based on the program that has been compiled, the Sensor is able to distinguish 9 types of colors, set the switch of 3 electric drive and displaying information of color.
 TCS3200 adalah salah satu jenis sensor yang mampu mengidentifikasi berbagai jenis warna. Kemampuannya dalam membedakan warna dapat digunakan sebagai pemilih dan pengendali kerja pada beberapa perangkat kelistrikan. Untuk mengetahui manfaat sensor TCS300, sebuah penelitian dilakukan guna mengetahui fungsi sensor TCS3200 pada beberapa penggerak dan perangkat listrik. Pada penelitian ini dibuat sebuah aplikasi sensor TCS3200 dalam bentuk perangkat relay DC 5V (untuk memulai atau menghentikan penggerak listrik) dan beberapa perangkat elektronik. Alat ini menggunakan media dalam bentuk kartu warna sebagai input data. Kartu akan dibaca oleh sensor TCS3200, setelah itu data pembacaan akan diterima oleh mikrokontroler Atmega8535, kemudian hasilnya akan ditampilkan pada beberapa perangkat aplikasi seperti relay, LCD, speaker dan LED sebagai output. Sensor akan bekerja membaca warna dalam jarak 2,5 cm dari objek warna. Setelah melakukan penelitian, sensor TCS3200 dapat mendeteksi kartu warna yang telah disediakan. Berdasarkan program yang telah disusun, Sensor mampu membedakan 9 jenis warna dan membutuhkan waktu 1 - 2 detik untuk mengaktifkan output setelah input warna diberikan.
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Saad, Hasnida, Wan Muhammad Luqman Wan Ahmad Hilmi, Naimah Mat Isa, Noor Hafizah Abdul Aziz, and Lorena Ilagan. "Development of a Smart Profiling Sensor for Stingless Bee Honey Species in Malaysia." Journal of Advanced Research in Applied Sciences and Engineering Technology 64, no. 1 (2025): 95–109. https://doi.org/10.37934/araset.64.1.95109.
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The local stingless bee honey in Malaysia is highly valued because of its significant nutritional and natural remedy. Two commonly found stingless-bee species in Malaysia are Heterogona itama and Geniotrigona thoracica. Currently, the lack of standard profile data for the pure stingless bee honey from these two species leads to challenges in evaluating the authenticity of the stingless bee honey. To address this gap and provide a reliable solution, the objective of this research work is to develop a smart profiling system that can characterize stingless bee honey. This research work presents an innovative 3-in-1 smart profiler for characterizing pH, moisture content and colour intensity for different concentrations of stingless-bee honey. The developed profiler can characterize the stingless bee honey profile in situ without tediously bringing the samples to the laboratory. The 3-in-1 smart profiler utilized an Arduino Uno microcontroller, a TCS3200 colour sensor, an E-201-C pH sensor and an HD-38 moisture sensor. The research methodology involves designing the simulation environment using Tinkercad software, developing a hardware prototype, system testing, sensor calibration and performing comprehensive analysis. The developed profiler has successfully characterized pH level, moisture content and colour intensity for 100% pure honey, 75%, 50%, 25%, and 12% stingless bee honey with the repeatability of the output trend. For Heterogona itama species, the measured acidity level, moisture content and RGB colour intensity for 100% pure honey are in the range of 2.76-2.77, 82-84 % and 973-976-726 respectively. On the other hand, 100% pure honey from Geniotrigona thoracica species has 2.4-2.42 pH level, 86-89 % moisture content and RGB values of 970-963-707. This smart profiling system has the potential to be a part of the profiler in creating a standard profile for stingless bee honey for itama and thoracica. This research work has advantages in terms of in-situ detection, affordable to own and simple operating sensing system. It has the potential to be marketed and promote local socio-economic development. In the future, the accuracy of the results obtained from the prototype will be compared to sophisticated equipment such as gas chromatography.
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Fadilah, Maulina, Yulian Zetta Maulana, and MUHAMMAD YUSRO. "Compared RGB Methods Towards Efficient Money Detector for Blind People." Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics 6, no. 1 (2024): 1–9. http://dx.doi.org/10.35882/ijeeemi.v6i1.345.
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Limitations of profound visual impairment distinguishing each nominal number of banknotes are often used by people with bad intentions to take advantage of that basis, like money fraud. Due to this reason, the blind people need to be helped to recognize their surroundings by developing assistive technology that is advanced for them. This study aims to build an efficient design of a money detector by comparing three RGB methods: range breakdown, If-Then Rules, and decision tree to recognize the nominal of money. The sample used in this experiment is rupiah banknotes for the 2016 and 2022 issuances. The device is built with a TCS3200 colour sensor and designed in a real-time platform. It has been found that the highest average percentage accuracy was achieved by the breakdown range method with 100% (2016 sample) and 90% (2022 sample). This device also successfully produced a notification sound from a speaker that mentions the detected nominal value. This research could be used as a reference to improve assistive technology for blind people.
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Suhud, Khairi, Sukoma Sukoma, Sitti Saleha, and Muhammad Syukri Surbakti. "Development of TCS3200 Color Sensor Based on Arduino Uno and Its Application in Determining Borax Levels in Food." Indonesian Journal of Fundamental and Applied Chemistry 9, no. 2 (2024): 74–81. http://dx.doi.org/10.24845/ijfac.v9.i2.74.
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A color scanner application using the TCS3200 sensor, Arduino Uno microcomputer with IDE Software Program, a black box container, and a 12x2 matrix display has been designed, built, and tested. This sensor is employed to measure the level of borax in food items such as meatballs, tofu, and noodles in Banda Aceh. The obtained results are then compared with the measurement results of the Standard Ultraviolet-Visible Spectrophotometry (UV-Vis) method. Samples were prepared using centrifuge technique and the filtrate was collected. Subsequently, optical samples were prepared using dried filter paper with curcumin and scanned with the TCS3200 color sensor. Sample collection was carried out at Lamnyong Market, Lamdingin Market, Seutui Market, Suzuya Mall, and Ulee Kareng Market. Sample identification was performed using qualitative analysis, namely the flame test, and quantitative analysis using the TCS3200 color sensor based on Arduino Uno. The results of the quantitative analysis obtained from the TCS3200 color sensor compared with the ultraviolet-visible spectrophotometry (UV-Vis) method as the standard method indicate that the samples of meatballs, tofu, and noodles do not contain the harmful preservative borax. The positive control for borax using the TCS3200 color sensor is 56.8 ppm, while using the UV-Vis spectrophotometer it is 57.6 ppm. The t-test results from both methods show consistency between the TCS3200 color sensor measurement method and UV-Vis spectrophotometer
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Suhud, Khairi, Dian Utari, Muhammad Syukri Surbakti, et al. "Development of TCS3200 Color Sensor Based on Arduino Uno Microcontroller for Determination of Capsaicin Level in Sauces." Sains Malaysiana 53, no. 12 (2024): 3339–48. https://doi.org/10.17576/jsm-2024-5312-17.
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A color sensor has been designed to measure the capsaicin level in commercial sauces. This system is designed using a TCS2300 color sensor as an input, and an Arduino Uno microcontroller with Integrated Development Environment (IDE) software as signal conditioning and signal processing. The measurement result will be compared to the standard Ultraviolet-Visible (UV-Vis) spectrophotometer method. The sauce samples were taken using a sampling technique, namely eight samples of sauces circulating in the city of Banda Aceh. The result showed that the levels of capsaicin using the TCS3200 color sensor and UV-Vis spectrophotometer ranged from 5.39 to 22.42 mg/L and 5.58 to 22.64 mg/L, respectively. The linearity obtained in the concentration range of 5.25 mg/L shows a linear calibration curve using the TCS3200 color sensor (R2 = 0.9961) and UV-Vis Spectrophotometer (R2 = 0.9973). Accuracy (% recovery) for the TCS3200 color sensor and UV-Vis spectrophotometer ranged from 98.94 to 106.63%, and 98.13 to 110.2% mg/L, respectively. In the case of interday and intraday relative standard deviation has not more than 2%. Based on the t-test assessment, it shows that the TCS3200 color sensor has no differences statistically in results with UV-Vis Spectrophotometer. These results describe that the TCS3200 color sensor can be an alternative for analyses of capsaicin in sauce samples.
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Muhammad Ferdiyansyah, Yoga Putra Pratama, and Emmidia Djonaedi. "Analisis Pengaruh Jarak dan Kondisi Pencahayaan terhadap Alat Deteksi Warna dengan Sensor TCS3200 Berbasis Arduino." JURAL RISET RUMPUN ILMU TEKNIK 4, no. 2 (2025): 88–96. https://doi.org/10.55606/jurritek.v4i2.5556.
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The TCS3200 color sensor demonstrates limited accuracy under certain environmental conditions, particularly in relation to the distance between the sensor and the object, as well as the surrounding lighting. This study aims to investigate the effects of distance variation (0 cm, 2 cm, 4 cm, and 6 cm) and lighting conditions (bright and dark) on color detection using the TCS3200 sensor integrated with an Arduino microcontroller. An experimental method was employed, with color data converted into the CIELAB color space and analyzed using Delta E as the deviation indicator. The results indicate that the most accurate color readings occur at a distance of 0 cm, where the sensor receives maximum reflected light. Furthermore, measurements taken under dark conditions exhibit more consistent results compared to those under bright lighting, which tends to introduce optical interference. It can be concluded that the TCS3200 sensor performs best at close range and under controlled lighting conditions to ensure accurate and reliable color detection.
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Pratama, Bayu rizki, and Jaka persada Sembiring. "Rancang Bangun Alat Pemilah Biji Kopi Berdasarkan Kualitas Buah Menggunakan Sensor TCS3200." Electrician : Jurnal Rekayasa dan Teknologi Elektro 18, no. 2 (2024): 104–11. http://dx.doi.org/10.23960/elc.v18n2.2553.
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Coffee fruit is a trade commodity that has been known for centuries. Coffee fruit can be processed into a delicious drink, but when coffee farmers harvest at the same time, farmers combine immature and ripe coffee fruit in one container, this results in a decrease in the quality of the taste. significant. In this research, the fuzzy Sugeno method was used to determine the classification of ripe, semi-ripe and ripe coffee fruit. This tool uses an Arduino Uno Atmega328 microcontroller to control the TCS3200 color sensor as a reader for the color of the coffee fruit and uses a servo to sort the coffee fruit according to quality. In testing the automatic control system for separating coffee beans based on color using the TCS3200 Color Sensor, it was successful in directing the coffee beans to a predetermined container. Keywords— TCS3200 Sensor, Arduino ATmega328P,Coffee,Color,Quality,Fuzzy sugeno.
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Wati, Rani Laras, Endang Rosdiana, and Valentina Adimurti Kusumaningtyas. "Rancang Bangun Pendeteksi Kadar Formalin pada Mie Basah Menggunakan Sensor Warna TCS3200." Jurnal Sains dan Kesehatan 3, no. 5 (2021): 727–36. http://dx.doi.org/10.25026/jsk.v3i5.831.
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Wet noodles have a short shelf life because they are spoiled more quickly by microorganisms. Therefore, some irresponsible wet noodle producers add formalin so that the noodles can last longer. However, formalin is a substance that is prohibited from being used because it is dangerous to health. In this research, an instrument has been made that can detect formalin levels in wet noodles which have formalin concentrations of 0 ppm, 40 ppm, 95 ppm and 150 ppm. The instrument consists of a TCS3200 color sensor and an ATmega328P microcontroller. The color detected by the TCS3200 sensor is the color from mixing the formalin wet noodle sample withreagent schiff's. Furthermore, the sample will be selected by the instrument based on the RGB color value detected by the TCS3200 color sensor. The test results obtained the reliability of the instrument in selecting the sample of formalin wet noodles with a concentration of 0 ppm worth 92.5%, 40 ppm worth 95%, 95 ppm worth 97.5% and 150 ppm worth 100%.
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Alhamid, Umar Djafar, Yoga Listi Prambodo, and Asruddin Asruddin. "Rancang Bangun Alat Pendeteksi Keaslian Batu Bacan Doko Berbasis Mikrokontroler ATMega2560." Sistem Komputer dan Teknologi Intelegensi Artifisial (SIKOMTIA) 1, no. 3 (2023): 206–13. http://dx.doi.org/10.59039/sikomtia.v1i3.20.
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This research designed and developed a tool to detect the authenticity of Bacan Doko. The development of this tool uses TCS3200 sensor components as a detection of color variations in stones, BH1750 sensors to measure light intensity, and LCD1602 to display information on stone detection results visually. This study aims to overcome the problem of identifying the authenticity of Bacan Doko stones which are often difficult to detect accurately by ordinary people who do not understand the world of gemology, which results in the existence of fake stones on the market. The presence of this tool provides innovation in the world of gemology by utilizing microcontroller and sensor technology to overcome the authentication problem of Bacan Doko stone accurately, and support the integrity of the gemstone market. The development of data processing algorithms is carried out to analyze and process information received from input values on sensors. The detection tool provides good results to recognize and distinguish genuine Bacan Doko stones based on the color characteristics of the sensor identification results TCS3200 taking into account the light intensity measured by the BH1750 sensor and information can be displayed clearly through the LCD screen. The development of this tool successfully proved its effectiveness in identifying the authenticity of Bacan Doko stone. This tool can be a reliable solution for traders and gemstone observers in ensuring the authenticity of Bacan Doko.
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Surbakti, Muhammad Syukri, Muhammad Farhan, Zakaria Zakaria, et al. "Development of Arduino Uno-Based TCS3200 Color Sensor and Its Application on the Determination of Rhodamine B Level in Syrup." Indonesian Journal of Chemistry 22, no. 1 (2022): 630. http://dx.doi.org/10.22146/ijc.69214.
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The use of the notorious synthetic dye, rhodamine B, in food and beverage products has been widely reported. This application urges the need to develop an analytical method that can provide reliable rhodamine B data with an easy operational technique. Therefore, this research is aimed to develop an Arduino Uno-based TCS3200 color sensor and study its application to determine rhodamine B levels in syrup. The design of the analytical instrument included TCS3200, an Arduino Uno microcomputer, an Integrated Development Environment (IDE) software, a black box container, and a 24 × 2 matrix display screen, where samples were prepared via absorption using wool thread. With a linear range of 1–20 mg/L, our proposed colorimetric sensor had recoveries of 96.25–110.3%, which was better compared to that was obtained from the UV-vis (81.8–100.6%) method. The detection and quantification limits of the sensor were 2.766 and 8.383 mg/L, respectively. The syrup samples used in this study were purchased from the local stores in Banda Aceh. Based on the proposed TCS3200 color sensor, the highest rhodamine B concentration from the syrup sample was 16.74 mg/L. The t-test analysis in this study revealed that the Rhodamine B levels quantified using the newly developed TCS3200 color sensor were not statistically or significantly different from the UV-Vis spectrophotometer method.
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Vicananda, Ladayan Pradana, Saptiana Nur Prahasti, Khakam Ma’ruf, Rizal Justian Setiawan, and Darmono Darmono. "Design and Implementation of a Candy Color Sorter Device using Microcontroller-Based Color Sensor TCS3200." Journal of Electrical Technology UMY 8, no. 1 (2024): 1–8. https://doi.org/10.18196/jet.v8i1.20346.
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The purpose of this research is to design and implement a candy color sorter device using a microcontroller-based TCS3200 color sensor. This technology can be applied in the confectionery and fruit businesses for color-based sorting. The method used is an experimental approach that begins with a literature study, followed by hardware and software design, and device testing. The research results show that the candy sorter device was successfully designed and implemented. This device is capable of sorting candies based on red, green, and blue colors with optimal sensor detection levels. The novelty value of this research is the development of an automatic candy sorter device based on the TCS3200 color sensor, which can help reduce human workload and increase sorting process efficiency in the confectionery industry.
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Sandra, R. Damayanti, Y. Hendrawan, B. Susilo, and S. Oktavia. "Prediction of tomatoes maturity using TCS3200 color sensor." IOP Conference Series: Earth and Environmental Science 475 (May 7, 2020): 012011. http://dx.doi.org/10.1088/1755-1315/475/1/012011.
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Bubela, Tetiana, and Bohdan Bohush. "PRECONDITIONS FOR THE CREATION OF A MEAT FRESHNESS CONTROL AND IDENTIFICATION SYSTEM." Measuring Equipment and Metrology 84, no. 3 (2023): 59–65. http://dx.doi.org/10.23939/istcmtm2023.03.059.
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The relevance of creating a comprehensive system for meat control and identification to determine its freshness level has been demonstrated in the study. The drawbacks of traditional organoleptic and laboratory methods commonly used for meat inspection were analyzed. The authors presented the advantages and challenges of employing an electronic nose. A design for a meat control and identification system was proposed, which includes an Arduino Uno microcontroller, Raspberry Pi, USB to TTL adapter, gas sensors, color sensor, thermal camera, and image sensor. The proposed implementation of the electronic nose system on a single-board computer demonstrates its success in controlling and identifying meat freshness. A matrix of semiconductor gas sensors, TGS2602, MQ137, and MQ138, is formed as olfactory sensors, and TCS3200 is used as an RGB vision sensor, enabling the identification of the smell and color of different degrees of meat freshness. To obtain clear output differences from the gas sensors that react to the freshness level of meat, the baseline method is proposed for use. Therefore, a system enhanced with neural network capabilities will replace traditional devices for identifying meat freshness.
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Bardani, Ahmad Imam, and Nuryono Satya Widodo. "Deteksi Zona pada KRSTI dengan Sensor Warna TCS3200." Buletin Ilmiah Sarjana Teknik Elektro 1, no. 2 (2019): 56. http://dx.doi.org/10.12928/biste.v1i2.955.
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Robot seni tari Lanange Jagad untuk lomba Kontes Robot Seni Tari Indonesia (KRSTI) belum mampu membedakan zona warna pada arena yang menyebabkan robot melakukan gerakan tarian yang tidak sesuai dengan tempatnya. Oleh karena itu dibutuhkan kontrol otomatisasi menggunakan sensor warna TCS3200. TCS3200 akan memperoleh komposisi RGB yang tepat menggunakan perhitungan frekuensi. Hasil yang dicapai dalam penelitian ini adalah robot seni tari Lanange Jagad dapat membedakan zona dengan memanfaatkan warna merah, biru, biru muda, hijau, dan putih dengan tingkat keberhasilan 84%. Ketika robot mendeteksi warna yang sudah ditentukan pada setiap zona, robot akan secara otomatis melakukan gerakan tari yang sudah disesuaikan dengan zona tersebut. Saat robot masuk ke zona warna berbeda maka robot akan menghentikan gerakan tari pada zona sebelumnya dan memanggil gerakan tari selanjutnya. Namun masih terdapat banyak noise saat melakukan pengujian sehingga nilai RGB yang digunakan untuk memanggil gerakan tari berubah sehingga robot tidak merespons perintah yang dimasukkan pada program. Nilai RGB yang stabil di dapatkan pada kondisi kaki robot menapak atau bersentuhan langsung dengan zona warna, nilai tersebut yang digunakan untuk pemanggilan gerakan tari.The Lanange Jagad dance robot for the Indonesian Robot Dance Contest (KRSTI) has not been able to distinguish the color zone in the arena that causes the robot to perform dance moves that are not in accordance with its place. Therefore we need automation control using the TCS3200 color sensor. TCS3200 will obtain the right RGB composition using frequency calculations. The results achieved in this study are the Lanange Jagad dance robot can distinguish zones by utilizing red, blue, light blue, green, and white with a success rate of 84%. When the robot detects the colors that have been determined in each zone, the robot will automatically perform dance moves that have been adapted to the zone. When the robot enters a different color zone, the robot will stop the dance movement in the previous zone and call the next dance movement. However, there is still a lot of noise when testing so that the RGB value used to call dance moves changes so that the robot does not respond to commands entered in the program. A stable RGB value is obtained when the robot's foot steps or comes into direct contact with the color zone, the value that is used for calling dance moves.
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Huynh, Quoc-Khanh, Chi Ngon Nguyen, Nguyen Phuong Lan Tran, Nguyen Hong Phuc Vo, Thanh Thuong Huynh, and Van Cuong Nguyen. "Evaluating the optimal working parameters of the color sensor TCS3200 in the fresh chili destemming system." Can Tho University Journal of Science 14, no. 1 (2022): 35–42. http://dx.doi.org/10.22144/ctu.jen.2022.004.
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In a previous study, a fresh chili destemming system has been proposed, and the TCS3200 color sensor was used as low-cost equipment in the arrangement section of the system. However, the working and installing parameters have not yet been investigated in detail. This study focused on investigating the optimal working conditions of TCS3200 on the fresh chili destemming system. The study included three experiments including the effect of the red and green color channels, the effect of the height between the sensor and fruits, and the effect of the running velocity on the received signal level of the sensor. A total of 260 ripen fruits were chosen to test. The results showed that the red channel generated a stronger signal than the green one. The optimal height from the sensor to the fruits was obtained at 25 mm, and the maximum conveyor velocity is limited to 100 mm/s. This study helps to determine the optimal operating parameters and enhance the working ability of a low-cost sensor. However, the high-speed pushing actuating mechanism should be developed in further works.
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Salsabilla, Salma, Irma Nirmala, and Tedy Rismawan. "Sistem Pemilah Otomatis Tingkat Kematangan Buah Kelapa Sawit Menggunakan Metode Logika Fuzzy Mamdani Dan Sensor TCS3200." Journal of Computer System and Informatics (JoSYC) 5, no. 1 (2023): 144–54. http://dx.doi.org/10.47065/josyc.v5i1.4449.
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The palm oil sector has a strategic impact on the growth of Indonesia's economy, because the fruit of palm oil produces oil which can be used as alternative fuel, food oil and basic materials for various industries. Currently, oil palm fruit is sorted manually based on color, which takes much longer. As a result, a system was created to categorize oil palm fruit according to their state of maturity. This system uses the TCS3200 sensor as the main sensor to detect the color of oil palm fruit and implements the Mamdani fuzzy logic method to classify it. Arduino Uno can control the hardware components used in the system. Data obtained from RGB color values (red, green, blue) obtained by the TCS3200 sensor is used as input in the system. Meanwhile, the outcomes this system produced are in the form of maturity levels of oil palm fruit which are classified into 3 categories, namely unripe, ripe and past ripe. Based on tests carried out with the confusion matrix, the accuracy value obtained was 95.6%.
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Bahri, Saeful, and Muhammad Fachri Baharsyah. "Rancang Bangun Alat Uji Kadar Gula Darah Non-Invasif Berbasis Internet of Things." RESISTOR (Elektronika Kendali Telekomunikasi Tenaga Listrik Komputer) 6, no. 1 (2023): 55. http://dx.doi.org/10.24853/resistor.6.1.55-64.
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ABSTRAKJumlah penderita Diabetes terus meningkat setiap tahunnya, salah satu penyebab terjadinya peningkatan jumlah penderita Diabetes adalah banyaknya orang yang enggan memeriksakan kadar gula darahnya ke fasilitas-fasilitas kesehatan seperti klinik, puskesmas ataupun rumah sakit. Alasan dibalik enggannya orang-orang untuk memeriksakan kadar gula darahnya adalah karena pada metode invasif yang umum digunakan pada pemeriksaan kadar gula darah, biaya pemeriksaannya relatif mahal khususnya untuk kalangan menengah ke bawah, selain itu metode tersebut juga memberikan efek ketakutan akan jarum suntik. Untuk mendukung tindakan preventif akan meningkatnya jumlah penderita diabetes, diperlukan sebuah alat yang mampu melakukan pengujian terhadap kadar gula darah secara non invasif. Metode urine-benedict merupakan salah satu metode non invasif yang cukup akurat dalam menguji kadar gula darah. Metode ini memanfaatkan perubahan warna pada larutan benedict yang telah dicampurkan dengan urin. Dengan menggunakan sensor TCS3200, pengujian kadar gula darah secara non invasif ini bisa dilakukan dengan lebih mudah dimana sensor akan mendeteksi warna pada spesimen lalu data hasil pengujian akan diolah oleh NodeMCU ESP8266 dan kemudian dikirimkan ke perangkat IoT yang bisa dimonitor melalui aplikasi berbasis web. Sensor TCS3200 yang digunakan pada pengujian ini mampu mendeteksi spektrum warna dari spesimen yang diuji dengan baik dengan akurasi 96%. Kata kunci : Alat uji gula darah, TCS3200, ESP8266, Internet of ThingsABSTRACTThe number of people with diabetes increases every year. One of the causes of the increase in the number of diabetics is the number of people reluctant to check their blood sugar levels at health facilities such as clinics, health centers, or hospitals. The invasive method uses a needle and blood sample to measure blood sugar. People are unwilling to check their blood sugar levels because they fear the relatively expensive cost of examinations, especially for the lower middle class, and fear needles. To support the prevention of the increasing number of people with diabetes, it needs a tool that can test blood sugar levels non-invasively.The urine-benedict method is one of the non-invasive methods that is quite accurate in testing blood sugar levels. This method utilizes discoloration in the benedict solution that has been mixed with urine. By using the TCS3200 sensor, this non-invasive blood sugar level testing can be done more easily where the sensor will detect color in the specimen and then the test result data will be processed by the NodeMCU ESP8266 and then sent to an IoT device that can be monitored through a web-based application. The TCS3200 sensor used in this test is able to detect the color spectrum of the tested specimen well with an accuracy of 96%.Keywords : Blood sugar test, TCS3200, ESP8266, Internet of Things
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Hakim, Muhammad Fahmi, Rahman Azis Prasojo, Rohmanita Duanaputri, Bustani Hadi Wijaya, Hanifiyah Darna Fidya Amaral, and Zakki Fuadi Emzain. "Transformer oil degradation detection system based on color scale analysis." Indonesian Journal of Electrical Engineering and Computer Science 37, no. 1 (2025): 15. http://dx.doi.org/10.11591/ijeecs.v37.i1.pp15-25.
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The rise in power transformer load results in degradation of the condition of the transformer oil and ultimately a deficiency in the distribution of electrical energy. This degradation can be slowed down by reconditioning transformer oil based on oil color detection. This research aims to design, test and validate a transformer oil color testing system based on color sensor and microcontroller. To obtain an accurate system, tests were carried out on selecting the types of sensors, the color of the chamber walls, and the shapes of transformer oil sample vessel used. The oil color scale of the samples was determined visually according to the ASTMD1500, 2009 standard as a benchmark. The test results showed that the TCS3200 color sensor was able to detect the color of all transformer oil samples. White chamber wall and test tube as oil sample containers were chosen to increase system accuracy. Overall, the system is able to detect the color of transformer oil, convert to the ASTMD1500, 2009 standard transformer oil color scale, determine the condition of the transformer oil and conclude the level of transformer oil degradation according to CIGRE-761, 2019. Validation results showed the system had an accuracy level of 92.65%.
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Muhammad, Fahmi Hakim Rahman Azis Prasojo Rohmanita Duanaputri Bustani Hadi Wijaya Hanifiyah Darna Fidya Amaral Zakki Fuadi Emzain. "Transformer oil degradation detection system based on color scale analysis." Indonesian Journal of Electrical Engineering and Computer Science 37, no. 1 (2025): 15–25. https://doi.org/10.11591/ijeecs.v37.i1.pp15-25.
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The rise in power transformer load results in degradation of the condition of the transformer oil and ultimately a deficiency in the distribution of electrical energy. This degradation can be slowed down by reconditioning transformer oil based on oil color detection. This research aims to design, test and validate a transformer oil color testing system based on color sensor and microcontroller. To obtain an accurate system, tests were carried out on selecting the types of sensors, the color of the chamber walls, and the shapes of transformer oil sample vessel used. The oil color scale of the samples was determined visually according to the ASTMD1500, 2009 standard as a benchmark. The test results showed that the TCS3200 color sensor was able to detect the color of all transformer oil samples. White chamber wall and test tube as oil sample containers were chosen to increase system accuracy. Overall, the system is able to detect the color of transformer oil, convert to the ASTMD1500, 2009 standard transformer oil color scale, determine the condition of the transformer oil and conclude the level of transformer oil degradation according to CIGRE-761, 2019. Validation results showed the system had an accuracy level of 92.65%.
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Suhud, Khairi, Sri Rahayu Ningsih, Muhammad Syukri Surbakti, et al. "Determination of Mercury Ions Level in River Water Using an Arduino Uno-Based TCS3200 Color Sensor with Silver Nanoparticle Indicators Synthesized from Moringa Oleifera Leaf Extract." Trends in Sciences 22, no. 8 (2025): 10089. https://doi.org/10.48048/tis.2025.10089.
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Mercury ions (Hg2+) are highly toxic due to their neurotoxic properties. They pose significant risks to organisms and humans, especially when they accumulate in the body and frequently contaminate water. An Arduino Uno-based TCS3200 color sensor utilizing silver nanoparticles (AgNPs) as indicators offer a promising alternative for detecting Hg2+. This approach is characterized by its simplicity, cost-effectiveness, environmental friendliness, and effectiveness for real-time detection in resource-limited areas. This study synthesized AgNPs from the ethyl acetate extract of Moringa oleifera leaves. These AgNPs were tested for selectivity against various metals commonly found in aquatic environments. Once the selective metals were identified, sensitivity and selectivity tests were conducted to confirm that the sensor accurately measures specific analytes, even in the presence of other components within a sample. The results showed that the synthesized AgNPs are highly selective and specific for Hg2+ ions, achieving an accuracy range of 89.3 - 110 %. The sensor can detect Hg2+ ions with a detection limit (DL) of 0.069 ppm. Analysis of river water samples revealed Hg2+ concentrations ranging from 0.128 to 0.287 ppm. Hg2+ concentration was measured using a TCS3200 color sensor and validated against UV-Vis spectrophotometry. This confirmed its comparable results and effectiveness for accurate Hg2+ detection in real-world water samples and resource-limited areas. HIGHLIGHTS Silver nanoparticles (AgNPs) were synthesized from Moringa oleifera leaf extract for mercury detection using a TCS3200 color sensor. High selectivity and sensitivity for Hg2+ ions were achieved, with a detection limit of 0.069 ppm and accuracy of 89.3 - 110 %. The sensor’s performance was validated against UV-Vis spectrophotometry, showing comparable results. The method was applied to river water samples, with Hg2+ concentrations detected between 0.128 and 0.287 ppm, and applicable for real-time monitoring for resource-limited areas. GRAPHICAL ABSTRACT
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Arafah Mufti, Azizurahman, Siti Amatullah Karimah, S.T., M.T., Hilal Hudan Nuha, and Endang Rosdiana. "Web-Based Formaldehyde Detection System in Chickens using IOT and Fuzzy Logic." International Journal on Information and Communication Technology (IJoICT) 10, no. 1 (2024): 141–51. http://dx.doi.org/10.21108/ijoict.v10i1.885.
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Chicken is a widely consumed source of animal protein globally, valued for its high protein content and essential nutrients. Ensuring the freshness of chicken meat is crucial to guarantee its healthiness and prevent harm to consumers. Unfortunately, there are concerns about the use of hazardous substances like formaldehyde by some traders for meat preservation. Formalin, a clear liquid with a pungent odor, is commonly utilized as a food preservative. To address the misuse of formaldehyde in broiler chickens, an innovative solution is proposed involving IoT technology and Fuzzy Logic. The developed formaldehyde detection system employs an ESP8266 microcontroller and a TCS3200 sensor to assess color variations in chicken meat samples mixed with Schiff's reagent. The TCS3200 sensor detects color changes, and the ESP8266 Microcontroller converts measurements into RGB basic colors. Calibration of the sensor yielded a 98.30% relative accuracy at a 3 cm distance. Fuzzy Logic is then applied to determine formaldehyde levels, displayed on an LCD screen. The tool exhibits a 95% reliability for achieving a 0 ppm level, 93% for 40 ppm, 92% for 80 ppm, and 100% for 200 ppm
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B.Badadwar, Bhakti, J. S. Awati, and M. S. Kumbhar. "Fuzzy Power, Converter for Color Sorting System." Journal of Power Electronics and Devices 9, no. 3 (2023): 7–13. http://dx.doi.org/10.46610/joped.2023.v09i03.002.
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Intelligent robot technology is currently widely applied to all facets of human production and existence. Future development must focus on using intelligent robots rather than humans to achieve automatic sorting. In the field of sorting robots, color sorting robots are a significant research object. This paper examines the color recognition principle of the TAOS Company’s TCS3200 color sensor, based on the introduction of the theory of three primary colors. It goes into detail about how important white balance is. An ATmega16 single-chip microcomputer serves as the robot's brain, color and grey sensors serve as its sense organs, and steering gears are used as its moving parts in the design of a color block sorting robot. It is capable of recognizing, organizing, and manipulating various color blocks. The technique of multiple detections and high probability results are used in color recognition, which greatly increases detection accuracy. There is a specific practical benefit to the system.
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Ulfah, Maria. "RANCANG BANGUN ALAT PEMILAH PADA BIJI BUAH KELAPA SAWIT BERDASARKAN WARNA DAN BERAT." JTT (Jurnal Teknologi Terpadu) 11, no. 2 (2023): 286–92. http://dx.doi.org/10.32487/jtt.v11i2.1865.
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In the palm oil industry, processing oil palm kernels in the field to improve the quality of palm oil produced is an important activity. Palm kernel harvesting occurs when the oil content is highest and the free fatty acid content is lowest. To maximize the harvest, it is necessary to develop a Sorting Equipment Design on Palm Oil Seeds based on color and weight carried out in Penajam Paser Utara. The purpose of this tool is to detect the maturity level of oil palm kernels with the TCS3200 Sensor, as well as reading the weight of oil palm seeds with the Loadcell Sensor. The main components in making this tool include TCS3200 Sensor and Loadcell Sensor, with other supporting components namely Conveyor, Infrared (IR) Sensor, DC Motor, Servo Motor, and LCD.The results of the IR sensor test had an average error of 0.05 in distance readings, the Loadcell test had an average error of 1.08 in weight readings and the TCS 3200 Sensor had no error in determining the maturity category in oil palm fruit seeds.
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Febryansah, M. Iqbal, Anton Yudhana, and Alfian Ma'arif. "Urinoir Analyzer Pintar Pendeteksi Kelainan Pada Fungsi Ginjal Dengan Analisis Kadar Ph Dan Warna Pada Urin." Mobile and Forensics 2, no. 1 (2020): 32–40. http://dx.doi.org/10.12928/mf.v2i1.2032.
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Perkembangan pemeriksaan penyakit kelainan ginjal melalui analisa urin saat ini dilakukan dalam dua proses pemeriksaan secara makroskopis dan mikroskopis. Pada dasarnya dibutuhkan sebuah alat yang mampu memproses dan menganalisis sebuah sampel urin secara otomatis agar tidak terjadinya kesalahan dalam melakukan pemeriksaan penyakit melalui sampel urin. Awalan perkembangan ini menggunakan sebuah Kontroler Arduino UNO dan dua buah variabel masukan yaitu sensor warna TCS3200 dan sensor PH meter SKU SEN0161. Dua buah variabel masukan sensor bekerja secara berdampingan dengan sensor TCS3200 memiliki hasil keluaran berupa nilai frekuensi RGB dan diproses kembali menjadi frekuensi keabuan. Lalu, sensor PH meter SKU SEN0161 menghasilkan sebuah nilai PH pada sampel urin. Hasil dari pemeriksaan tersebut ditampilkan pada sebuah penampil berupa LCD berukuran 16x2. Hasil pemeriksaan dari alat ini dibandingkan dengan hasil analisa pakar dari Balai Laboratorium Kesehatan Yogyakarta bagian Urology. dan mendapatkan tingkatan nilai akurasi 93% dengan keberhasilan data sebanyak 28 dari 30 data yang diambil. The development of examining kidney disorders through urine analysis is currently carried out in two processes of examination, macroscopic and microscopic. Basically, we need a tool that is able to process and analyze a urine sample automatically so that there are no errors in carrying out disease checks through the urine sample. The beginning of this development used an Arduino UNO controller and two input variables, namely the TCS3200 color sensor and the SKU SEN0161 PH meter sensor. Two sensor input variables working side by side with the TCS3200 sensor have an output in the form of RGB frequency values and are processed back into gray frequencies. Then, the PH meter SKU SEN0161 sensor generates a PH value in the urine sample. The results of these checks are displayed on a 16x2 LCD display. The examination results of this tool are compared with the results of the analysis of experts from the Yogyakarta Health Laboratory Center, Urology section. and get an accuracy level of 93% with the success of the data as much as 28 of the 30 data taken.
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Savitha, A. C., Kumar KM Madhu, M. S. Pruthviraj, et al. "Implementation of Color Detection Tool for Blind People." Journal of Scholastic Engineering Science and Management (JSESM), A Peer Reviewed Refereed Multidisciplinary Research Journal 4, no. 5 (2025): 19–23. https://doi.org/10.5281/zenodo.15389151.
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Color detection is an interesting area of technological application that has applications in art and design, automation, and quality control, among other domains. In this project, we’ll look at how to make a color detector out of an Arduino Uno, a 16x2 LCD display, and a TCS230/TCS3200 color sensor. This configuration will enable you to recognize and show the color of an object that is positioned in front of the sensor with accuracy. This blog demonstrates an accurate and efficient approach of detecting colors in the surroundings. MArobotics use of the TCS230 sensor and Arduino microcontroller provides an accessible and adaptable approach for applications including industrial automation to creative endeavors. This color detecting system enables automation, sorting, and interactive installations, which makes it an interesting and practical project at the crossroads of electronics and color sensing technology. The utility model discloses a color detector and a color recognition device, wherein the color detector comprises a luminous source which emits detecting light to to-be measured objects, and a sensor which is used for receiving reflected light to measuring color information, wherein the color recognition device comprises the color detector, a data processing unit which is used for recognizing color through collecting data, storing data and comparing data and is used for judging relative cases, and an output unit used for outputting color recognition results.
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Khafit, M. Noor, Nur Khamdi, Jajang Jaenudin, and Edilla Edilla. "Rancang Bangun Alat Sortir Buah Apel Berdasarkan Perbedaan Ukuran dan Warna Menggunakan Mikrokontroller Arduino." JTEV (Jurnal Teknik Elektro dan Vokasional) 9, no. 1 (2023): 147. http://dx.doi.org/10.24036/jtev.v9i1.122935.
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Indonesia is a country rich in natural resources, especially in agriculture. Plantation products, both in the form of raw materials and processed products, are one of the major contributors to the country's foreign exchange. Local apples from Batu City are one of the products exported. However, the process of sorting apples still uses human labor and is an obstacle for Indonesia to increasing the economic value of local apples in the export market. Therefore, an automatic sorting system was created to separate apples based on size and color. The system uses experimental methods and collects empirical data from each process for more accurate automated sorting. The size sorting mechanic consists of a conveyor that is designed to be tilted at 30 degrees to facilitate the process of sorting apples and then measuring rollers, hoopers, and shelters. The data processing controller used is Arduino Mega 2560. The main data input comes from the TCS3200 color sensor and proximity sensor. Meanwhile, the sorting executor uses 1 MG996 servo motor and 2 MG90s servo motors. Although there are constraints on the TCS3200 sensor which are sensitive to distance and light which affect the RGB value results, this automatic sorting system can successfully sort apples with a success rate of 96% for size sorting and 80% for color sorting.
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Susanti, Roza, Zas Ressy Aidha, Surfa Yondri, Sir Anderson, and Tri Oktaviandra. "The Use of Artificial Neural Networks (ANN) in the Chayote Chips Dough Mixer." Andalas Journal of Electrical and Electronic Engineering Technology 2, no. 2 (2022): 50–54. http://dx.doi.org/10.25077/ajeeet.v2i2.27.
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This study uses a backpropagation neural network to determine the evenness of the chayote chip dough. The Tcs3200 Color Sensor mounted on the stirrer alt is used as a sensor to determine the color of the chayote emping dough. A regression score of 1 indicates that the input and target data match in the test results of the artificial neural network, which has an objective error (MSE) value of 0.0096306 achieved in the 313th epoch. Changes in RGB color readings on the TCS sensor from min values ??<40 and max values>52 in mixing dough are influenced by distance and light intensity which will be converted in the form of frequency.
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Fitri, Niken Syah, Muhammad Ikhsan Sulaiman, and Yusriana Yusriana. "Rancang Bangun Prototipe Alat Deteksi Derajat Gongseng Kopi." Jurnal Ilmiah Mahasiswa Pertanian 9, no. 1 (2024): 434–43. https://doi.org/10.17969/jimfp.v9i1.29350.
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Abstrak. Pengolahan kopi sebelum diminum merupakan proses yang cukup panjang yang diawali dengan proses pemanenan biji kopi yang sudah matang, dilanjutkan dengan proses sangrai dengan menggunakan suhu yang berbeda. Kualitas kopi dipengaruhi oleh beberapa faktor, termasuk derajat gongseng atau tingkat pemanggangan kopi. Secara umum, tingkat pemanggangan kopi dibagi atas 3 yaitu light, medium, dan dark. Salah satu teknologi yang dapat bekerja otomatis adalah sensor warna digunakan untuk berbagai kebutuhan. Saat ini industri kopi sudah tersedia alat penyangrai dan penggiling kopi otomatis. Namun memiliki kelemahan membutuhkan daya sangat tinggi dan harga yang relatif mahal. Kemudian para roaster juga membutuhkan waktu yang cukup lama untuk mempelajari teknik penyangraian. Oleh karenanya, penelitian ini dilakukan untuk merancang prototipe alat deteksi derajat gongseng kopi dengan tujuan memudahkan para roaster dalam proses penyangraian untuk mempertahankan mutu kopi roasting. Pengujian dilakukan terhadap 3 tingkat kematangan biji kopi yaitu light, medium, dan dark dengan beberapa skenario percobaan. Dalam penelitian ini menggunakan sensor warna TCS3200 untuk menentukan warna kopi roasting. Setelah melakukan pengujian pengambilan data tersebut maka didapatkan nilai RGB dari masing- masing sampel. Hasil menunjukkan bahwa prototipe alat deteksi derajat gongseng kopi menggunakan sensor warna mampu memberikan informasi mengenai tingkat pemanggangan kopi. Hasil penelitian yang menunjukkan perbedaan nilai frekuensi RGB dari sensor TCS3200 antara perlakuan tanpa kotak dan dengan kotak yang disebabkan oleh sejumlah faktor. Abstract. Processing coffee before drinking is a fairly long process that begins with the process of harvesting the ripe coffee beans, followed by the roasting process using different temperatures. Coffee quality is influenced by several factors, including the degree of roasting or roasting level of the coffee. In general, coffee roasting levels are divided into 3, namely light, medium and dark. One technology that can work automatically is a color sensor used for various needs. Currently, the coffee industry has available automatic coffee roasters and grinders. However, it has the disadvantage that it requires very high power and is relatively expensive. Then roasters also need quite a long time to learn roasting techniques. Therefore, this research was carried out to design a prototype of a coffee roast degree detection tool with the aim of making it easier for roasters in the roasting process to maintain the quality of roasted coffee. Tests were carried out on 3 levels of coffee bean maturity, namely light, medium and dark with several experimental scenarios. In this research, the TCS3200 color sensor was used to determine the color of roasted coffee. After carrying out the data collection test, the RGB value of each sample is obtained. The results show that the prototype of the coffee roast degree detection tool using a color sensor is able to provide information about the level of coffee roasting. Research results showing differences in RGB frequency values from the TCS3200 sensor between treatment without a box and with a box caused by a number of factors.
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Khoiri, Rizky Dafa, Styawati Styawati, and Arya Afredha. "Implementation of Fish and Plant Nutrition Technology On Aquaponic Systems." IC-ITECHS 5, no. 1 (2024): 379–404. https://doi.org/10.32664/ic-itechs.v5i1.1684.
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Catfish farming often faces challenges due to high stress levels in fish caused by instability in water pH and temperature, which disrupt metabolism, reduce appetite, and harm their health. This can lead to nutrient deficiencies for plants in aquaponic systems, causing ecological imbalances. Many farmers still rely on instinct to monitor pond conditions, making it difficult to detect changes in pH, temperature, and nutrient levels promptly, resulting in suboptimal water conditions and high fish mortality rates. To address this, a device equipped with sensors for real-time monitoring of pH, water temperature, and nutrient levels is necessary, helping farmers maintain ecological balance and reduce fish mortality. This research aims to ease catfish farming by integrating an automatic feeding system controlled by a servo and RTC and monitoring critical parameters like pH, temperature, and plant color through Thingspeak. Using the prototype method, the system was developed with ESP32, Arduino Microcontroller, pH sensor, DS18B20 temperature sensor, TCS3200 color sensor, buzzer, and servo. The aquaponics system design included scheduled nutrient supply for fish feed and an accurate feeding process activated at 12:00 PM, running the servo for 2 seconds with a buzzer alert. Testing confirmed the sensors’ ability to transmit data to Thingspeak and display it via LCD. However, the temperature sensor requires periodic calibration, as weather conditions significantly influence readings. During the rainy season, the lowest temperature recorded was 27.10°C, while the highest temperature during summer reached 29.32°C, demonstrating the system’s adaptability across seasons.
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Li, Qiaoyi, Yanling Xiong, Wenlong Yang, Junsheng Han, and Huan Liang. "Study on Color Analyzer based on the Multiplexing of TCS3200 Color Sensor and Microcontroller." International Journal of Hybrid Information Technology 7, no. 5 (2014): 167–74. http://dx.doi.org/10.14257/ijhit.2014.7.5.15.
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Prabowo, Sulistyo, Chandra Kadwa Utama Sutrisno, Krishna Purnawan Candra, Anton Rahmadi, and Yuliani Yuliani. "Colorimeter design for dry food-products inspection using TCS3200 sensor and Arduino Mega-2560." Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering 6, no. 2 (2023): 134–41. http://dx.doi.org/10.21776/ub.afssaae.2023.006.02.4.
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This report describes the successful construction of a Colorimeter CK20.1 prototype using a TCS3200 sensor based on the Arduino Mega-2560 microcontroller for solid foodstuffs inspection. The sample color exposed is presented in RGB form. In this experiment, a commercial colorimeter (ColorFlex EZ Spectrophotometer, with the output, is in L*a*b* form) was applied as a validator of the prototype quality performance on color reading for green beans, wheat flour, palm sugar, ground coffee, and cocoa powder. Data were analyzed for mean comparison using t-test or Mann-Whitney for normally or not normally distributed data, respectively. Before data analysis, the RGB data provided by the prototype was transformed to L*a*b* by the template available from colormine.org and vice versa for the data provided by the ColorFlex EZ. The results showed that color component measurement data from the Colorimeter CK20.1 prototype and the Color FlexEZ were significantly different (p<0.05) for all the foodstuffs observed; however, the color produced by each color component is likely very similar visually. Further development of the CK2.1 prototype is being done to provide a cheap and practical color detector.
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Rahady, Redwin Arie, and Shazana Dhiya Ayuni. "SELECTION OF ROUND EGGPLANT BASED ON COLOR AND SIZE BASED ON ARDUINO." Journal for Technology and Science 1, no. 2 (2024): 1–6. https://doi.org/10.61796/ipteks.v1i2.150.
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Eating vegetables is important for both humans and farmers who process them to meet consumer needs. Round eggplant is a popular vegetable because it maintains its high nutritional value even with minimal cooking, leading to increased demand. A system for sorting eggplants based on color and size using Arduino Mega is needed. The research method used is research and development to test sensor accuracy and tool reliability in accordance with the research objectives. The tool uses Arduino Mega as a microcontroller, TCS3200 sensor for eggplant color detection, and HC-SR04 sensor for object detection. During the separation process, the eggplant rounds will be moved by a conveyor using a DC motor. In the last step, the tool will direct the round eggplant into the container based on its color and size using a servo motor
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Ulhaq, Nida Dhia, Irma Salamah, and Suroso Suroso. "IoT-Based Cooking Oil Quality Monitoring System Using Thresholding Method on Android Application." ITEJ (Information Technology Engineering Journals) 10, no. 1 (2025): 109–18. https://doi.org/10.24235/itej.v10i1.233.
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Repeated use of cooking oil can reduce its quality and have a negative impact on health, but these changes are difficult to recognize with the naked eye. This research aims to develop an Internet of Things (IoT)-based cooking oil quality monitoring system with a thresholding method connected to an Android application. The system is equipped with a TCS3200 sensor to detect color, an LDR sensor to measure clarity, and a pH sensor to monitor oil acidity. The readings from the three sensors are used to classify the oil quality into three categories : good, medium, and unfit. The final classification is determined using unified decision logic based on the majority values from the sensors. Tests were conducted on six oil samples with a reading frequency of 60 times per sample. Data was sent in real-time to firebase and displayed through an android app. In addition, the system sent automatic notifications via telegram for remote monitoring. The results show that one-time use oil is classified as good, 2 to 4 times use is moderate, and 5 times use is categorized as unfit for consumption. The system offers a practical and efficient solution for digital and real-time monitoring of oil quality.
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Watiasih, Richa, and Junior Risqy Cosabagus. "Decision-Making in Gripper Control Systems Using Fuzzy Logic Method and Telegram Application." JEECS (Journal of Electrical Engineering and Computer Sciences) 9, no. 1 (2024): 69–78. http://dx.doi.org/10.54732/jeecs.v9i1.8.
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The application of the gripper in the industrial world has facilitated human work in the sorting process but has the disadvantage of not being able to sort objects based on the object's color. Conditions like these can affect the production quality factor when sorting objects. This research resulted in a gripper end effector system using the fuzzy method and the telegram application as a control, which has a function to distinguish the color of objects gripped by the gripper, thereby minimizing errors in sorting objects based on color. Telegram is used because the application is relatively light and can be accessed anywhere as long as it is connected to an internet connection. This study uses the fuzzy logic method as a decision-making process. The fuzzy method is used because it is very flexible and has a tolerance value in the existing data. The telegram function in this study is the main control to give orders to the gripper. The TCS3200 color sensor, in this study, is used to detect object color. The TCS3200 sensor converts the light intensity value to 8 bits so that the microcontroller can read it for each color in the test. The colors red, green, and blue were chosen as a reference because they are the primary or basic colors of all colors. From the results of testing the entire system in this study, 90% success was obtained in moving objects precisely based on the object's color. This result is enough to prove that the system can work properly.
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Mohammad Nur, Ahmad Mustofa, and Rikawulandari. "The Design of a Tobacco Quality Detection Tool Using K-NN Classification Method." E-JOINT (Electronica and Electrical Journal of Innovation Technology) 5, no. 2 (2024): 43–47. https://doi.org/10.35970/e-joint.v5i2.2477.
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Tobacco is an important commodity on Madura Island, where farmers process it into shredded tobacco sold to middlemen. The quality of the shredded tobacco significantly affects its selling price, determined by factors such as color, aroma, leaf elasticity, and handling. Currently, quality assessment still relies on manual methods dependent on the sensory perceptions of experts. However, the physical and emotional instability of these experts can disrupt the accuracy of these evaluations. To solve this issue, there is a need for a tool that can automatically detect tobacco quality without relying on manual observation. This tool is designed using a series of sensors, including the TCS3200 for color analysis and MQ sensors (MQ4, MQ135, MQ138) for detecting aroma components. The output from these sensors is in the form of ADC values, which are then processed as training data. The K-NN (K-Nearest Neighbors) method will be applied to classify tobacco quality into three categories: low, standard, and good. The distance calculation uses the Manhattan Distance formula with a parameter of K=4, ensuring more accurate results. With this tool, the assessment of tobacco quality becomes more consistent and reliable,because reducing the risk of inaccuracies due to human factors.
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Sasmoko, Dani, Danang Danang, Padjar Setyo Budi, and Muhammad Agus Kurniawan. "Penggunaan Sensor TCS3200 dan NodeMCU untuk Mendeteksi Warna Daun Padi dalam Menentukan Jumlah Pupuk Urea Bebasis IoT." Elkom : Jurnal Elektronika dan Komputer 13, no. 1 (2020): 87–102. http://dx.doi.org/10.51903/elkom.v13i1.174.
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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.
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Wisjhnuadji, T. W., Arsanto Narendro, and Pribadi Wicaksono. "Sistem Sortir Barang Otomatis Berbasis Arduino Dengan Sensor Warna Dan Monitoring Via Android." Faktor Exacta 13, no. 2 (2020): 106. http://dx.doi.org/10.30998/faktorexacta.v13i2.6586.
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<p>The Arduino-based sorting system is equipped with a color sensor and the monitoring of the number of goods via Android is a series of tools that serves to ease the work process of sorting goods by color manually at certain industrial companies. The method used to realize the problem above is by making a prototype of the sorting tool based on color automatically and monitoring the results of the sum of the items as connecting information from the device to Android. The tool is equipped with a TCS3200 color sensor as a color detector, an infrared sensor as an object counter, a DC motor and conveyor as a driving medium, a Servo motor as a sorting media, Arduino as a control media, and ESP8266 as a communication media and Android as a monitoring media. The results of test have been carried out on the prototype of this system, and are able to provide results in accordance with the design specifications of the tool.</p><p>Keywords: arduino, android, sensor warna, sensor infrared, motor DC, motor servo, ESP8266</p>
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Kurniadi Wardana, Humaidillah, Elly Indahwati, and Lina Arifah Fitriyah. "Measurement of Non-Invasive Blood Glucose Level Based Sensor Color TCS3200 and Arduino." IOP Conference Series: Materials Science and Engineering 336 (April 2018): 012019. http://dx.doi.org/10.1088/1757-899x/336/1/012019.
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