<![CDATA[Fruit sorting based on ripeness and weight is still largely done manually, which poses a risk of inaccuracies, delays, and labor inefficiencies. This research aims to design and implement an automatic mango sorting system that can detect ripeness levels (raw, ripe, rotten) and measure the weight of the fruit. This system uses TCS3200 color sensors, a 20 kg Load Cell weight sensor, and is controlled by an ATMega328P microcontroller. A 20x4 LCD module is used as a user interface. The methods used include acquiring RGB value and weight data, classifying ripeness levels based on predetermined color thresholds, and real-time weight data processing. Testing results show that the system can accurately identify the skin color of mangos and display the weight with an average deviation of ±0.05 kg. This prototype has been proven to improve the accuracy, speed, and efficiency of the sorting process compared to manual methods. The developed tool is a tangible step towards the implementation of smart agriculture, particularly in the post- harvest process, and has the potential for further development in other fruit types.]]>
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