Olive oil is a traditional and ancient food, essential to the Mediterranean diet and popular worldwide for its nutritional and health benefits. High-quality extra virgin olive oil (EVOO) can only be made from healthy, fresh olives at the right ripeness. Determining the ideal ripeness is crucial for balancing the oil’s chemical, sensory, and stability properties. To find a simple and cost-effective way to measure phenolic content in olives, many methods have been developed. Recently, acoustic sensors have gained interest in food science, especially for oil and wine production. This study aims to create an acoustic wave-based platform to quickly detect polyphenol content in olives and to determine their ripeness. The sensing platform could provide fast, on-site assessments of olive quality, unlike the current method of sending samples to a lab and waiting for results. Using reliable and affordable tools to determine olive ripeness can help producers to harvest at the right time, improving EVOO quality. The device could also be used in industrial milling plants to evaluate and classify olives, preventing the mixing of low and high-quality olives and optimizing the extraction process. Additionally, the sensing platform could be integrated into mechanized sorting systems and blockchain technology to certify olive ripeness, ensuring product quality, improving farming practices, and planning better harvesting strategies. This would lead to more efficient farming and higher-quality production.