The paper aims to explore the intricacies of scent identification, conducting comprehensive research to uncover the underlying mechanisms of various odors. The main focus is on investigating the development of an effective aroma detection system capable of distinguishing between different scents, at a smaller scale. By integrating disciplines like signal processing, Machine Learning, and olfactometry, the aim is to gather insights that hold relevance across diverse sectors, including but not limited to food, safety, and environmental monitoring. Through experimentation and analysis, this paper seeks to shed light on the significance of scent detection through a cost-effective method.