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Over the years, researchers have explored various approaches for capturing and monitoring the eating activity, one among which is via Wi-Fi channel state information (CSI). CSI-based approaches commonly rely on multi-antenna systems for the capturing and monitoring tasks. With the advent of low-cost, single-antenna IoT devices with CSI measuring capabilities, a question that arises is whether these inexpensive devices can monitor human activities? In this paper we present the SandDune system that demonstrates the possibility of monitoring one human activity–eating–using only inexpensive single-antenna Wi-Fi devices. SandDune is an infrastructure-based system that continuously monitors CSI information to detect the eating activity occurring in its vicinity. When it detects an eating activity, it scrutinizes the signals further to identify all hand-to-mouth eating gestures in the eating episode. We tested SandDune and observed that SandDune can distinguish eating from other activities with an F1-score of 85.54%. Furthermore, it can detect the number of hand-to-mouth gestures that occurred in the eating episode with an error of ±3 gestures. Overall, we believe that a SandDune-like system can enable low cost, unobtrusive eating activity detection and monitoring with potential use-cases in several health and well-being applications.