Noncontact displacement measurement is widely used in experimental mechanics; however, many optical techniques rely on high-end imaging hardware and external computing resources, limiting their applicability in low-cost laboratory setups. In this paper, we present a compact, affordable (<USD 240) embedded system for lateral displacement measurement based on active Moiré patterns, integrating a mini projector, a camera, and a Raspberry Pi platform acting as an IoT edge node for wireless data transmission. The system estimates displacement through image-based analysis, utilizing both spatial and reference-based empirical calibration against a physical grating to mitigate optical distortions. Experimental validation was performed for lateral displacements in the range of 0–12 mm using a digital indicator as a reference. The results show a consistent linear response with a correlation coefficient of 0.98, a mean absolute error of 0.207 mm, a root mean square error of 0.235 mm, and a mean standard deviation of 0.033 mm across repeated measurements. Rather than competing directly with state-of-the-art Moiré approaches that demand high-end industrial cameras and sub-micrometer precision, we prioritize affordability, versatility, and real-world deployability. The main contribution of this work lies in providing an accessible IoT edge architecture capable of modernizing legacy manual equipment in resource-limited or educational laboratories. The achieved 0.2 mm resolution is demonstrated to be robust and sufficient for automated, quasi-static displacement monitoring in practical compression testing scenarios, effectively bridging the gap between advanced optical metrology and low-cost industrial monitoring.