Fixed-point arithmetic is central to embedded signal processing where resources and power are often strictly limited. This article explains how Qm.n notation represents numbers with integer and fractional bits, highlighting range and resolution constraints. It discusses the trade-offs between floating-point’s easier development and fixed-point’s hardware cost savings. Examples illustrate clipping, saturation, and rounding techniques for converting between floating and fixed-point. A detailed walk-through of converting Celsius to Fahrenheit in Q10.6 format shows how to preserve precision under hardware constraints. Practical code snippets for FIR and IIR filter implementations in C and Python further demonstrate fixed-point’s capabilities across real-world DSP applications.