Milk adulteration impairs food safety and public health and is a major issue in the less privileged regions of the world, where the monitoring of quality is minimal. An enhanced Internet of Things (IoT)-enabled milk adulteration detection system that conjoins a multispectral sensor AS7265x and an electrical conductivity (EC) sensor with the ESP32 microcontroller for real-time, reagent-free analysis is presented in this research paper. The AS7265x sensor with 18 spectral channels ranging from the visible to near-infrared (410–940 nm) can quickly detect the change in milk optics caused by the contamination of water, detergent, and urea. The EC sensor changes the analysis by measuring ionic concentration changes, thus offering a dual-parameter approach that improves detection accuracy. The ESP32 module, after processing the sensor data, transmits it wirelessly to the Blynk IoT dashboard for easy monitoring and data visualization. The experimental results show that the hybrid system proposed outperforms the existing optically detection methods in terms of sensitivity and reliability, while portability and low power consumption are maintained. Such a smart sensing architecture gives a practical and scalable way of supporting food safety and supply chain transparency through on-site milk quality checks