The human body cannot work properly without water. Therefore, it is essential to conduct testing and monitoring of drinking water quality to ensure its safety and suitability for consumption. This has prompted researchers to develop more efficient systems compared to traditional methods. This study employs a systematic literature review approach by analysing various published articles to identify and evaluate the application of different types of sensors capable of detecting physical and chemical parameters for assessing drinking water quality. The findings indicate that the integration of sensors, microcontrollers, and Internet of Things (IoT) technology can provide accurate data that is accessible in real-time and remote locations. Furthermore, to enhance the reliability of the system, it is necessary to further develop data processing algorithms by applying artificial intelligence (AI) and/or machine learning technique to create smart systems with improved predictive capabilities. The implementation of these technologies is expected to support the Indonesian government’s Sustainable Development Goals (SDGs) by providing safe and affordable access to drinking water for all its citizens.