In the era of informatization and population aging with rapidly advancing technology, nursing homes also pursue ‘smart systems’ to provide better care for elderly people. Although several smart systems have been implemented in care services for elderly people, there has not been an appropriate evaluation method for smart monitoring systems that can be used for nursing homes. Therefore, we developed an evaluation system considering recent technologies such as the Internet of Things, artificial intelligence, and sensor technology. Using the decision experiment and evaluation laboratory (DEMATEL) method and the analytical network process (ANP), the indicators for the evaluation of the smart monitoring system were defined by invited experts from diverse industries. As a result, four Level 1 indicators (system equipment capability, system stability, sensor configuration, and data processing) and 12 Level 2 indicators [sensing device frequency, life monitoring assistance, emergency response capabilities (system equipment capability), system running efficiency, system failure rate, system durability (system stability), assisted living device coverage, safety protection, emergency detection and alert (sensor configuration), and health data monitoring accuracy, health data acquisition speed, and health data analysis ability (data processing)] were determined. For the operation of the smart monitoring system, data processing capability and system stability were important, while system running efficiency, safety protection, emergency detection alert, and health data monitoring accuracy were important indicators for the evaluation of the system. The importance of the indicators was confirmed by the results of the evaluation of pension institutions in Suzhou City, China, which were selected by the constructed evaluation method and ArcGIS, a geographic information system (GIS) software. The results of this study indicate that the importance of sensor technology must be considered in the establishment and evaluation of smart monitoring systems for nursing homes. The results also provide a reference for the development of other smart systems for diverse purposes.