The integration of information and communication technologies (ICT), wireless sensor networks (WSNs), devices of Internet of Things (IoT), artificial intelligence (AI), machine learning (ML), edge computing and other technologies within a city for sustainable development of the territory and improvement of citizens’ wellbeing created the concept of a smart city. Long-term sustainable development of smart city is possible only if several components are balanced, including economic, social and environmental ones. Greenery like parks, squares, gardens and green zones are important part of the ecological component and environment of the city. Worsening of greenery state leads to worsening of the environment and vice versa, therefore, it is important to monitor constantly greenery state. In many smart cities, as the analysis showed, monitoring and estimation of the greenery state is performed via visual or remote observations, measurements of climatic parameters. Although comprehensive information about plants’ state and influence of stress factors can be obtained by estimating one of the main indicators of plant life, namely photosynthesis. The task in the paper is the development of the architecture of a smart system for the estimation of greenery, applicable for integration into the smart city, based on the developed own sensors, devices and wireless networks for express diagnostics of plants’ state by the method of chlorophyll fluorescence induction. A feature of the system is the integration of devices at the edge, which process the acquired data and make management decisions near monitored objects.