654 ITU‐T's Technical Reports and Specifications 1 Introduction 1.1 Background \"A smart sustainable city is an innovative city that uses information and communication technologies (ICTs) and other means to improve quality of life, efficiency of urban operation and services, and competitiveness, while ensuring that it meets the needs of present and future generations with respect to economic, social, environmental as well as cultural aspects\". The above definition describes what a smart sustainable city should be. However, significant urban challenges – such as security, criminality, pollution, traffic congestion, inadequate infrastructure, response to natural hazards – still prevent this vision to become reality. Some examples of the challenges faced by cities are listed in Figure 1. Figure 1 – Examples of challenges faced by cities In order to successfully address these challenges, cities should take into consideration the deployment of the necessary tools to be able to monitor, map and report what is happening in real time. An effective reporting mechanism will ensure that such problems are tackled rapidly to avoid or reduce possible causalities and economic losses [b‐Namb]. As part of a recent widespread urban digitalization process, several cities have deployed a variety of sensors, including cameras, rain gauge, and pressure transducer, etc., to be able to acquire first‐hand information about all city's operations in a timely manner. Even if all this information is available in cities, it is unfortunately distributed in different departments or even regions. Nonetheless, an effective management mechanism is still lacking. In response to this challenge, this Technical Report proposes an integrated management solution for smart sustainable cities. With IMSSC, the sensors, nodes, and models can function in an organized way. As a result, when emergency events occur, the data, models and other resources needed can be rapidly discovered and acquired. To achieve the goal of making a city smarter and more sustainable, the first step is to analyse real‐time processes and understand event patterns