The IEEE Smart Cities Newsletter, an online publication features practical and timely technical information and forward-looking commentary on Smart Cities developments and deployments around the world.  Designed to bring clarity to the global Smart Cities industry and to foster greater understanding and collaboration between diverse stakeholders, the newsletter brings together experts, thought-leaders, and decision-makers to exchange information and discuss issues affecting the evolution of the Smart Cities.   

This Web Portal ( is home to the Newsletter.  The IEEE Smart Cities Newsletter strives to publish articles in a timely fashion and offers a rigorous review process to ensure the highest quality publication for your work.  Each month the recently published articles are proactively promoted through the broad array of IEEE communications vehicles.

IEEE Smart Cities Author Guidelines are available online.

Current Articles (July/August 2019)

Traffic management systems, which aim to provide measures for sustainable and optimal traffic on road network, require monitoring the traffic flow. Traffic flow is commonly monitored using sensors that are deployed on roads, such as inductive loops or camera systems . Due to high cost of installation and maintenance for such sensor systems, it is impractical to cover traffic networks with an adequate number of sensors. The information shared on social media by users or ”human sensors” as commonly referred, can complement or replace the data provided by physical sensors, as a sustainable source of data. Twitter, where 313 million active users send an average of around 500 million tweets a day, is used as a data source to evaluate the methods proposed [1][2]. Our observations show that among other topics and daily issues, tweets cover the road and traffic flow conditions, as well.  

Multi-Agent Systems (MAS) is a paradigm derived from the distributed artificial intelligence field that offers an alternative way to design complex large-scale systems by decentralizing the control system by distributed, autonomous and cooperative entities [1]. It mainly differs from conventional approaches due to its inherent capabilities to adapt to emergence without external intervention. The MAS concept is usually pointed out as a suitable approach and technology to distribute intelligence in applications from smart production, smart logistics, smart health, smart cities and smart electrical grids. Industrial agent-based solutions, aligned with the Cyber-Physical Systems (CPS) perspective, impose additional requirements namely in terms of flexibility, robustness, scalability and responsiveness to industrial automation systems.


Past Articles (March/April 2019)

More than 120 people from 20 countries particpated in the 2nd annual event held in Genk , Belgium.

Enhancing the resilience of power grids to high-impact, low-probability events, such as extreme weather event due climate change, is of great important for constructing a smart grid and a smart city. Compared with expensive and high-cost power infrastructures hardening strategies, the economic smart control and operation strategies are easier to implement and welcome by power producers and consumers. This letter introduced a smart grid techniques-based defensive scheme of network failure by natural disaster, which have three layers, including information collection layer, component fault probability assessment layer and coordinating and decision system. As a result of information technology advancement and its deep integration with the electric power industry, smart grid techniques play an essential role in power system resilience enhancement. A resilient and smart grid forms a solid foundation to build a smart city.

Due to the unprecedented scale and speed of urbanization, cities are facing the daunting task of  accommodating the urban dynamics. One of the critical service requirements of future cities is the safety management for citizens and communities

As distributed energy resources (DER) deployment by households and communities continues to grow in many cities, city planners are struggling to integrate them into both energies yet also wider infrastructure (such as transport) planning and implementation in the smartest way. To best address these challenges, smart infrastructure planning strategies should align both design and operation objectives to achieve allocative efficiency and revenue adequacy to optimize social welfare for households and communities, and to incentivize customer participation and private investments.  The integration and coordination of distributed community resources can be best undertaken through multi-level energy management systems (EMS) at both the household and the community level that work with each other to achieve wider power system, network and community goals

Due to the large number of non-standard building addresses and the semantic ambiguity of addresses expressed in Chinese natural language, traditional methods based on string matching are difficult to meet requirements. To address these problems, we propose an innovative joint learning approach based on the hash map principle and the word frequency theory for standardizing Chinese non-standard building addresses. Our experimental results on a real-world dataset constructed via the crowdsourcing technology show that our approach has an outstanding accuracy and the adaptability for utilizing data from different sources.

Past articles are available via the IEEE Smart Cities Resource Center.  Content in the IEEE SC Resource Center is complimentary to members of the Smart Cities Partners Organizations (ComSoc, CSS, IAS, PES, SMCS).  IEEE members who are not members of the IEEE SC partners can access the material at a reduced cost.