Smart cities initiatives, challenges and software architecture

Abstract:

The research on the green roof is of great importance in the field of urban beautification and improving ecological effect. According to the previous research, plants have shown a significant impact on the absorption of PM2.5. Therefore, it is justified that the appropriate planting design or some particular combinations of plants can be considered as a solution, dealing with the urban fine particulate matter (PM2.5). This paper presented a work in progress on developing wireless sensor networks (WSN) system based on a prototype wind tunnel, which is used for the simulation of the green roof. Several data collection processes are handled by this system, where the concentration of PM2.5, wind speed, temperature & relative humidity are obtained and stored in the database simultaneously. Additionally, users are able to real-timely define their commands in details, controlling the sensor's height through a GUI on the website. Experimental and simulation results and measurements have verified the validity of the wind tunnel module as well as the reliability of the sensor network. The system can be operated on thousands of devices when the packet delay maintained in a low level.

 

A mapping study on living labs: Characteristics, smart cities initiatives, challenges and software architecture aspects  

Abstract:

A Living lab (LL) allows the development of systems in a user-driven fashion in realistic environments. Despite the idea behind LL is promising, its development is still an open problem. This occurs in part because the concept of LL is still in development, does not have clear boundaries, and the discussion around the theme transcends many disciplines. We have faced some of these uncertainties when a customer asked us to develop a LL environment for Smart Cities. This scenario motivated us to perform a mapping study with the purpose of characterizing LLs, their challenges, domains where they can be applied, and software architecture aspects related to the theme. As result, 51 primary studies were identified and six aspects of them were analyzed: LL characteristics, application domains, LLs smart cities initiatives, challenges, and current evidence on software architecture for LL. The results are beneficial for both researchers and practitioners. For researchers, this work provides information about the current status of LL research, as well as topics that require further investigation. For practitioners, the paper discusses challenges that they need to be prepared to face when developing LLs, as well as aspects related to software architecture and considered application domains. The organized set of information can support development teams on the conception of new LLs.

How to Create a Smart City: Future-Proofed Cities That Foster Growth and Innovation  

Abstract:

As SMART CITY technology advances, smart cities around the world are maturing, and, with all of the critical components in place, even more cities are vying to become smart. The Internet of Things (IoT) is the driver of growth in this market, and a prediction by Cisco says that it will be a US$14.4 trillion industry by 2020 (Berthon 2015). The technologies for building a smart city are maturing, and the standards on which to build one have been proven in practice. Ultimately, for any city, the goal is to achieve substantial benefits for its citizens and to build a future-proofed platform that can scale with the projected growth of network end points and applications. That was once a formidable challenge, but, today, it's a realistic and realizable goal.

Artificial intelligence framework for smart city microgrids: State of the art, challenges, and opportunities  

Abstract:

Smart city concepts have gained substantial attention over the last few years, as they apply advances in Information and Communication Technology (ICT) to enhance the quality and efficiency of services and resources. Microgrids are potentially powerful building blocks in the development of smart cities. Motivated by the opportunity, this article examines the factors leadings to the adoption of microgrids for mainstream electrical utilities grids, discusses the benefits that drive the growth, identifies the issues hindering benefit-capture of distributed energy generation inside microgrids, and provides a framework for the application of Artificial Intelligence (AI) to overcome challenges. We examine a simulation framework scenario and useful data sources that can help build AI capabilities within utilities. A brief description of the scalable BluWave-ai framework that leverages deep learning in the data centre is also provided, and AI inference at edge computing nodes and IoT sensors to optimize the benefits from microgrids at residential, neighbourhood, campus, enterprise and community levels is examined.