Towards a Digital Ecosystem for a Smart City District: Procedure, Results, and Lessons Learned

Abstract

The digital transformation supports many cities on the way to becoming smarter cities, enabling them to enhance digital processes, care about climate-friendly goals, or improve the quality of life of their citizens. However, such changes usually take place step by step and not in a big-bang approach. In order for the direction of the digital transformation to be defined, it is necessary to know and understand the needs and requirements of all relevant stakeholders who will be affected or are intended to use the new digital solutions. As our environment, a smart city district, is currently under construction, we do not know most of the future stakeholders yet. Therefore, we had to find new ways of eliciting the needs and requirements for digital solutions without knowing, e.g., the citizens who will live in the future district. We show a framework of the procedures we followed, classified into (a) vision and concepts, (b) smart city district digital ecosystem, and (c) dissemination and events. We substantiate the processes with example results and provide a discussion on how we evaluate our solutions with respect to future applicability. Because evaluations are only very limited in our setting right now, we focus on four lead questions to argue why the procedures and results are adequate and share the lessons we learned on this path towards a digital smart city district.

The Use of Robotic Process Automation (RPA) as an Element of Smart City Implementation: A Case Study of Electricity Billing Document Management at Bydgoszcz City Hall

“…The Los Angeles Community Analysis Bureau used cluster analysis and infrared aerial photography to produce reports about demographic data and housing quality [38]. A virtual digital city implemented in Amsterdam in 1994, where internet access was provided to a large group of citizens for the first time, could be considered the next milestone [1,39,40]. Smart city research picked up steam in 2000 when multinational technology conglomerates spent hundreds of millions of US dollars in order to gain detailed knowledge and experience in urban topics [41].…”

“…Currently, it constitutes an answer to challenges related to progressing urbanization; the growing requirements of the public with respect to more productive and, at the same time, sustainable urban services; and to the improvement of quality of life [44]. As indicated by Elberzhager et al [40], one of the most often cited works related to the smart city is the paper written by Giffinger and others [45]. It enumerates smart city dimensions: smart economy, smart people, smart management, smart mobility, smart environment, and smart living.…”

“…Furthermore, it defines a smart city as being "a city well performing in a forward-looking way in these six characteristics, built on the 'smart' combination of endowments and activities of self-decisive, independent and aware citizens." According to Elberzhager et al [40], the other frequently used approach to a smart city is provided in a paper by Yang et al [46]. They note that there are "six application domains for smart cities: natural resources and energy, transportation and mobility, building and infrastructure, living, governance, industry, and human resources".…”

“…In contrast, the approaches related to technology-primarily digital technology-are aimed at improving the efficiency of services and infrastructure (for example, communications, transportation, and supplies). The evolution of the perception of digital technologies in the context of developing smart cities has been emphasized in [40]. A number of smart city projects carried out earlier this decade were focused on developing smart infrastructure (equipped with sensors).…”

“…The most important among these may include, inter alia, the risk of perceiving the whole idea of robotic automation wrongly (solely through the prism of reducing the costs related to human resources), the risk related to choosing the wrong robotic automation approach within the given organization, the risk related to choosing the wrong robotic automation tool, the risk related to using the wrong approach to changing management within robotically automated processes, the risk related to push-back from staff engaged in the robotically automated processes, and the risk of having a competence gap [33] (pp. [37][38][39][40][41][42]. Additional risk factors may also include a continued high proportion of hardcopy documents that are entered as input to the robotically automated processes (this is a material constraint as it requires the use of OCR software); a lack of up-to-date and codified knowledge about the actual course of the business processes, in particular with respect to how exceptions that occur during business processes should be dealt with; and a lack of coordination for changes in the systems that a robot is operating on, which results in emergency stoppages.…”